dengue who 2016

ISSN 0250-8362
The WHO Regional Office for South-East Asia publish the annual Dengue Bulletin.
All manuscripts received for publication are subjected to in-house review by
professional experts and are peer-reviewed by international experts in the
respective disciplines.
Dengue Bulletin
The objective of the Bulletin is to disseminate updated information on the
current status of dengue fever/dengue haemorrhagic fever infection, changing
epidemiological patterns, new attempted control strategies, clinical management,
information about circulating DENV strains and all other related aspects. The
Bulletin also accepts review articles, short notes, book reviews and letters to the
editor on DF/DHF-related subjects. To provide information for research workers and
programme managers, proceedings of national/international meetings are also
published.
2016
Volume 39, December 2016
Dengue
Bulletin
Volume 39, December 2016
WHO
I S SN 0250- 8362
From the Editor’s Desk
Dengue has become one of the fastest spreading diseases with half of the world population being
at risk and millions of infections and taking thousands of lives every year. Dengue is endemic in ten
out of eleven countries in WHO South-East Asia Region, with the exception of Democratic
Republic of Korea. In the year 2015, a total of 428 287 cases of dengue were reported from WHO
SEA Region. This amounts to more than 50% increase compared to the previous year. With large
outbreaks in several countries, the year 2015 saw the largest number of reported cases in the
region. However, the case fatality rate went down from 0.47 to 0.36 compared to the previous
year, reflecting sustained efforts of the countries to strengthen the capacity to manage clinical
cases of dengue.
Considering the dramatic increase in incidence and ability to cause large outbreaks affecting
mass population, especially in bigger cities, dengue has already been identified as a major public
health problem in many countries. The frequency and increasing magnitude of dengue outbreaks
have gained much attention of media, general public and research community. The research
community has been engaged on several research activities covering wide range of dengue
spectrum and transmission dynamics. In line with this priority, every year Dengue Bulletin is
published encouraging researchers to explore different aspects of the disease and contribute to
the knowledge gap and evidence base for combating the rapid spreading of this deadly disease.
The 39th volume of Dengue Bulletin has captured the recent researches on clinical
management, possible association with genetics and pathological factors, surveillance system,
software application, role of dengue vaccine and a book review. We hope these peer reviewed
articles will help the policy makers , programme managers, physicians and researchers to make
scientifically proven, cost effective efficient decisions in future.
We now invite contributions for Volume 40. The deadline for receipt of contributions is
30 June 2017. Contributors are requested to please pursue the instructions given at the end of the
Bulletin while preparing the manuscripts. Contributions should either be sent accompanied by
flash drives to the Editor, Dengue Bulletin, WHO Regional office for South East Asia, Mahatma
Gandhi Road, I.P. Estate, Ring Road, New Delhi 110002, India, or by email as a file attachment to
the Editor at [email protected]. Readers who want copies of the Dengue Bulletin
may write to the same address or the WHO Country representative in their country of residence.
The pdf version will be available on the WHO SEARO website.
Dengue
Bulletin
Volume 39, December 2016
ISSN 0250-8362
© World Health Organization 2016
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Contents
Acknowledgements................................................................................................... iii
1.
Genetics of susceptibility to severe dengue virus infections: an update and
implications for prophylaxis, prognosis and therapeutics.................................... 1
Kalichamy Alagarasu
2.
Temporal spatial distribution of dengue and implications on control in
Hulu Langat, Selangor, Malaysia...................................................................... 19
Zahir Izuan Azhar, Ahamad Jusoh, Syed Sharizman Syed Abdul Rahim,
Mohd Rohaizat Hassan, Nazarudin Safian, Shamsul Azhar Shah
3.
Pathogenesis of dengue associated haematological dysfunction........................ 32
Nitali Tadkalkar, Ketaki Ganti, Kanjaksha Ghosh, Atanu Basu
4.
Phylodynamics of dengue viruses in India vis-à-vis the global scenario............. 41
Sarah S Cherian and Devendra T Mourya
5.
Association of dengue symptoms with haematological parameters:
a retrospective study of 10 hospitals in India.................................................... 62
BK Tyagi, S Karthigai Selvi, Vidya Chellaswamy, NK Arora, Donald S Shepard, Yara A Halasa,
Mukul Gaba, Deoki Nandan, Vivek Adhish, T Mariappan, P Philip Samuel, R Paramasivan,
and the INCLEN Study Group
6.
Estimation of burden using active dengue sentinel surveillance and
fever surveillance............................................................................................. 78
Zinia T Nujum, Achu Thomas, Vijayakumar K, Thomas Mathew, Saran S Pillai
7.
Identification of key containers of Aedes breeding – a cornerstone to
control strategies of dengue in Delhi, India...................................................... 87
B.N. Nagpal, Sanjeev Kumar Gupta, Arshad Shamim, Kumar Vikram, Anushrita, Himmat Singh,
Rekha Saxena, V.P. Singh, Aruna Srivastava, Babita Bisht, N.R. Tuli, R.N. Singh and Neena Valecha
8.
A comprehensive report of dengue activity in Kolkata, India –
a four-year profile.......................................................................................... 100
Tanuja Khatun, Shyamalendu Chatterjee
Dengue Bulletin – Volume 39, 2016
i
9.
Impact of dengue vaccination: a public health perspective............................ 111
Tikki Pang, Daniel Goh Yam Thiam, Maria Rosario Capeding, Sri Rezeki Hadinegoro,
Sutee Yoksan, Terapong Tantawichien, Zulkifli Ismail, Usa Thisyakorn and Tippi K. Mak
10. Dengue and dengue haemorrhagic fever....................................................... 117
(2nd Edition; Edited by Duane J. Gubler, Eng Eong Ooi, Subash Vasudevan and
Jeremy Farrar. 2014)
11. Instructions for contributors........................................................................... 121
ii
Dengue Bulletin – Volume 39, 2016
Acknowledgements
The Editor, Dengue Bulletin, World Health Organization (WHO) Regional Office for South-East
Asia, gratefully thanks the following for peer reviewing manuscripts submitted for publication.
1.
2.
3.
4.
Baruah, Kalpana
Joint Director
National Vector Borne Disease Control
programme
Sham Nath Marg
Delhi-110 054, India
Biswas, Ashuthosh
Professor, Department of Medicine
All India Institute of Medical Sciences
New Delhi, India
Dash, A.P
Vice Chancellor
Central University of Tamil Nadu
Thiruvarur, India
Gubler, Duane J
Programme on Emerging Infectious Diseases
Duke-NUS Graduate Medical School,
Singapore 169857
5.
Hoti, S.L
Scientist ‘G’ and Director-in-Charge
Regional Medical Research Centre (ICMR)
Karnataka, India
6.
Jambulingam, Purushothaman
Director Vector Control Research Centre
Medical Complex, Indira Nagar
Puducherry-605006, India
7.
Kalayanarooj, Siripen
Former Director, WHO Collaborating Centre
for Case Management of Dengue/ DHF/ DSS
Queen Sirikit National Institute of Child Health
Bangkok, Thailand
8.
Mourya, D.T.
Director
National Institute of Virology
Dr Ambedkar Road
Pune-411001, India
9.
Nagpal, B.N
Senior Scientist “G”
National Institute of Malaria
New Delhi, India
10. Sharma, R.S.
Additional Director
National Centre for Disease Control
New Delhi, India
11. Shepard, Donald S
Schneider Institutes for Health Policy
Brandeis University
Massachusetts, USA
12. Thisyakorn, Usa
Faculty of Tropical Medicine
Mahidol University
Bangkok 10400, Thailand
13. Tyagi, B K
Scientist and Director
Centre for Research in Medical Entomology
Chinnachokkikulam
Madurai-625002, India
14. Velayudhan, Raman
Coordinator
Vector Ecology and Management Unit
Department of Control of Neglected Tropical
Diseases
WHO, Geneva
15. Yadhav, Rajpal
Vector Ecology and Management Unit
Department of Control of Neglected Tropical
Diseases
WHO, Geneva
The quality and scientific standing of the Dengue Bulletin is largely due to the conscious
efforts of the experts and also to the positive response of contributors to comments and
suggestions.
The manuscripts were reviewed by Dr Aditya P Dash and Dr Mohamed A Jamsheed, with
respect to format; content; conclusions drawn, including review of tabular and illustrative
materials for clear, concise and focused presentation; and bibliographic references.
Dengue Bulletin – Volume 39, 2016
iii
Genetics of susceptibility to severe dengue virus
infections: an update and implications for prophylaxis,
prognosis and therapeutics
Kalichamy Alagarasu#
Dengue/Chikungunya Group, National Institute of Virology, 20A, Dr Ambedkar Road,
Pune-411001, Maharashtra, India
Abstract
The clinical outcome of dengue virus (DENV) infection is influenced by variation in the human
and viral genes. Genetic susceptibility to severe forms of dengue involves multiple genes that
contribute to the innate immune recognition of the virus (genes coding for entry receptors and
pattern recognition receptors), recognition of DENV by the adaptive immune system involving
products of human leukocyte antigen genes and effector responses of the immune system (genes
affecting cytokines, chemokines and immunomodulators). Genetic susceptibility to severe dengue
is further complicated by the genetics of the virus involving multiple serotypes/genotypes, geneenvironment and gene–gene interactions. A series of prospective immunogenetic studies with
complete data on infecting serotype and immune status are warranted to delineate the complex
host–virus interactions. This might identify the genetic factors that are definitely associated with
severe dengue and could lead to the development of novel therapeutic and prophylactic measures.
This review updates the status of immunogenetics of severe dengue infections, and attempts to
identify the gaps and evolve more sensible approaches to study the genetics of susceptibility to
severe dengue.
Keywords: Dengue, severe dengue, immune response.
Introduction
Dengue and its severe forms, namely, dengue haemorrhagic fever (DHF) and dengue shock
syndrome (DSS), caused by four serotypes of dengue virus (DENV), have become a major
public health concern that is straining the health systems of both developing and developed
countries. More than 50% of the people at risk of getting infected are living in the South East
Asian Region (SEAR) of the World Health Organization (WHO). Lack of approved vaccines
#
E-mail: [email protected]
Dengue Bulletin – Volume 39, 2016
1
Genetics of susceptibility to severe dengue
and antivirals for prevention and treatment of the disease and the failure of vector control
programmes to combat the disease-carrying mosquitoes of Aedes species had contributed
to the spread and increased incidence of dengue.1
The reason why only some infected individuals progress to more severe forms of the
disease while others develop a mild form of the disease or remain asymptomatic is still elusive.
Epidemiological studies carried out during various major outbreaks and studies based on
continued surveillance have suggested the role of immune status (primary or secondary);
infecting serotypes/genotypes; sequence of infecting serotype during primary and secondary
infections; time interval between primary and secondary infections; host immune response;
and the host genetics in determining dengue disease severity2 (see Figure 1). The present
review is an attempt to compile and update the role of host genetics in determining dengue
disease severity, identify the gaps and evolve more sensible approaches to study the genetics
of susceptibility to severe forms of dengue, which will lead to findings having implications
in the prediction and treatment of severe forms of dengue.
Figure 1: Genetic factors influencing clinical outcome of dengue virus infection
2
Dengue Bulletin – Volume 39, 2016
Genetics of susceptibility to severe dengue
Genetic factors influencing clinical outcomes of DENV infection operate at different
levels of immune response (see Figure 1). They include:
(1) Entry of the virus into cells of the immune system;
(2) Recognition of the virus by the innate immune system and associated response;
(3) Recognition of viral epitopes by CD4+ and CD8+ T-cells in the context of human
leukocyte antigen (HLA) class I and class II molecules presented by antigen presenting
cells; and
(4) The effector phase of the immune response during which different effector cells
and the molecules secreted by them mediate the immune response against the
virus and its elimination.
Polymorphisms in the genes related to viral entry and
severe dengue
Dendritic cell specific intercellular adhesion molecule grabbing 3 non integrin (DC-SIGN)
helps the DENV to infect DCs while Fcγ Receptor II A (FcγRIIA) augments DENV infection
of monocytes during secondary infection through antibody dependent enhancement (ADE)
process. Single nucleotide polymorphisms (SNPs) in the genes coding for these receptors are
known to influence the expression and function of the receptors. An SNP (rs4804803) in the
promoter region of the gene CD209 that codes for DC-SIGN has been shown to be associated
with DHF in Thai and Taiwanese populations while the same SNP showed no association
with DHF in Brazilian and Indian populations.3–6 An SNP (rs1801274) in the FCGR2A gene,
which substitutes arginine with histidine in 131st position of FcγRIIa, is known to affect
binding of IgG antibodies to FcγRIIa and might influence ADE.7 The arginine variant of the
gene has been shown to be associated with protection to DHF in Vietnamese children and
a Cuban population.8-9 The histidine variant of the gene has been shown to be associated
with bleeding symptoms and persistence of clinical symptoms in the Cuban population.10 In
contrast, the same histidine variant was shown to be associated with protection to symptomatic
infection in a Mexican population11.
Polymorphisms in the genes related to innate immunity and
severe dengue
After its entry, DENV virus is recognized by pattern recognition receptors (PRR). PRRs such as
toll like receptor (TLR) -3, -7 and -8 are known to recognize RNA genome of the virus in the
endosomes and initiate the expression of antiviral response. Apart from TLRs, retinoic acid
Dengue Bulletin – Volume 39, 2016
3
Genetics of susceptibility to severe dengue
inducible gene (RIG)-1 family of receptors (RLRs) such as RIG-1 and myeloid differentiation
factor are known to recognize viral RNA in the cytosol and initiate the innate immune
response. Innate immune response culminates in the production of type I interferons (IFN),
which in turn induces the expression of antiviral proteins, including oligoadenylsynthetases
(OAS). OAS activates the enzymes that degrade the viral RNA.12 Genetic variations in the
genes coding for TLRs, RLRs, associated signaling proteins and OAS are known to affect
innate immune response and hence susceptibility to severe dengue. The so-called T allele
of rs377529, a coding region SNP in the TLR3 gene has been shown to be associated with
protection to DHF in an Indian population.13 The C/T genotype of rs669260, an intronic SNP
in DDX58 gene, which codes for RIG-1, has been shown to be associated with susceptibility
to DHF in an Indian population.14 Haplotypes of OAS (OAS1-OAS3-OAS2) gene cluster was
found to be associated with clinical outcomes of DENV infection in an Indian population.15
A recent study on OAS gene polymorphisms in a Thai population has revealed that OAS3
S381R variant, which demonstrated strong antiviral activity in cell culture, was associated with
dominant protection to shock in patients infected with DENV-2.16 In a Brazilian population,
SNPs in the gene coding for janus kinase (JAK)-1, which is a signaling protein associated with
type I IFN receptor, were found to be associated with DHF.17 In an Indian population, an
SNP (rs8177374 C/T genotype) in the coding region of the gene coding for toll-interleukin-1
receptor domain containing adapter protein (TIRAP) was found to be associated with DHF.13
Various C type lectins such as mannose binding lectin (MBL) and C type lectin domain
family member 5 A bind to DENV to initiate an inflammatory response. Deficiency of MBL,
a complement component, has shown to be associated with DHF in an Indian population.18
The wild type genotype of a coding region SNP in the MBL2 gene, associated with higher levels
of MBL, was observed to be associated with protection against thrombocytopenia in dengue
infection in a Brazilian population.19 Interaction of DENV with a CLEC5A stimulates the release
of pro-inflammatory cytokines. Blockade of CLEC5A suppresses pro-inflammatory cytokine
response and DENV induced plasma leakage in a mouse model. In a Brazilian paediatric
population, T/T genotype of an SNP (rs1285933) in the CLEC5A gene was associated with
severe dengue. It was also demonstrated that CLEC5A SNPs regulated tumor necrosis factor
(TNF)-α production in severe dengue disease.20
Complement system, which is composed of about 30 proteins, has been reported to be
an important player in the innate defence against DENV. Altered regulation of complement
activation has been implicated in dengue disease pathogenesis. Complement factor H (CFH)
is an important regulator of complement activation. CFH levels are influenced by SNPs in
the gene coding for CFH. In a Brazilian population, T allele of rs375334, a promoter region
SNP, correlated with higher levels of CFH, has been shown to be associated with protection
against severe dengue.21 In contrast, complotype involving SNPs in the genes coding for
factor B, C3 and CFH was not associated with dengue in a Thai population.22
4
Dengue Bulletin – Volume 39, 2016
Genetics of susceptibility to severe dengue
Genetic variations in natural killer cell receptors and its
association with dengue
Natural killer (NK) cells play an important role in the innate immunity against infectious
diseases. NK cells have an array of receptors to help them in discriminating between self
and non-self and regulate NK cell response. Killer cell immunoglobulin like receptors (KIR)
and major histocompatibility class I related molecules (MIC) are important among them and
are polymorphic. MICA*008 and MICB*008 alleles were reported to be associated with
symptomatic dengue in a Cuban population and the association was stronger in DF cases
versus asymptomatic controls.23 In a Brazilian population, presence of KIR2DL5 and KIR2DS1
genes were associated with DF. The AA genotype of the KIR gene complex was associated
with protection to DF.24 A study from India has shown that KIR3DL1/KIR3DS1 loci influence
the risk of developing mild DF.25
Human leukocyte antigens and severe dengue
Human leukocyte antigen (HLA) class I and class II molecules expressed by antigen presenting
cells are involved in presenting viral peptides (epitopes) to CD4+ and CD8+ T-cells and
activating them to act against virus infected cells. Humans differ in the composition of the
HLA alleles they possess and this difference contributes to the interindividual variation in
the repertoire of viral epitopes presented to the T-cells and hence the quality of the immune
response generated and susceptibility to clinical outcomes of viral infection. HLA alleles have
been shown to be associated with susceptibility to many infectious diseases.26 Numerous
studies in dengue also have implicated the association of HLA class I and class II alleles with
dengue disease severity (see Table 1).
In a Vietnamese population, HLA-A*24 allele was found to be associated with susceptibility
to DHF while HLA-A*33 was associated with protection to DHF.27 Specifically, HLA-A*24 with
histidine at codon70 was associated with severe forms of dengue while HLA-DRB1*09:01
was associated with protection to severe dengue.28 A preliminary study on HLA antigens in
DHF cases revealed the association of HLA-A1 and HLA-A9 with susceptibility to primary
DHF and HLA-B13 and HLA-B15 with protection to grade II DHF in secondary infections.29
In an ethnic Thai population, in secondary infections, HLA-A*02:03 was associated with DF
while HLA-A*02:07 was associated with DHF in DENV-1 and DENV-2 infections. Among the
HLA-B alleles, HLA-B*51 was associated with DHF while HLA-B*52 was associated with DF
in secondary infections.30 A recent study on the analysis of HLA supertypes in dengue cases
from the Thai population revealed the association of HLA-B*44 supertype with protection
to DHF and HLA-A*02 and HLA-A*01/*03 supertypes with susceptibility to DF in secondary
infections. Moreover, HLA-B*07 supertype was associated with susceptibility to DHF in
secondary infection.31 In a Sri Lankan population, HLA-B*31 and HLA-DRB1*08 alleles were
associated with DSS in secondary infection while HLA-A*24 was associated with DHF in
Dengue Bulletin – Volume 39, 2016
5
6
DHF
DF
Symptomatic
disease
HLA-B*51
HLA-B*52
HLA-B44, HLA-B62, HLA-B76 and
HLA-B77
DF
DF
HLA-A*23, HLA-Cw*04, HLADQB1*02, HLA-DQB1*03 and HLADQB1*06
HLA-DRB1*07
HLA-A*24 and HLA-DRB5*01/02
DHF
HL-A*31 and HLA-B*15
Cuba
Jamaica
DHF
HLA-DRB1*04
DHF
DF
DHF
HLA-A*02:07
HLA-DQ1
DF
HLA-A*02:03
DHF
HLA-A*33
DHF grade II
HLA-B13 and HLA-B15
DHF
DHF
HLA-A2 and HLA-B blank
HLA-A*24
DHF
Nature of dengue
disease severity
HLA-A1 and HLA-A9
Associated HLA allele/genotype/
supertype
Mexico
Brazil
Thailand
Vietnam
Thailand
Population
Protection
Susceptibility
Protection
Susceptibility
Protection
Susceptibility
Protection
Susceptibility
Susceptibility
Susceptibility
Susceptibility
Protection
Susceptibility
Protection
Susceptibility
Susceptibility
Nature of
association
Unknown
Unknown
Secondary
Secondary
Overall and
Secondary
Unknown
Secondary
Secondary
Secondary
Secondary
Secondary
Unknown
Unknown
Secondary
Secondary
Primary
Immune
status
Unknown
Unknown
2
2
Unknown
Unknown
All
1 &2
All
1&2
All
Unknown
Unknown
Unknown
Unknown
Unknown
Dengue
virus
serotype
Table 1: Association between HLA alleles and clinical outcomes of dengue reported in different populations
Genetics of susceptibility to severe dengue
Dengue Bulletin – Volume 39, 2016
Dengue Bulletin – Volume 39, 2016
Thailand
Malaysia
Brazil
Brazil
Sri Lanka
Mexico
Vietnam
Venezuela
Population
HLA-B*48
DHF
DHF
HLA-A*03 and HLA-B*18
DHF
HLA-B*44
DHF
Symptomatic
dengue
HLA-DRB1*11 and HLADQA1*05:01
HLA-B*13
Symptomatic
dengue
DHF
HLA-A*31
HLA-DQB1*06:11
DHF
HLA-A*01
DHF
HLA-A*24 and HLA-DRB1*12
DF
HLA-DQB1*02:02
DSS
DHF
HLA-DQB1*03:02
HLA-A*31 and HLA-DRB1*08
DF
DSS
HLA-DRB1*09:01
HLA-B*35
DHF and DSS
DHF
HLA-B*40
HLA-A*2402/03/07
DF
Nature of dengue
disease severity
HLA-B*15 and HLA-B*57
Associated HLA allele/genotype/
supertype
Susceptibility
Protection
Susceptibility
Susceptibility
Protection
Susceptibility
Protection
Susceptibility
Susceptibility
Susceptibility
Susceptibility
Susceptibility
Protection
Protection
Susceptibility
Susceptibility
Protection
Nature of
association
Secondary
Unknown
Unknown
Overall
Unknown
Unknown
Unknown
Unknown
Primary
Secondary
Unknown
Unknown
Unknown
Secondary
Both
Unknown
Unknown
Immune
status
Unknown
Unknown
Unknown
3
3
3
Unknown
Unknown
Unknown
Unknown
Unknown
Unknown
Unknown
2
Unknown
Unknown
Unknown
Dengue
virus
serotype
Genetics of susceptibility to severe dengue
7
8
References: 27-44.
Thailand
India
Population
DF
HLA_A*02 and HLA-A*01/*03
supertype
Symptomatic
dengue
HLA-B*18 and HLA-Cw*07
DHF
DF
HLA-A*33
HLA-B*44 supertype
DHF
Nature of dengue
disease severity
HLA-DRB1*07 allele and HLADRB1*07/*15 genotype
Associated HLA allele/genotype/
supertype
Susceptibility
Protection
Susceptibility
Susceptibility
Susceptibility
Nature of
association
Secondary
Secondary
Unknown
Unknown
Unknown
Immune
status
Unknown
Unknown
Unknown
Unknown
Unknown
Dengue
virus
serotype
Genetics of susceptibility to severe dengue
Dengue Bulletin – Volume 39, 2016
Genetics of susceptibility to severe dengue
primary infection.32 In a Malaysian population, HLA-B*13 was associated with severe dengue
while HLA-B*18 was associated with protection to progression against severe dengue.33 In an
Indian population, HLA-A*33 was associated with DF while HLA-B*18 and HLA-C*07 were
associated with symptomatic dengue.34 Among the HLA class II alleles, HLA-DRB1*07 allele
and HLA-DRB1*07/*15 genotype were associated with DHF.35 In a Philippines paediatric
population, HLA-A*33:01 was found to be associated with protection from severe dengue.36
Studies carried out in Brazilian dengue cases reported the association of HLA-A*01 with
susceptibility to dengue.37 HLA-B*44 was found to be associated with susceptibility to DHF in
secondary infections with DENV-3.38 Among the HLA class II alleles, a study reported higher
frequency of HLA-DQ1 in Brazilian DF and symptomatic dengue cases.39–40 In a Mexican
population, HLA-DRB1*04 was associated with protection to DHF.41 Another study from
Mexico reported the association of HLA-DQB1*03:02 with DHF and HLA-DQB1*02:02
with DF.42 Studies carried out in Cuba reported the association of HLA-A*31 and HLA-B*15
with susceptibility to DHF while HLA-DRB1*04 and HLA-DRB1*07 were associated with
protection to DHF. The association of HLA-B*15, HLA-DRB1*04 and HLA-DRB1*07 in
secondary infections were significant.43
Apart from HLA alleles, genetic variants in the gene coding for molecules involved in
the processing and presentation of antigens are also known to influence susceptibility to
infectious diseases. A study from southern India has reported the association of polymorphisms
in the genes coding for transporters associated with antigen presentation (TAP) with severe
dengue. Coding region polymorphisms at the 333rd and 637th positions of TAP1 protein and
at the 379th position of TAP2 protein were found to be associated with severe dengue in
primary infection.45
Cytokine and chemokine gene polymorphisms and their
association with dengue disease outcomes
Cytokines are immune mediators produced by the immune cells that contribute to the
immune response. Cytokines have been reported to be the major contributors in the
pathogenesis of dengue. Elevated levels of pro-inflammatory cytokines such as TNF-α and
IFN-γ and anti-inflammatory cytokines such as interleukin (IL)-10 and tumour growth factor
(TGF)-β have been reported in DHF cases by multiple studies.46 SNPs in the cytokine genes
affect their production and function. Numerous studies have investigated the association of
cytokine gene polymorphisms with dengue disease severity (see Table 2).
Multiple studies reported the association of genotype/alleles of TNF gene, correlated
with higher TNF-α levels, with DHF or bleeding manifestations in Thai, Cuban, Mexican
and Venezuelan dengue cases.47–50 TNF gene haplotypes involving rs1800629, rs361525 and
rs1800610 were found to be differentially associated with DHF in the context of immune
Dengue Bulletin – Volume 39, 2016
9
Genetics of susceptibility to severe dengue
Table 2: Cytokine gene polymorphisms and their association with dengue disease severity
in different populations
Population
Gene
SNP
Associated allele/genotype/
haplotype
Form of
dengue and
nature of
association
Venezuela
and Cuba
TNF
rs1800629
A allele
Susceptibility to
DHF
Malaysia
TNF
rs1800629
A allele and GA genotype
Protection to
DHF/DSS
rs361525
A allele and GA genotype
Susceptibility to
DHF/DSS
Thailand
TNF
rs1800629
A allele
Susceptibility to
risk of bleeding
India
TNF
rs1799964
CC genotype
Susceptibility
to symptomatic
dengue
IL8
rs4973
AT genotype
Susceptibility to
DHF
IL10
rs1800871
AG genotype
Susceptibility to
DHF
IL17F
rs763780
TC genotype
Susceptibility
to symptomatic
dengue
Cuba
TGFB1
rs1800471
G allele and GG genotype
Protection to
DHF
Brazil
IL6
rs1800795
GC genotype
Protection to
DF
Taiwan
TGFB1
rs1800469
CC genotype
Susceptibility to
DHF
Thailand
TNF
rs1800629,
G-G-A haplotype (TNF-3)
Susceptibility to
primary DHF
rs361525 and
rs1800610
G-A-G haplotype (TNF-4)
Susceptibility to
secondary DHF
ILB
rs1143627
C allele carriage
Susceptibility to
DSS
IL1RA
86 bp VNTR
2/4 genotype
Susceptibility to
DSS
Thailand
References 46-53.
10
Dengue Bulletin – Volume 39, 2016
Genetics of susceptibility to severe dengue
status.51 In contrast to earlier studies, the allele/genotype of TNF gene, correlated with higher
TNF-α levels, was associated with protection to DHF in a Malaysian population.52 In an Indian
population, combinations of high TNF-α producing genotypes and HLA class I and class II
alleles were associated with DHF.34–35 Apart from TNF-α, IL-1β, another pro-inflammatory
cytokine, has also been implicated in dengue disease pathogenesis. A study from Thailand
reported the association of IL1B rs1143627 C allele carriage with susceptibility to DSS.
The same study also reported the association of 86 base pair repeat polymorphisms (2/4
genotype) in the gene coding for IL-1 receptor antagonist with susceptibility to DSS.53 IL-8,
another inflammatory cytokine, levels have been constantly reported to be elevated in DHF
cases. The heterozygous genotype of IL8 rs4973 was found to be associated with protection
to DHF in an Indian population.54
SNPs in the anti-inflammatory cytokine genes such as IL10 and TGFB have also been
studied in dengue disease pathogenesis. Alleles/genotypes of promoter region polymorphism
(rs1800871) in IL10 gene, correlated with low levels of IL-10, have been shown to be
associated with susceptibility to DHF in a Cuban population.48 In an Indian population,
heterozygous genotype of IL10 rs1800871 polymorphism was found to be associated with
protection to DHF.54 The CC genotype of rs1800469, a promoter region SNP in the TGFB gene,
was found to be associated with DHF and DENV-2 viral load in a Taiwanese population.55
In a Cuban population, the GG genotype and ‘G’ allele of rs1800471, a coding region SNP
at the 25th codon of TGFB gene, was observed to be associated with protection to DHF.48
When the combinations of cytokine gene polymorphisms were analysed, combinations
of genotypes correlating with higher pro-inflammatory cytokine levels and lower antiinflammatory cytokines were observed to be associated with susceptibility to DHF in Cuban
and Indian populations.48,54
Vitamin D is an immunomodulator known to enhance innate immune response and
suppress adaptive immune response. Vitamin D acts through the vitamin D receptor (VDR).
Many studies have related vitamin D and its related molecules in the pathogenesis of dengue.
VDR gene polymorphisms have been shown to be associated with many infectious diseases.
A study from Vietnam reported the association of VDR rs731236 C allele with protection to
severe dengue.8 In Western India, VDR rs222870 T allele in a dominant mode was associated
with susceptibility to DHF.56
Genome-wide association studies and severe dengue
In the era of genomics, genome-wide association studies (GWAS) investigating thousands of
SNPs have been successful in identifying the disease loci and subsequently help in pinpointing
the causal variants by fine mapping studies. A GWAS was carried out in 2008 paediatric DSS
cases and 2018 controls from Vietnam. A replication study involving the most significantly
associated markers was independently carried out in 1737 DSS cases and 2934 controls
from Vietnam.57 These studies identified a susceptibility locus at MICB in the chromosome 6
Dengue Bulletin – Volume 39, 2016
11
Genetics of susceptibility to severe dengue
involving an SNP (rs3132468) that is located outside the HLA class I and class II loci. Another
variant (rs3765524) within phospolipase C, epsilon 1 (PLCE1) gene located in chromosome
10 was also found to be associated with DSS. An extended study on the identified SNPs in a
larger cohort of dengue cases and controls revealed that these SNPs were not only associated
with DSS but also with less severe clinical phenotypes.58
Challenges in studying immunogenetics of dengue
Many of the studies dissecting the genetics of susceptibility to severe dengue are
underpowered. Further, these studies are complicated by the circulating serotypes/genotypes
in different geographical regions; varying disease profile in the Americas, South East Asia
and the Indian subcontinent; immune status of the studied patients; and the dilemma as to
whom to use as healthy controls. Genotypes of the circulating serotype vary from place to
place and, in many endemic regions, all the four serotypes are circulating. Disease profile
in South East Asia is characterized by a large number of DSS cases and mainly children are
the most affected. In the Americas and India, the disease profile is characterized by a large
number of DF cases, DHF among severe cases and young adults are the most affected.59–60
In most of the studies, data is not available for infecting serotype and immune status, which
might contribute to inconsistencies observed between different studies.
Many studies have used cord blood samples or dengue negative healthy controls while
a few have used healthy controls dominantly consisting of seropositive individuals without
a history of hospitalization. A small number of studies have used asymptomatic healthy
controls. However, the definition of asymptomatic itself might have issues since there could
be a recall bias related to very mild symptoms among the asymptomatic subjects. Using
seronegative healthy controls might reduce the power of study since there is a possibility
that the seronegative subjects, if infected, might progress to DF or DHF. Hence a uniform
criterion should be defined for selection of controls used in the dengue immunogenetic
studies. The appropriate way is to use cases with mild disease as controls. Care must be
taken to match these controls with severe cases for immune status and infecting serotype.
Matching for immune status between controls (mild disease) and cases (severe disease) is
possible if the subjects are sampled during the acute phase of the disease. However, matching
for serotype might be an issue in places where multiple serotypes are circulating. Unless
the blood samples are obtained within four to five days of onset of disease, detecting the
serotype may not be possible. However, recent studies have suggested that patients secrete
viruses in their urine samples after the appearance of IgM antibodies in blood.61 This strategy
of detecting infecting serotype using urine sample can be utilized to enhance the number
of study subjects with serotype data. Moreover, delineating T-cell response against serotype
specific epitopes might help in determining the infecting serotypes and those serotypes that
are involved in previous infections.
12
Dengue Bulletin – Volume 39, 2016
Genetics of susceptibility to severe dengue
Hence, more prospective studies with sufficiently powered sample size in different
populations integrating data on immune status, infecting serotype and the number of
serotypes the patients are exposed to might help in delineating the susceptibility factors
against severe dengue.
Immunogenetics of dengue: implications for vaccine design,
prognosis and therapeutics
Studies carried out in different populations have reported the HLA alleles that are associated
with protection and those that are associated with susceptibility to severe dengue. HLA alleles
have also been reported to be associated with vaccine response in other viral diseases62 and
might have relevance for dengue vaccine studies. Investigation of CD8+ T-cell response in
dengue cases has demonstrated that HLA class I alleles, associated with protection to severe
dengue, restrict epitopes, which induce poly functional T-cell response of higher magnitude.
HLA alleles, associated with susceptibility to severe dengue, restrict epitopes, which induce a
weak T-cell response that lacks multifunctionality.63 A recent study on DENV-specific CD4+
T-cells revealed that the virus-specific cells were highly polarized, with a strong bias towards
a CD4 cytolytic phenotype, and these cells correlated with a protective HLA DR allele.64 The
epitopes restricted by protective HLA alleles include both conserved and serotype specific
epitopes. Thus, identification and characterization of conserved and serotype specific
epitopes which are restricted by multiple HLA alleles prevalent in different populations,
might be useful in vaccine design. Recent vaccine trials based on recombinant live attenuated
tetravalent chimeric yellow fever dengue vaccine (CYD) reported varying vaccine efficacy
for different serotypes.65–67 Whether host genetic factors also contribute to varying vaccine
efficacy observed in the vaccine trials needs further investigations. CYD lacks non structural
proteins that are targeted by T-cells and hence the vaccinees lack T-cell immune response
against dengue. Serotype specific and conserved epitopes restricted by multiple HLA alleles
can supplement envelope protein based dengue vaccines.
Moreover, various non-HLA gene polymorphisms identified to be associated with severe
dengue, if replicated in multiple prospective cohort studies, can serve as markers to predict
severe dengue and help in the clinical management of dengue cases. Genetic studies have
identified the role of genes coding for virus entry receptors, PRRs, innate immune and
inflammatory mediators in the pathogenesis of severe dengue. Hence, it is possible to identify
the mechanism of association of genetic variants with severe dengue, which might have
implications for developing therapeutics for severe dengue targeting these gene products.
Conclusion
Susceptibility to severe dengue is a polygenic phenomenon and is influenced by gene–gene
and gene environment (infecting serotype, immune status and other factors) interactions.
Dengue Bulletin – Volume 39, 2016
13
Genetics of susceptibility to severe dengue
Multiple prospective cohort studies with data on infecting serotype and immune status might
lead to understanding the pathogenesis of severe dengue. Such results might have implications
for vaccine design, prognosis and therapeutics against severe dengue.
Acknowledgements
The author gratefully acknowledges the encouragement provided by Dr D.T. Mourya, Director,
National Institute of Virology, Pune, India, for writing this review article.
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Dengue Bulletin – Volume 39, 2016
Temporal spatial distribution of dengue
and implications on control in
Hulu Langat, Selangor, Malaysia
Zahir Izuan Azhara,b#, Ahamad Jusohc, Syed Sharizman Syed Abdul Rahima,
Mohd Rohaizat Hassana, Nazarudin Safiana, Shamsul Azhar Shaha
a
Department of Community Health, Faculty of Medicine, Universiti Kebangsaan Malaysia,
Kuala Lumpur, Malaysia
Department of Population Health and Preventive Medicine, Faculty of Medicine,
Universiti Teknologi MARA (UiTM), Selangor, Malaysia
b
c
Petaling District Health Office, Selangor, Malaysia
Abstract
Dengue has continued to be one of the most important public health problems in Malaysia. Dengue
infections and mortalities have remained at a high level. By combining Geographic Information
System (GIS) and ovitrap surveillance, this study aims to discover the spatial patterns of dengue
infections and also the association between ovitrap monitoring. This is a retrospective review
involving all confirmed dengue cases and ovitrap data from 2009 to epidemiology week 10 in
2012, from Hulu Langat, Selangor and a total of 6907 cases were analysed using ArcGIS version
10.0 and SPSS version 19.0. Results showed age group of 21 to 30 had the highest number of cases
at 1866 (27%) cases, majority were male with 3948 (57.2%) cases and Malay with 3908 (56.6%)
cases. Kajang had the highest number of ovitrap placement at 257 (39.0%) and has higher level of
indexes. The majority of cases were located in Ampang, followed by Cheras and Kajang. Ovitrap
Index did not have a significant relationship between low or high risk areas for dengue (x2=2.847,
p=0.092). Spatial global pattern analysis by average nearest neighbour resulted in nearest neighbour
ratio of less than 1 with Z-score ranging between 68.17 to -14.51 and p value of <0.001. When
mapping clusters with hotspot analysis (Getis-Ord Gi), hotspots were identified. Hotspot areas fell
on the northwest, west, southwest and the biggest area at the northeast side of the Hulu Langat
district. This study demonstrated significant spatial patterns of clustering of dengue cases in Hulu
Langat district. Integration of GIS application with dengue cases and ovitraps in the Hulu Langat
district can provide a new insight regarding incidence of dengue and vector populations.
Keywords: Dengue, cluster, ovitrap, spatial analysis
#
E-mail: [email protected]
Dengue Bulletin – Volume 39, 2016
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Temporal spatial distribution of dengue and implications on control in Hulu Langat, Selangor, Malaysia
Introduction
In 2012, report by World Health Organization (WHO) showed dengue ranks at the top as
the world’s most important mosquito born viral disease. The emergence and spread of all
four serotypes (DEN 1, DEN 2, DEN 3 and DEN 4) represent a global pandemic threat. The
incidence of dengue has also increased 30-fold during the past five decades. Yearly, around
50-100 million new reported infections occur in more than 100 endemic countries.1 Western
Pacific Region of WHO ranks the top in both cases reporting and frequency of epidemics. Over
90% of the total dengue cases reported in this region are contributed by Cambodia, Malaysia,
Philippines and Vietnam.2 Malaysia alongside Thailand, Vietnam, Laos and Singapore are
presumably known as the clusters for dengue infections in the Asia-Pacific region.3
Since the first reported case of dengue in 1901 and dengue haemorrhagic fever in 1962,4
dengue has remained as one of the most important public health problems in Malaysia. In a
decade, dengue infections and mortalities have increased with the second half of the decade
show overall incidence have stabilized but remained at a high level. Malaysia is the only
country which has this trend compared to other countries in the Western Pacific region.5
Recently in 2014, Malaysia had the worse epidemic with a historical 240% increase in cases
and almost similar increase in numbers of deaths compared to the same period in 2013.
Until the end of November 2014, Malaysia had total cases of 93 402 and 178 deaths.6 The
predominance of dengue cases has also shifted from children to adults.7
Given the unique biological characteristic of Aedes populations, trapping eggs via the
ovitrap method has become the easiest and cost effective surveillance for Aedes. Many studies
have proven that ovitrap surveillance could be used for the prediction of dengue outbreak
and is highly recommended as a surveillance tool.8 In fact, ovitrap allows better assessment
of infestation densities as compared to the conventional larvae search methods which do
not provide information regarding mosquito population density.9
Geographic Information System (GIS) has allowed the integration of environmental
and disease elements associated with mosquito breeding patterns.10 By using GIS, areas of
dengue incidence can be detected with great accuracy and urgent prevention measures can
be taken to tackle this disease.11 GIS is beneficial in improving the cases prediction capability
and strengthening preventive measures through good resources allocation.12
This research can contribute useful information regarding vector control programmes
to reduce the burden of this disease. The Hulu Langat district reports a high number of
dengue cases yearly and contributes significantly to the total cases in Malaysia and the state
of Selangor. The benefit of this analysis will be better planning of preventive actions that
can be more focused on the affected areas. This study also highlights the role of ovitraps. By
combining GIS and ovitrap surveillance, this study aims to discover the spatial patterns of
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Dengue Bulletin – Volume 39, 2016
Temporal spatial distribution of dengue and implications on control in Hulu Langat, Selangor, Malaysia
dengue infections and also the association between ovitrap monitoring. Correct identification
of the pattern and its significance will help the district in effectively planning and implementing
prevention and control programmes.
Methodology
Hulu Langat is the fifth largest district in the state of Selangor on the west coast of Peninsular
Malaysia, which is located between Putrajaya and Kuala Lumpur. It is made up of seven mukim
(subdivisions), which are Ulu Langat, Ampang, Cheras, Ulu Semenyih, Kajang, Semenyih
and Beranang. Ulu Langat and Ulu Semenyih are partly covered by forest and hilly areas.
Ampang and Cheras have more infrastructures involving high human activities like shopping
centres, offices and residential areas. Kajang has abundant residential areas, schools, higher
learning centres and small scale industries. Semenyih and Beranang have growing township
area with some areas of small industries.
According to the 2010 census, Hulu Langat district has a total population of 1 138 198.
Ampang and Kajang are among the highest populated subdivisions in Hulu Langat with
populations of 342 676 and 342 657 respectively. This district has a mixed population of
urban and rural settlements. The majority of the population is centred in towns near Kuala
Lumpur. Hulu Langat has more cases of dengue than almost any other district in the country.
Vector control programme is currently done by the Hulu Langat District Health Office located
in Kajang.
This is a retrospective review involving all confirmed dengue cases and ovitrap data from
2009 to epidemiology week 10 in 2012, from Hulu Langat district. Approval for research
has been obtained from the Hulu Langat District Health Office.
Vector density estimation is based on ovitrap index (OI). OI is the number of positive
Aedes ovitraps over the total number of recovered ovitraps determined from each ovitrap
surveillance done in percentage. Ovitrap index was divided into 4 levels. Level 1 is OI less
than 5%, Level 2 is between 5 to 19%, Level 3 is between 20 to 39% and Level 4 is above
40%.13
Data analysis for descriptive and analytical purposes was done by using Statistical Package
for Social Sciences (SPSS) Version 19.0. GIS spatial data was analysed using ArcGIS software
version 10. Spatial analyses included mean centre, average nearest neighbour and hotspot
analysis (Getis-Ord Gi). Mean centre is calculated by finding the average of the x-coordinate
of all the features, then finding the average of all the y-coordinate values. The resulting x, y
coordinate pair is the mean centre. Mean centre indicates a coordinate that has the shortest
total distance from other case coordinates. This can be useful for determining the movement
of a set of data over time.14 In this study, mean centre can show movement of dengue cases
over a period of time.
Dengue Bulletin – Volume 39, 2016
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Temporal spatial distribution of dengue and implications on control in Hulu Langat, Selangor, Malaysia
Average Nearest Neighbour is an index calculated to reveal the average distance of a
case to all its neighbours compared to the average distance for a random distribution. This
technique for pattern analysis will answer the question whether the data is assumed to be
clustered, dispersed or occurred due to random chance. Nearest neighbour ratio of less
than 1 points towards a more clustering pattern, while ratio of more than 1 points towards
a more dispersed pattern.14 Getis-Ord Gi statistic will give a Z score value that will reveal
spatial features with either high or low value cluster. The greater the Z score value, the more
extreme the clustering of hotspot, while with lesser Z score value, the clustering of low values
or coldspot will be more concentrated. Utilization of the Average Nearest Neighbour analysis
in GIS can show a clustered or dispersed pattern of dengue cases in the studied area and
determine whether it is significant or not. Dengue cases hotspot areas can also be revealed
by using the Getis-Ord Gi statistic in GIS.
Results
Dengue cases in the district showed age distribution more at the younger adult age group.
Age group of 21 to 30 had the highest number of cases which contributed to 1866 cases,
which was 27.0% of all the cases. The oldest case was found to be at the age of 84 years
old. There were more male cases compared to females, which contributed to 3948 cases
and was 57.2% of all cases. Malay holds the majority cases with 3908, which was 56.6% of
all the dengue cases in Hulu Langat (Table 1).
Kajang had the highest number of ovitrap settled up in a particular locality at a given
time, which was 257 (39.0%) and has higher level of indexes. The lowest number of ovitrap
was in mukim Ulu Semenyih. According to the level of Ovitrap index % (OI), Level 3 had
the highest number with 252 (38.2%). Level 1 was the least found (Table 2).
There were not many changes in numbers over the years in dengue cases trend. From
2009 to 2011, there were 2263, 2404 and 2043 cases respectively with incidence rate of
198.82, 211.21 and 179.49 per 100 000 population. Number of deaths in those years was
12, 3 and 7 respectively from the year 2009 to 2011.
In general, by looking at the trend of cases, there would appear to be more cases during
start of the year compared to at the end, with minor dengue cases fluctuation between weeks.
Ovitrap index level seems to follow the trend of dengue cases except at some particular weeks.
For example, week 33-35 and 50-51 had high number of ovitrap indexes but cases do not
appear to be as high as expected. However, there is a limitation in this aspect because the
ovitraps are not consistently placed at a particular area every week and might not represent
the real trend between dengue cases and ovitrap index.
The top three dengue cases were notified from Ampang with 2571 (37.2%), followed
by Cheras with 1631 (23.6%) and Kajang with 1290 (18.6%). Higher ovitrap indexes and
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Temporal spatial distribution of dengue and implications on control in Hulu Langat, Selangor, Malaysia
Table 1: Characteristics of dengue cases’ distribution from 2009 to March 2012
Characteristics
No. of cases (N= 6907)
n (%)
Age in years
Under 5 years old
5 to 10 years old
207 (3.0)
462 (6.7)
11 to 20 years old
1622 (23.4)
21 to30 years old
2055 (29.8)
31 to 40 years old
1241 (18.0)
41 to 50 years old
758 (11.0)
51 to 60 years old
414 (6.0)
61 years old and above
148 (2.1)
Ethnicity
Malay
3908 (56.6)
Chinese
1741 (25.2)
Indian
775 (11.2)
Others
483 (7.0)
Mukim (Subdivisions)
Ampang
2571 (37.2)
Cheras
1631 (23.6)
Kajang
1285 (18.6)
Semenyih
869 (12.6)
Beranang
332 (4.8)
Ulu Langat
219 (3.2)
Ulu Semenyih
0 (0.0)
numbers were noticed in Kajang area. Ampang showed less ovitrap monitoring done even
though it has the highest number of notified dengue cases.
Ovitraps were placed at all the mukim but only minimal ovitraps were located at the
Ulu Langat and Ulu Semenyih area (Figure 1). There was a positive significant correlation
between the dengue cases and Ovitrap Index of < 5% with calculated r = 0.295, p = <0.05,
with a R2 = 0.087. Regarding Ovitrap Index and dengue risk area, no significant relationship
was noted (x2=2.847, p=0.092). Low dengue risk area is defined as an area which has less
than 10 dengue cases reported while high dengue risk area is defined as an area which has
10 or more dengue cases reported.15
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Temporal spatial distribution of dengue and implications on control in Hulu Langat, Selangor, Malaysia
Table 2: Ovitrap data distribution from 2009 to 2012
No. of ovitrap at one locality at a given time
(N= 659)
n (%)
Ovitrap
Mukim
Kajang
Semenyih
Cheras
Ampang
Beranang
Ulu Langat
Ulu Semenyih
n = 659
257 (39.0)
193 (29.3)
147 (22.3)
39 (5.9)
20 (3.0)
3 (0.5)
0 (0.0)
Ovitrap index (O.I) level
Level 1 (OI <5%)
Level 2 (OI 5%-19%)
Level 3 (OI 20%-39%)
Level 4 (OI >40%)
n = 659
66 (10.0)
215 (32.6)
252 (38.2)
126 (19.1)
Figure 1: Ovitrap locations in Hulu Langat from 2009–2012
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Dengue Bulletin – Volume 39, 2016
Temporal spatial distribution of dengue and implications on control in Hulu Langat, Selangor, Malaysia
Figure 2: Mean centre and standard
distance for dengue cases in 2009 for
dengue cases in 2009
Figure 3: Mean centre and
standard distance for dengue cases
in 2010
Figure 4: Mean centre and standard
distance for dengue cases in 2011
Figure 5: Mean centre and standard
distance for dengue cases in 2012
Dengue Bulletin – Volume 39, 2016
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Temporal spatial distribution of dengue and implications on control in Hulu Langat, Selangor, Malaysia
From the year 2009 until March 2012, the majority of cases can be clearly seen located
in Ampang, followed by Cheras and Kajang (Figure 2 to Figure 5). In this situation, the mean
centre was noted to move from north to south from 2009 to 2012. It was located in Cheras
in 2009 and moved southwards to Kajang in 2012.
From 2009 to 2012, the z-score ranges from -68.17 to -14.51 and p-values were all
significant, which was < 0.001. All the nearest neighbour ratios were less than 1 and this
indicates that all the cases are trending towards clustering. From 2009 to 2012, several hotspot
locations can be identified. Hotspot locations are situated at Ampang, Cheras, Kajang and the
biggest area at the northeast of Hulu Langat district (Figure 6). The majority of the areas in
the Hulu Langat district have a high population density which includes places like Ampang,
Beranang and Kajang. An area which has a low population density includes a forest reserve,
located in mukim Ulu Langat (Figure 7).
Figure 6: Hotspot analysis for dengue cases from 2009–2012
Note: Hotspot locations in Hulu Langat district are red-coloured areas in the dashed-red box
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Dengue Bulletin – Volume 39, 2016
Temporal spatial distribution of dengue and implications on control in Hulu Langat, Selangor, Malaysia
Figure 7: Population density of Hulu Langat district
Areas of
Low Populated
Areas of
High Population
Note: A – Ampang subdivision
B – Beranang subdivision
C – Kajang subdivision
In general, Ampang revealed plenty of hotspot areas and also has high ovitrap index
scattered at that area. Two areas that did not have any ovitrap monitoring are hotspots.
Those places are located at the northeast (Ulu Langat subdivision) and southwest (Kajang
subdivision) areas of Hulu Langat district (Figure 8).
Discussion
Spatial analysis demonstrated that all the dengue cases are found to be distributed in clusters.
It also revealed hotspot locations in the Hulu Langat district. In addition, there was a positive
significant correlation between the dengue cases and Ovitrap Index of < 5%.
Dengue Bulletin – Volume 39, 2016
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Temporal spatial distribution of dengue and implications on control in Hulu Langat, Selangor, Malaysia
Figure 8: Ovitrap Index and hotspot areas in Hulu Langat
1–2
3–4
Note: A – Ampang subdivision
B – Ulu Langat subdivision
C – Kajang subdivision
It is documented that incidence of dengue will increase in areas with high human
activity. Large housing areas, industrial areas and school areas are some of the examples
of places where there will be more humans performing their daily activities.11 In this study,
the subdivisions of Ampang, Cheras and Kajang consist of many housing areas, schools and
shops. This can certainly contribute to high incidence of dengue cases, as shown by the high
trend from 2009 to 2012 at those areas. The local effects of human mobility in an urban
area, such as going to the office or school, need better understanding and can be applied
to the spatial dynamics of dengue transmission.16
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Temporal spatial distribution of dengue and implications on control in Hulu Langat, Selangor, Malaysia
Besides places with high human activity, places which are abandoned can also be a
breeding ground for mosquitoes. Cemeteries, which can have containers such as flower vases,
can be a source for Aedes breeding.2 Spatial analysis revealed two cemeteries located at
hotspot areas in the Hulu Langat district. Therefore, surveillance by ovitrap or control measures
such as fogging and placement of larvicides should not be forgotten at these cemeteries.
Other locations that might be of interest for control and prevention of dengue include
areas located at the south of Kajang. These places were noted to be hotspots for dengue
cases and must be monitored closely. High human activity in these areas and the large area
of land that is located close to natural forest make it an ideal place for mosquito breeding.
However, we did not include surrounding environmental exposure risks in our research. In
areas where clusters of cases appear to be high, they may have an environmental risk pattern
which surely will be beneficial to explore such as temperature and rainfall.
Population density also plays a role where highly populated areas can be a high risk area
for dengue.11,17 In the Hulu Langat district, subdivisions like Ampang, Beranang and Kajang
in particular, showed a high population density. There will be more susceptible patients that
will be exposed to Aedes mosquitoes in a highly populated area and this will increase the
chances of a person to develop dengue.18
Concerning vector populations, there was a weak but positive correlation between
presence of dengue cases and ovitrap index. Places with high ovitrap indexes located in the
Ampang subdivision and Cheras subdivision also recorded high number of dengue cases.
As these areas are located in an urban area, cleanliness must be given priority. If garbage
disposal management is not done correctly, accumulation of rubbish thrown at the housing
areas that can include containers such as cans or tyres will provide a perfect breeding ground
for Aedes mosquitoes.
Regarding locations for ovitrap placements, more ovitraps should be placed at the
subdivision of Ulu Langat (northeast of Hulu Langat district) and Kajang (southwest of Hulu
Langat district) as these are hotspots. Subdivisions of Beranang and south of Kajang do not
need to have a lot of ovitraps as these are not found to be hotspots. Lastly, analytical analysis
has shown that the Ovitrap Index does not have a significant relationship between low or
high risk areas for dengue. Therefore, the placements of ovitraps in the district of Hulu Langat
should be revised or changed accordingly from time to time.
Integration of GIS application with dengue cases and ovitraps in the Hulu Langat district
can provide a new insight regarding incidence of dengue and vector populations. Spatial
analysis done from this study will be useful to health authorities to implement surveillance,
control and prevention of dengue. A more focused effort, targeted at hotspot areas identified
by the GIS software, can save time and budget in order to reduce incidence of dengue in this
district. Future studies that integrate GIS can look into other variables such as socioeconomic
factors, rainfall and temperature which may reveal new information regarding dengue. The
Dengue Bulletin – Volume 39, 2016
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Temporal spatial distribution of dengue and implications on control in Hulu Langat, Selangor, Malaysia
next step in this area of research would be to expand the study area to other districts which
are known to have persistent dengue hotspots and eventually looking at the national level.
Conclusion
GIS is a tool that can integrate maps of a particular area and data of medical diseases.
Therefore, for future use, GIS can be effectively utilized to identify targeted areas for dengue
control programmes and benefit the population’s health.
Acknowledgements
The authors would like to thank the Director General of Health Malaysia for permission to
publish this paper. We also would like to acknowledge with thanks the assistance of officers
from the Hulu Langat District Office for data release to be used in this research.
References
[1] World Health Organization. Global strategy for dengue prevention and control 2012-2020. Geneva:
WHO, 2012. http://apps.who.int/iris/handle/10665/75303 - accessed 11 April 2016.
[2] Chang MS, Christophel EM, Gopinath D, Abdur R. Challenges and future perspective for dengue vector
control in Western Pacific Region. West Pacific Surveill Response. 2011;2:9–16.
[3] Banu S, Hu W, Guo Y, Naish S, Tong S. Dynamic Spatiotemporal Trends of Dengue Transmission in the
Asia-Pacific Region, 1955–2004. PLoS One. 2014;9(2):e89440.
[4] Poovaneswari S. Dengue situation in Malaysia. Malays J Pathol. 1993 Jun;15(1):3–7.
[5] Mohd-Zaki AH, Brett J, Ismail E, L’Azou M. Epidemiology of dengue disease in Malaysia (2000-2012):
a systematic literature review. PLoS Negl Trop Dis. 2014;8(11):e3159.
[6] World Health Organization. Update on the dengue situation in the Western Pacific Region. Dengue
Situation Update. Geneva: WHO, 2014.
[7] Mohd-Zaki AH, Brett J, Ismail E, L’Azou M. Epidemiology of dengue disease in Malaysia (2000–2012):
a systematic literature review. PLoS Negl Trop. 2014;8(11):e3159.
[8] Norzahira R, Hidayatulfathi O, Wong HM, Cheryl A, Firdaus R, Chew HS, et al. Ovitrap surveillance of
the dengue vectors, Aedes (Stegomyia) aegypti (L.) and Aedes (Stegomyia) albopictus skuse in selected
areas in Bentong, Pahang, Malaysia. Trop Biomed. 2011;28:48–54.
[9] Morato VCG, Teixeira M da G, Gomes AC, Bergamaschi DP, Barreto ML. Infestation of Aedes aegypti
estimated by oviposition traps in Brazil. Rev Saude Publica. 2005;39:553–8.
[10] Palaniyandi M. The role of remote sensing and GIS for spatial prediction of vector-borne diseases
transmission: a systematic review. J Vector Borne Dis. 2012;49:197–204.
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Temporal spatial distribution of dengue and implications on control in Hulu Langat, Selangor, Malaysia
[11] Shafie A. Evaluation of the spatial risk factors for high incidence of dengue fever and dengue hemorrhagic
fever using GIS application. Sains Malaysiana. 2011;40(8):937–43.
[12] Shah SA. GIS application in communicable and non-communicable disease: an overview. J Jab Kesihat
Masy. 2004;10:46–56.
[13] Food and Environmental Hygiene Department. Ovitrap survey in community and port areas. The
Government of the Hong Kong Special Administrative Region,2006. http://www.fehd.gov.hk/english/
safefood/pestnewsletter200602.html - accessed 11 April 2016.
[14] Allen, DW. GIS Tutorial Spatial Analysis Workbook. California: Ingram Publisher Services, 2011. pp.
255-301.
[15] National Environment Agency. Location of active clusters. Singapore, 2015. http://www.dengue.gov.
sg/ - accessed 11 April 2016.
[16] Stewart-Ibarra AM, Muñoz AG, Ryan SJ, Ayala E, Borbor-Cordova MJ, Finkelstein JL, et al. Spatiotemporal
clustering, climate periodicity, and social-ecological risk factors for dengue during an outbreak in
Machala, Ecuador, in 2010. BMC Infect Dis. 2014;14(1):610.
[17] Naqvi, SAA, Kazmi, SJH, Shaikh, S and Akram, M. Evaluation of prevalence Patterns of Dengue Fever in
Lahore District through Geo-Spatial Techniques. Journal of Basic and Applied Sciences. 2015;11:20–30.
[18] Li Z, Yin W, Clements A, Williams G, Lai S, Zhou, H, et al. Spatiotemporal analysis of indigenous and
imported dengue fever cases in Guangdong province, China. BMC Infectious Diseases. 2012; 12: 132.
Dengue Bulletin – Volume 39, 2016
31
Pathogenesis of dengue associated
haematological dysfunction
Nitali Tadkalkara, Ketaki Gantia*, Kanjaksha Ghoshb, Atanu Basu#
a
National Institute of Virology, 20A Dr Ambedkar Road, Pune 411001, India
National Institute of Immunohaematology, Mumbai
b
*
Current address: Tumor Biology Laboratory
International Center for Genetic Engineering & Biotechnology, Trieste, Italy
Abstract
Dengue virus infection is rapidly emerging to be an important challenge to global public health as the
geographical regions affected by the virus as well disease severity have shown significant changes in
the recent past. The clinical disease caused by dengue virus infection remains broad spectrum but
haematological dysfunctions constitute a major hallmark. Thrombocytopenia, bleeding disorders
and peripheral blood leukopenia are common features and severe bleeding with frank capillary
leakage and shock develops into dengue haemorrhagic fever/shock syndrome (DHF/DSS) in a
subset of individuals. The pathophysiology of the dysfunctional haematology remains incompletely
understood. While earlier studies have indicated that several factors like immunopathology and
high viremia are important triggers of disease severity, recent studies have revealed out-of-box
evidence of dengue virus directly affecting platelets and endothelial cells that could institute
early but crucial triggers for tipping the disease equilibrium towards a severe form. These events,
primarily, direct binding of dengue virus to human platelets leading to activation and inflammatory
responses, including possible support of virus replication by platelet environment, have been
dramatic recent findings.1,2,3 Moreover, the susceptibility of vascular endothelium to dengue virus
and alteration of subsequent endothelial physiology, especially cell adhesion biology and transport
could be important in the genesis of capillary dysfunction seen in DSS cases. Collectively, in view
of these recent findings, the paradigm shift in potential for developing novel clinical intervention
and therapeutic approaches in combating the severe clinical haematological dysfunction associated
with dengue infection is rapidly gaining credence as future strategies.
Keywords: Dengue, haematological dysfunction, platelet abnormalities
#
E-mail: [email protected]
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Dengue Bulletin – Volume 39, 2016
Pathogenesis of dengue associated haematological dysfunction
Introduction
Dengue is a flavivirus of significant public health importance as is evident from the evolution
of the recent outbreaks spanning over a decade that has witnessed more severe disease and
haemorrhagic manifestations. According to a few recent studies, approximately 3.6 billion
people are at risk of acquiring dengue infections; with approximately 230 million new
infections every year, including over 2 million cases of severe disease (DHF/DSS) and 21 000
deaths.4 Haematological abnormalities are frequently encountered in patients with dengue
infections. These include platelet abnormalities such as thrombocytopenia, leukopenia,
disseminating intravascular coagulopathies, vascular leakage and other bleeding diathesis
that may show varied case presentations. Besides thrombocytopenia, hypofibrinogenemia is
also a prominent finding in DHF cases. Although the pathology remains unclear, increased
intravascular clotting and low levels of factor II, V, VII, VIII, IX, X and XII have also been
documented.5 The possibility of direct and indirect virus mediated injury to the vascular
endothelium is also becoming significant in light of recent findings. The present review
explores the current knowledge on our understanding of the pathophysiologic mechanisms
involved in the etiology of dengue associated haematological dysfunction.
Dengue associated haematological abnormalities
A typical case of classical dengue fever (DF) presents with a febrile onset associated with
severe retro-orbital pain, myalgia, vomiting and fatigue. The fever and related symptoms
are usually self-limiting in nature and the patient recovers within a span of a week. The
presentation of myopathy can differ from mild to severe deep muscle and joint pain but
not radiculopathies. Laboratory function tests usually show a haemogram typical of a viral
infection with elevated monocytes but the differential diagnosis lies with thrombocytopenia
and mild to severe leukopenia. Serum alanine transferase levels are found to be elevated
commonly, but more serious complications such as fulminant hepatic failure or encephalitis
are rare.6,7,8 However, in a fraction of dengue virus infected cases severe haematological
abnormalities with life threatening bleeding and vascular leakage are observed, a syndrome
collectively termed dengue haemorrhagic fever with shock syndrome (DHF/DSS).
Normal haemostasis is maintained through a fine balance between coagulation and
fibrinolysis. The nature of alteration in coagulation factors in cases of DHF in comparison with
DF have been studied in detail and the findings suggest that activation of coagulation and
fibrinolysis is more acute in DHF/DSS cases when compared with classical DF cases.9 Frank
cases of disseminated intravascular coagulopathy (DIC) are rarely observed in dengue virus
infection and in a study involving 40 paediatric cases with different stages of disease, mild
to moderate degree of prothrombin deficiency was noted in 15–50% of the cases in grade
II and III, respectively, with laboratory confirmed evidence of consumption coagulopathy in
30% of the cases with DSS.10 Although a study on other coagulation related factors, especially
the effect on von Willibrand factor, showed a positive correlation with thrombocytopenia in
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Pathogenesis of dengue associated haematological dysfunction
a group of paediatric cases with DHF,11 however, more case controlled studies are required
before a conclusive profile on the effect of dengue associated changes in coagulation factor
biology can be summarized.
The origin of the thrombocytopenia, leukopenia and transient neutrophil deficiency
in dengue disease has been attributed to possible suppression of haematopoiesis directly
by DENV inhibiting megakaryocytic differentiation; combined with indirect immune
injury this has been suggested to play an important role in the origin of dengue associated
thrombocytopenia.1,12,13,14,15
Platelet abnormalities in dengue disease
Human blood platelets are anucleated so-called packets of cytoplasm fragmented from
megakaryocytes formed from the bone marrow through the process of thrombopoiesis.
These organelles are crucial for normal haemostasis and their physiology is carefully
orchestrated via a fine balance between ligand activation and intra-platelet signalling
events. Interestingly, platelets have mitochondria to suffice their energy requirement but
they have a limited life span of 120 days. Platelet dysfunction is very common in DENV
infection and is clinically presented as thrombocytopenia, aggregation abnormalities and
other dysfunctional behaviour.5,16 While the mechanisms remain incompletely understood,
antiplatelet antibodies, abnormalities in coagulation factors and suppression of thrombopoiesis
in the bone marrow directly by DENV or by disease pathology have been implicated as major
causes.13,17,18 Interestingly, early studies had also shown evidence of direct suppression of
thrombopoiesis and haematopoetic suppression in bone marrow of fatal DHF cases.19 In a
landmark study carried out in 1989, platelet functions were profiled in 35 paediatric cases
with serologically confirmed dengue virus infection. Findings from this study showed abnormal
platelet aggregation responses to agonists, increased plasma betathromboglobulin and
platelet factor 4. Moreover, the ADP induced aggregation was also seen to be compromised
significantly in these cases.20 Direct effects of dengue virus binding to platelets leading to
functional abnormalities have not been explored in detail and need further study. In 1995,
Wang et al. showed that dengue 2 virus could bind to human blood platelets in presence of
virus specific antibodies.21 This observation opened a new vista in exploring the mechanisms
of dengue-associated thrombocytopenia that was further supported from the direct evidence
of dengue 2 virus binding and physiologically activating platelets.1
Immunopathogenic mechanisms, especially presence of anti-platelet cross reactive
antibodies against both viral and platelet antigens, have been postulated, and also
experimentally demonstrated to some extent but conclusive evidence is still lacking.22,23 It
has been demonstrated that DENV infected vascular endothelial cells attract both platelets
and neutrophils to them and through both apoptosis and autoimmune mechanisms lead to
destruction of these cells.24 Although evidence of platelet associated antibodies, especially
anti-DENV IgM and immune complex deposits, has been shown in patients with severe
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Dengue Bulletin – Volume 39, 2016
Pathogenesis of dengue associated haematological dysfunction
dengue disease, the pathophysiology of this process is not clear as patients with very
low platelet counts may not present with any bleeding diathesis. The early evidence of
immunopathogenic mechanisms as an important component of platelet lesions in dengue
disease came from the studies of Funahara, who showed three fundamental observations:
(i) DENV antigens could directly associate with platelets; (ii) anti DENV antibody binding to
platelet induces thrombocyte destruction; and (iii) modulation of endothelial cell function by
DENV.25 Subsequent studies attempting to characterize the nature of anti-platelet immune
response showed evidence of anti-platelet IgM autoantibodies that could be detected even
eight to nine months after the initial illness.26 In 2003, Oishi et al. studied 53 hospitalized
patients with confirmed diagnosis of secondary dengue infection and studied the pattern
of platelet-associated IgG and thrombocytopenia. Their findings were consistent with the
earlier studies of Funahara et al. that anti-platelet antibodies could play an important role
in dengue-associated thrombocytopenia.27 Interestingly, in a subsequent study involving a
larger study population of 78 patients, both platelet associated IgG and IgM were studied
in confirmed secondary dengue infections with a study design to correlate the incidence of
thrombocytopenia. An inverse correlation between platelet counts and pAIgG and pAIgM
were found in these patients and the pAIg levels were significantly higher in the patients
with clinical presentation of DHF compared with those of DF, further confirming the role of
anti-platelet immunglobins in the origin of thrombocytopenia.28
The hunt for the elusive cross reactive epitope(s) between DENV proteins and platelets
remains controversial. A study in mice model suggested that DENV NS1 protein may have
shared epitopes, especially in the C-terminal region in a 251-372 amino acid stretch, the
findings need more in-depth studies as definite animal models for DENV are still lacking.29
The possibility of anti DENV NS1 antibody reacting to a platelet surface enzyme-disulfide
isomerase has also been shown.30
Paradigm shifts in pathophysiology of dengue associated thrombocytopenia were found
in two studies. The first by Anderson et al. who showed that non homologous antibodies
to dengue serotypes could enhance platelet binding by the virus immune complex but not
affected by presaturating the system with excess purified Fc, suggesting that presence of
antibody was essential.2 The second paper by Ghosh et al. was the first to demonstrate that
dengue 2 virus could directly interact and activate normal donor platelets in the absence of
any antibodies.1 These observations have been subsequently supplemented with new data
and confirm the direct binding of dengue virus to human platelet as a fundamental event in
the pathophysiology of thrombocytopenia.31,32
Dengue and vascular endothelial cells
Human vascular endothelial cells are probably one of the most physiologically unique and
functionally complicated cells. These cells make up the inner lining of all blood vessels and
constitute the major functional barrier between blood and organ parenchyma at the tissue
Dengue Bulletin – Volume 39, 2016
35
Pathogenesis of dengue associated haematological dysfunction
level.33 Although originally thought to be having passive barrier functions, current knowledge
on endothelial cell physiology is beginning to understand its manifold functionalities, especially
in immune responses and inflammation. Rapid developments in the field of cell culture
techniques have further enriched our understanding of vascular endothelial cell biology.
Endothelial cells have been shown to be involved in the pathogenesis of a variety
of infectious diseases ranging from tuberculosis, septicemic shock states to severe viral
haemorrhagic fevers such as Ebola, Marbug and Hantaan. In the case of severe dengue
infections such as DHF and DSS, the role of vascular endothelial cells is gaining prominent
ground.34 Many studies ranging from human autopsies and in vitro experiments suggest
that endothelial cells are susceptible to DENV both in vivo and in vitro.35,36 Several studies
have also suggested that DENV infection of endothelial cells can lead to release of cytokine
like IL6 and IL8, induce apoptosis and alter the transcriptome of the cell37 and affect gene
expression.38 Interestingly, a more heterogenous and differential gene expression profile
was observed after DENV infection of microvascular endothelial cell lines like ECV 304 and
HMEC.39 Importantly, the molecular and cellular events that lead to the major physiological
alterations of endothelial cells causing haemorrhage and vascular leak still remain incompletely
understood. Several novel findings from recent research have suggested that ubiquitineproteasome pathways,40 engagement of late endosomal events by the virus41 and cellular
endosomal membrane reorganization, especially through autophagic induction, could
constitute several key endothelial stress reactions to DENV.42,43 Moreover, alterations in
expression of haemostatically important molecules on endothelial cell surface has also been
shown but its significance in vivo remains to be elucidated.42
The main pathophysiology of the capillary leak in DSS is due to compromised integrity of
inter-endothelial cell junctional barrier. Under normal physiological situations, the junctions
between endothelial cells are precisely regulated through a well-orchestrated network of
signalling pathways involving, Fyk, Syn, FAK kinases and ion channel activities.44,45
In DENV infection, in vitro studies have shown that alterations in the beta integrin
biology of endothelial cell line HMEC-1 could breach the paracellular integrity.46 Dewi et al.
further showed that the so-called cytokine tsunami associated with severe DEN disease could
also lead to increased trans-endothelial electrical resistance and enhanced permeability of
endothelial cells.47,48 Interestingly, Cardier et al. showed that sera from cases of severe dengue
infection, DHF and DSS cases could also activate vascular endothelial cells in vitro, suggesting
possible presence of soluble vasoactive factors that might be involved in barrier disruption and
haemorrhage.49 Although DENV can infect different cell types, cells of the monocytic lineage
such as Langerhans cells and interstitial DCs are thought to be the primary targets of DENV.
Immature monocyte-derived DCs are also susceptible to DV with subsequent activation and
release of β3-integrin, which is required for DV entry into human HMEC-1. Permeability
alteration of microvascular endothelium is a factor in the plasma leakage produced by DENV
infection, and β3-integrin plays a central role in maintaining capillary integrity and regulating
vascular permeability vasoactive cytokines such as IL-8 and TNF-alpha.50
36
Dengue Bulletin – Volume 39, 2016
Pathogenesis of dengue associated haematological dysfunction
An injury causes transendothelial migration of the DCs and expression of matrix
metalloproteinases that can have deleterious effects on endothelial cell integrity.51 In vitro, DV
suppresses soluble VEGFR2 production by endothelial cells but upregulates surface VEGFR2
expression and promotes response to VEGF stimulation.52 Luplertlop et al. showed that DVinfected DCs overproduced soluble gelatinolytic matrix metalloproteinase MM9 and MMP2
with loss of the platelet endothelial adhesion molecule (PECAM) expression and increase
in vascular permeability.53 Angiopoetin-2 has also been shown to be upregulated in human
umbilical vein endothelial cells, which by itself can induce endothelial hyper-permeability
and also further augment inflammation through sensitization to TNF-α.54 These studies have
initiated the need to examine in more detail the possible role of host factors in the origin of
dengue-associated vascular pathophysiology.
In summary, the recent findings of dengue virus interacting with both platelets and vascular
endothelium leading to altered physiological responses in both might constitute critical and
irreversible events that have potential to evolve by engaging other pre-existing pathology of
the infection process towards severe bleeding diathesis and capillary leakage characterized
by DHF/DSS. More in-depth understanding of these processes poses an immediate future
challenge in developing newer intervention strategies and therapeutics.
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[8] Wahid SF, Sanusi S, Zawawi MM, Ali RA. A comparison of the pattern of liver involvement in dengue
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[18] Murgue B, Cassar O, Guigon M, Chungue E. Dengue virus inhibits human hematopoietic progenitor
growth in vitro. J Infect Dis. 1997;175:1497-501.
[19] Na-Nakorn S, Suingdumrong A, Pootrakul S, Bhamarapravati N. Bone-marrow studies in Thai
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[20] Srichaikul T, Nimmannitya S, Sripaisarn T, Kamolsilpa M, Pulgate C. Platelet function during the acute
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[21] Wang S, He R, Patarapotikul J, Innis BL, Anderson R. Antibody-enhanced binding of dengue-2 virus
to human platelets. Virology. 1995;213:254-7.
[22] Falconar AK. The dengue virus nonstructural-1 protein (NS1) generates antibodies to common epitopes
on human blood clotting, integrin/adhesin proteins and binds to human endothelial cells: potential
implications in haemorrhagic fever pathogenesis. Arch Virol. 1997;142:897-916.
[23] Falconar AK, Young PR. Production of dimer-specific and dengue virus group cross-reactive mouse
monoclonal antibodies to the dengue 2 virus non-structural glycoprotein NS1. J Gen Virol. 1991;72
(Pt 4):961-5.
[24] Butthep P, Bunyaratvej A, Bhamarapravati N. Dengue virus and endothelial cell: a related phenomenon
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Public Health. 1993;24(Suppl 1):246-9.
[25] Funahara Y, Ogawa K, Fujita N, Okuno Y. Three possible triggers to induce thrombocytopenia in dengue
virus infection. Southeast Asian J Trop Med Public Health. 1987;18:351-5.
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Pathogenesis of dengue associated haematological dysfunction
[26] Lin CF, Lei HY, Liu CC, Liu HS, Yeh TM, Wang ST, et al. Generation of IgM anti-platelet autoantibody
in dengue patients. J Med Virol. 2001; 63:143-9.
[27] Oishi K, Inoue S, Cinco MT, Dimaano EM, Alera MT, Alfon JA, et al. Correlation between increased
platelet-associated IgG and thrombocytopenia in secondary dengue virus infections. J Med Virol 2003;
71:259-64.
[28] Saito M, Oishi K, Inoue S, Dimaano EM, Alera MT, Robles AM, et al.Association of increased plateletassociated immunoglobulins with thrombocytopenia and the severity of disease in secondary dengue
virus infections. Clin Exp Immunol. 2004;138:299-303.
[29] Chen LC, Shyu HW, Lin HM, Lei HY, Lin YS, Liu HS, et al. Dengue virus induces thrombomodulin
expression in human endothelial cells and monocytes in vitro. J Infect. 2009;58:368-74.
[30] Cheng HJ, Lei HY, Lin CF, Luo YH, Wan SW, Liu HS, et al. Anti-dengue virus nonstructural protein
1 antibodies recognize protein disulfide isomerase on platelets and inhibit platelet aggregation. Mol
Immunol. 2009;47:398-406.
[31] Hottz ED, Oliveira MF, Nunes PC, et al. Dengue induces platelet activation, mitochondrial dysfunction
and cell death through mechanisms that involve DC-SIGN and caspases. J Thromb Haemost.
2013;11(5):951-962.
[32] Simon AY, Sutherland M, Pryzdial ELG. Dengue-virus binding and Replication by platelets. Blood.
2015 Jul 16;126(3):378-85.
[33] Cines DB, Pollak ES, Buck CA, Loscalzo J, Zimmerman GA, McEver RP, et al. Endothelial cells in
physiology and in the pathophysiology of vascular disorders. Blood. 1998;91:3527-61.
[34] Dewi BE, Takasaki T, Kurane I. In vitro assessment of human endothelial cell permeability: effects of
inflammatory cytokines and dengue virus infection. J Virol Methods. 2004;121:171-180.
[35] Bunyaratvej A, Butthep P, Yoksan S, Bhamarapravati N. Dengue viruses induce cell proliferation and
morphological changes of endothelial cells. Southeast Asian J Trop Med Public Health. 1997;28 (Suppl
3):32-37.
[36] Jessie K, Fong MY, Devi S, Lam SK, Wong KT. Localization of dengue virus in naturally infected human
tissues, by immunohistochemistry and in situ hybridization. J Infect Dis. 2004;189:1411-1418.
[37] Avirutnan P, Malasit P, Seliger B, Bhakdi S, Husmann M. Dengue virus infection of human endothelial cells
leads to chemokine production, complement activation, and apoptosis. J Immunol. 1998;161:63386346.
[38] Warke RV, Martin KJ, Giaya K, Shaw SK, Rothman AL, Bosch I. TRAIL is a novel antiviral protein against
dengue virus. J Virol. 2008;82:555-564.
[39] Liew KJ, Chow VT. Microarray and real-time RT-PCR analyses of a novel set of differentially expressed
human genes in ECV304 endothelial-like cells infected with dengue virus type 2. J Virol Methods.
2006;131:47-57.
[40] Kanlaya R, Pattanakitsakul SN, Sinchaikul S, Chen ST, Thongboonkerd V. The ubiquitin-proteasome
pathway is important for dengue virus infection in primary human endothelial cells. J Proteome Res.
2010;9:4960-4971.
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[41] Pattanakitsakul SN, Poungsawai J, Kanlaya R, Sinchaikul S, Chen ST, Thongboonkerd V. Association of
Alix with late endosomal lysobisphosphatidic acid is important for dengue virus infection in human
endothelial cells. J Proteome Res. 2010;9:4640-4648.
[42] Chen LC, Shyu HW, Lin HM, Lei HY, Lin YS, Liu HS, et al. Dengue virus induces thrombomodulin
expression in human endothelial cells and monocytes in vitro. J Infect. 2009;58:368-374.
[43] Gangodkar SV, Jain P, Dixit N, Ghosh K, Basu A. Dengue virus-induced autophagosomes and changes
in endomembrane ultrastructure imaged by electron tomography and whole-mount grid-cell culture
techniques. J Electron Microsc (Tokyo). 2010;59:503-511.
[44] Cereijido M, Gonzalez-Mariscal L, Contreras RG, Gallardo JM, Garcia-Villegas R, Valdes J. The making
of a tight junction. J Cell Sci. 1993;17(Suppl):127-132.
[45] Gonzalez-Mariscal L, Contreras RG, Bolivar JJ, Ponce A, Chavez De Ramirez B, Cereijido M. Role
of calcium in tight junction formation between epithelial cells. Am J Physiol. 1990;259:C 978-986.
[46] Zhang JL, Wang JL, Gao N, Chen ZT, Tian YP, An J. Up-regulated expression of beta3 integrin induced
by dengue virus serotype 2 infection associated with virus entry into human dermal microvascular
endothelial cells. BiochemBiophys Res Commun. 2007; 356:763-768.
[47] Dewi BE, Takasaki T, Kurane I. In vitro assessment of human endothelial cell permeability: effects of
inflammatory cytokines and dengue virus infection. J Virol Methods. 2004;121:171-80.
[48] Dewi BE, Takasaki T, Kurane I. Peripheral blood mononuclear cells increase the permeability of dengue
virus-infected endothelial cells in association with downregulation of vascular endothelial cadherin. J
Gen Virol. 2008;89:642-52.
[49] Cardier JE, Marino E, Romano E,Taylor P, Liprandi F, Bosch N, et al.Proinflammatory factors present in
sera from patients with acute dengue infection induce activation and apoptosis of human microvascular
endothelial cells: possible role of TNF-alpha in endothelial cell damage in dengue. Cytokine.
2005;30:359-365.
[50] Juffrie M, van Der Meer GM, Hack CE, Haasnoot K,Veerman AJ, Thijs LG. Inflammatory mediators
in dengue virus infection in children: interleukin-8 and its relationship to neutrophil degranulation.
Infect Immun. 2000;68:702-707.
[51] Asahi M, Wang X, Mori T, Sumii T, Jung JC, Moskowitz MA, et al. Effects of matrix metalloproteinase-9
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[52] Srikiatkhachorn A, Ajariyakhajorn C, Endy TP, Kalayanarooj S, Libraty DH, Green S, et al. Virus-induced
decline in soluble vascular endothelial growth receptor 2 is associated with plasma leakage in dengue
hemorrhagic Fever. J Virol. 2007;81:1592-1600.
[53] Luplertlop N, Misse D, Bray D, Deleuze V, Gonzalez JP, Leardkamolkarn V, et al. Dengue-virusinfected dendritic cells. trigger vascular leakage through metalloproteinase overproduction. EMBO
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[54] Siew Pei Ong, Mah Lee Ng, Justin Jang Hann Chu. Differential Regulation of Angiopoietin-1 and
Angiopoietin-2 during Dengue Virus infection of Human umbilical vein endothelial cells: implications
for endothelial hyperpermeability. Med Microbiol Immunol. 2013 Dec;202(6):437-452.
40
Dengue Bulletin – Volume 39, 2016
Phylodynamics of dengue viruses in India
vis-à-vis the global scenario
Sarah S Cherian# and Devendra T Mourya
National Institute of Virology, 20-A Dr Ambedkar Road, Pune 411001, India
Abstract
Dengue has been primarily an infection of the tropical and subtropical countries, mainly Southeast
and South Asia, Central and South America, and the Caribbean, but in the last few years, it is
emerging in the United States of America and also making its entry into Europe. Phylogenetic
analyses suggest that currently circulating serotypes diverged from their sylvatic ancestors
approximately 1000 years ago, while the transmission to humans occurred independently for
all the four dengue virus (DENV) types only a few hundred years ago. Recent phylogeography
studies attempted identifying the geographic origins of DENV types and their genotypes as well as
mapping the dispersion of the viruses globally. Southeast Asia, where all four serotypes have been
co-circulating since the Second World War, has been identified as a source population for the
rapid and dramatic re-emergence of DENV globally over the last half-century. India’s role during
the Second World War and its strategic location at the tip of the Indian Ocean facilitating global
movements in the aftermath of the war have been stated to be significant for the propagation of
the virus. In recent years, India has further contributed to the dissemination of DENV viruses due
to various reasons. With this background, the present review aims at compiling the phylodynamics
of the four serotypes of dengue viruses in India vis-à-vis the global scenario, the understanding of
which is important in the management and control of the spread of these viruses.
Keywords: Dengue types 1-4, India, molecular clock, phylogeography, migration links.
Introduction
Dengue is the most prevalent flavivirus infection of the tropical and subtropical countries
where the mosquito vectors Aedes aegypti and Aedes albopictus thrive.1,2 The dengue
virus (DENV) is a single stranded, positive-sense RNA virus and its genome is composed of
three structural genes encoding the nucleocapsid (C) protein, a membrane (M) protein, an
envelope glycoprotein (E) and seven non-structural (NS) proteins.3 There are four serotypes
of the virus referred to as DENV-1, DENV-2, DENV-3 and DENV-4, which are antigenically
and phylogenetically distinct. The four serotypes are further subdivided into numerous
phylogenetically distinct genotypes. All four serotypes can cause the full spectrum of the
#
E-mail: [email protected]; [email protected]
Dengue Bulletin – Volume 39, 2016
41
Phylodynamics of dengue viruses in India vis-à-vis the global scenario
disease from a subclinical infection to a mild self-limiting disease, the dengue fever (DF), and
a severe disease that may be fatal, the dengue haemorrhagic fever/dengue shock syndrome
(DHF/DSS).4
Southeast Asia, where all four serotypes have been co-circulating since the Second
World War, has been recognized as a main source-sink for the dispersion of DENV globally
over the last half-century.5 The spread of the virus was initially facilitated during the Second
World War, by the movement of ships and transport of goods.4 However, the recent past
evidenced by remarkable growth in human population, globalization, extensive and
unrestrained urbanization, international trade and commerce, and mass human movements
in the form of pilgrimages, international travel and tourism etc,6–9 further contributed to the
virus dissemination. The World Health Organization estimates a global annual incidence of
around 50–100 million cases of DF and 500 000 cases of DHF in tropical and subtropical
countries, mainly Southeast and South Asia, Central and South America, and the Caribbean.10
In the last few years, dengue has also emerged in the United States of America and has also
made its entry into Europe.11 Based on high spatial-resolution estimates of contemporary
global dengue risk and burden in 2010, it was estimated that India accounts for one third
of the global dengue infections.12
The first isolation of DENV was in 1943,13 while the first isolation in India at Kolkata
was in 1944, from serum samples of US soldiers.14 The disease is endemic in most major
cities and all four serotypes are known to circulate in India. Recent reviews elaborate on
the epidemiology, circulation of serotypes in different parts of the country and changes in
the circulating serotypes in consecutive years as well as the current status of DENV in the
country.15,16 Several reports are also available with regard to the evolution of DENV at a local
level and in different states in the country,17–20 and likewise also at a global level, the majority
of existing studies have focused on the evolution of individual DENV types at regional or
local scales.21–29 A recent study summarized the 70-year global distribution of dengue types
in a series of global maps.30 However, a comprehensive picture of the evolutionary dynamics
of the four DENV types in India vis-à-vis the global dynamics would serve the purpose of
comprehending the establishment and endemicity of DENV in the country and subsequent
dissemination of the virus. This review is an overview of studies carried out with respect to
the phylogeny, molecular clock, rates and dates of evolution and phylogeography of all the
four serotypes utilizing Indian as well as representative global sequence data over a period
of about 50–60 years.
Phylogeny and molecular clock analyses
Phylogeny based molecular clock analysis involves the determination of rates of nucleotide
substitution and root ages viz. divergence times for different genotypes as well as the time to
the most recent common ancestor (tMRCA) of various sub-groups. The inputs required are
the dated nucleotide sequences of known sampling time and output is seen as calibrated
42
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Phylodynamics of dengue viruses in India vis-à-vis the global scenario
phylogenies and genealogies, that is, rooted trees incorporating a time-scale. Molecular clock
analyses of DEN viruses are usually based on full-length E-gene sequences. Most studies apply
the BEAST1.5.3,31 which uses the Bayesian Markov Chain Monte Carlo (MCMC) approach
and allows implementation of both strict as well as relaxed clock models.32 The Tree Annotator
program also available in BEAST is used to generate the maximum clade credibility (MCC)
tree while tools such as Fig Tree 1.2.3 (http://tree.bio.ed.ac.uk/) are used for visualization of
the annotated tree. The 95% Highest Posterior Density (HPD) intervals are used to ascertain
the uncertainty in the parameter estimates.
DENV-1: DENV-1 has been circulating in India since the 1940s,33,34 the time frame
coinciding with the first reports of DENV-1 in 1943 in Japan and French Polynesia; and Hawaii
in 1944 and 1945.30 Over the period since then, the disease profile has changed from mild
to severe forms.35 DENV-1 was associated with a DHF outbreak in Delhi in 1997.36 DENV-1
was also implicated during recent outbreaks in Delhi in 2006 and 2008.37–39
Phylogeny of DENV-1 sequences reveals the delineation of this serotype into five
genotypes described based on their geographical distribution.40,34 These genotypes are also
designated as I–V.41 An MCC tree (Figure 1a) of 269 DENV-1 sequences of isolates over the
time span 1944-2011, with the earliest Indian isolates from India of 1962, showed that the
majority of the Indian strains belong to the Cosmopolitan genotype (Genotype V) while
a single Indian strain of 2001 was noted to belong to the Asian genotype (Genotype I).42
Within the Cosmopolitan genotype, Indian strains are distributed in three main sub-lineages
viz. India I, II and Afro-India.40,34 An earlier report by Anoop et al.19 had also reported the
categorization of Indian viruses into four Indian lineages on the basis of core/prM region.
Three Indian isolates of 1962 and 1963, notably including isolates from mosquitoes, clustered
with the American and India I sub-lineages. The estimated rate of nucleotide substitution
(Table 1) showed the 95% confidence interval (CI) to be 6.8x10-4 - 9.1x10-4 substitutions/
site/year (subs/site/year).42 Based on these rates, the inferred mean root age was ~108
years (HPD: 78, 150 years), indicating the existence of DENV-1 since ~1903 (beginning of
the 20th century). As per one of the earliest reports considered as a first report of DHF in
medical literature, dengue epidemics were noted in 1897.43 Similar rates as well as tMRCA
for DENV-1 have been reported.34,44,45,23 Further, molecular clock studies showed that the
different genotypes of DENV-1 emerged in the 20th century with Thailand and Malaysian
genotypes being the more recent ones. The Cosmopolitan genotype and the South Pacific
genotype emerged around the same time period (~65 years ago, 1940s) while the Asia
genotype was estimated to have emerged earlier (~92 years ago, 1920s). The tMRCA for the
Asia genotype was earlier estimated to be ~1937.45,23 However, the discrepancy could be
explained as inclusion of the earliest isolate from Japan (1943) in our dataset, as against the
earliest isolate of this genotype being considered as a Hawaii isolate of 1944 in the former
study while a Thailand (Asian genotype) isolate of 1980 was considered in the latter study.
The existence of phylogenetically distinct lineages in India suggests that there may have
been independent entries of the virus into the country. The India III lineage containing
Dengue Bulletin – Volume 39, 2016
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Phylodynamics of dengue viruses in India vis-à-vis the global scenario
Table 1: Rates of evolution*, estimated age and probable ancestral locations for the root
and genotypes of the 4 serotypes of DENV
Genotype
Most likely
ancestral location
(probability)
tMRCA (Time to the Most Recent Common
Ancestor) with 95% HPD (Highest Posterior
Density) interval
Node age
Year
DENV-1 [6.8 x 10-4 – 9.1 x 10-4 subs/ site/year]*
Root
Southeast Asia (0.5)
108.3 (77.7, 150)
1902.7 (1861, 1933.3)
Cosmopolitan (V)
India (0.86)
64.9 (59.2, 71.3)
1946.1 (1939.7, 1951.8)
Malaysia (III)
Southeast Asia (0.93)
47 (39.7, 56.6)
1964 (1954.4, 1971.3)
South Pacific (IV)
Southeast Asia (0.66)
63.8 (49.3, 81.1)
1947.2 (1929.9, 1961.7)
Asia (I)
Southeast Asia (0.45)
91.6 (75, 111.6)
1919.4 (1899.4, 1936)
Thailand (II)
Southeast Asia (0.98)
53.1 (48.4, 62.3)
1957.9 (1948.7, 1962.6)
DENV-2 [5.9 x 10-4 – 8.7 x 10-4 subs/ site/year]*
Root
Southeast Asia (0.12)
325.2 (159.3, 567.4)
1685.8 (1443.6, 1851.7)
Sylvatic
West Africa (0.23)
158.4 (78.4, 267.6)
1852.6 (1743.4, 1932.6)
Cosmopolitan (IV)
Southeast Asia (0.36)
67.9 (49, 92.5)
1943.1 (1918.5, 1962)
Asian II
Southeast Asia (0.61)
83.3 (73.5, 97.4)
1927.7 (1913.6, 1937.5)
Asian I
Southeast Asia (0.98)
57.6 (48.2, 69.7)
1953.4 (1941.3, 1962.8)
Asian/American (III)
Southeast Asia (0.88)
44.4 (34.3, 56.8)
1966.6 (1954.2, 1976.7)
American (V)
India (0.3)
103.3 (73.4, 143.7)
1907.7 (1867.3, 1937.6)
DENV-3 [6.9 x 10-4 – 1.0 x 10-3 subs/ site/year]*
Root
Philippines (0.08)
127 (74, 199)
1883 (1811, 1936)
GI
Indonesia (0.3)
49 (41, 60)
1961 (1950, 1969)
GII
Thailand (0.93)
32 (29, 38)
1978 (1972, 1981)
GIII
India (0.7)
56 (47, 68)
1954 (1942, 1963)
GIV
Caribbean (0.2)
80 (56, 112)
1930 (1898, 1954)
GV
Philippines (0.7)
57 (54, 64)
1953 (1946, 1956)
44
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Phylodynamics of dengue viruses in India vis-à-vis the global scenario
Genotype
Most likely
ancestral location
(probability)
tMRCA (Time to the Most Recent Common
Ancestor) with 95% HPD (Highest Posterior
Density) interval
Node age
Year
DENV-4 [4.1 x 10-4 – 1.0 x 10-3 subs/ site/year]*
Root
India (0.36)
158 (79, 291 )
1851 (1718, 1930)
GI
India (0.57)
96 (66, 141)
1913 (1868, 1943)
GII
Indonesia (0.24)
68 (39, 108)
1941 (1901-1970)
GIII
Thailand (0.9)
16 (12, 23)
1993 (1986, 1997)
GIV
Malaysia (0.98)
37 (36, 40)
1972 (1969, 1973)
GV
India (0.66)
97 (65, 146)
1912 (1863, 1944)
isolates exclusively from the 1960s and the Afro-India lineage with isolates from 1970 and
1971 are representative of extinct lineages. Indian isolates of lineage I from 2003-2006 were
closely related with isolates from East Africa (Reunion, 2004) and an isolate from Singapore
of 1990, which is a major economic and travel hub in Southeast Asia. Lineage India II had
viruses from 1962, 1982 and 2005 along with isolates from West Asia, East Africa, East Asia
and Southeast Asia and, therefore, represents an evolving lineage. This change in the lineage
of DENV-1 was suggested to be the cause for disease severity of DENV-1 in India. The 2005
isolates from Pune belonging to lineages I and II indicate that there was co-circulation of
two lineages during a single outbreak.
DENV-2: DENV-2 was first reported in 1944 in Papua New Guinea and Indonesia.46
In 1944 itself, DENV-2 was first isolated in India from the sera of American soldiers during
the Second World War.47 Since then, epidemics of DENV have been recorded from almost
all over India at different times. Limited phylogenetic studies of DENV-2, utilizing a small
fragment of either the E/NS1 gene or the capsid–premembrane (C–prM) gene, have been
reported, showing a change in the circulating genotype of DENV-2 in India.48,49,18
Our earlier studies for DENV-250 had indicated transmission of DENV-2 among India,
Caribbean Islands and the Americas while later, to further elucidate the direction of dispersal,
we carried out phylogeography analyses utilizing a larger and more temporally spread data.
The MCC tree for 307 E-gene isolates of DENV-2 (1944–2011) in this study42 represents the
six genotypes including the sylvatic genotype as described previously51 (Figure 1b). The Indian
isolates from 1956 to 1971 belonged to the American genotype previously designated as
genotype V,52 which also contains the Caribbean isolates (1953–1981), isolates from South
America (1967–1986), Central America (1984–1994), Oceania (1971–1974) and Trinidad
(1953). Indian isolates from 1974 to 2010 fall in the Cosmopolitan genotype previously
designated as genotype IV,52 which includes strains with a wide geographical distribution.
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Phylodynamics of dengue viruses in India vis-à-vis the global scenario
Figure 1: Maximum Clade Credibility (MCC) tree for (a) DENV-1 (b) DENV-2. The
collapsed branches correspond to the genotypes/major sub-clades. The countries (ISO
3166-1-alpha-2 Codes) and sampling times of the isolates are also indicated. The numbers
correspond to the tMRCA (Time to the Most Recent Common Ancestor) estimates of key
nodes, the ancestral states with their probabilities.(Figure based on Ref. 42)
(a)
46
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Phylodynamics of dengue viruses in India vis-à-vis the global scenario
(b)
Almost all the isolates in this genotype are dated beyond 1970 and comprise isolates from
South-Central Asia, East Asia, East Africa, West Asia, Southeast Asia and Oceania.
Similar estimates of rate (mean 7.2x10-4 subs/site/year and 95% HPD, 5.9x10-4 - 8.7x10-4,
Table 1) and age are reported in previous studies44,53 as also estimated in our study.42 Similar
evolutionary rates are thus inferred for DENV-1 and DENV-2 as also shown by Twiddy et
al.44 Moreover, our results indicate an earlier existence of DENV-2 as compared to that of
DENV-1 as also reported earlier.54,44 The tMRCA of the cosmopolitan genotype was ~1940s.
Dengue Bulletin – Volume 39, 2016
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Phylodynamics of dengue viruses in India vis-à-vis the global scenario
This genotype was divided into two subgroups, indicated by node A and B (Figure 1b). A
majority of Indian isolates belong to one subgroup of the Cosmopolitan genotype along with
isolates of Sri Lanka, Bangladesh, Bhutan, Saudi Arabia, Seychelles and a few of Australia,
Uganda and Singapore, having an ancestral time around 1960s.
DENV-3: DENV-3 was first reported in 1953 in the Philippines and Thailand, and has
been reported in Asia every year since 1962 with Thailand reporting several outbreaks.30
DENV-3 isolates are distributed into five genotypes, I–V, with six lineages (A–F) in GIII.55,56
Re-emergence of DENV-3 was reported in the 2005 outbreak in Northern India.57,58 The same
genotype was implicated in causing DHF outbreaks in the Americas.59,60 The data from India
is fragmentary with no representation from 1967 to 2005 except for a single 1984 isolate.
Bayesian analyses of a total of 95 E-gene sequences of Indian DENV-3 isolates (two of 1966,
and the majority from the period 2005–2010) analysed with global representative sequences
of DENV-356 revealed that the all Indian isolates grouped into GIII (Figure 2a). The Indian
isolates of 1966, including one mosquito and one human, are the oldest representative isolates
of GIII, and formed the new lineage F. Lineage E, which was not a tight cluster, consisted of
isolates from Sri Lanka (pre-DHF era), India (1984) and Samoa (1986). Lineage D included
one Indian isolate of 2009, from Kerala, along with isolates from Sri Lanka (1993–2000, postDHF) and Taiwan. Lineage C included Indian isolates of 2003–2010 along with isolates from
Cambodia, Bhutan, Saudi Arabia, Abidjan and Tanzania. Lineage B consisted of isolates from
Sri Lanka (post-DHF era) and Somalia while lineage A was represented by American isolates.
Under the relaxed uncorrelated exponential clock with constant growth population model,
the mean substitution rate was 9.0x10-4 subs/site/year (95% HPD limits: 6.9 x10-4 – 1.0 x10-3,
Table 1) similar to that reported by Araujo et al.28 DENV-3 is the only serotype for which no
sylvatic isolates are available.61 The estimate of the tMRCA for all genotypes of DENV-3 was
about 127 years ago (95% HPD: 74 199 years) with respect to the Indian isolates of 2010,
correlating to the period around 1883.56 DENV-3, at the oldest node, diversified into two
main branches, one that seeded Pacific region (GIV) and became extinct and the second
that diverged to populate South Asia/South Pacific (GI/ GV), Thailand (GII) and the Indian
subcontinent (GIII). Within genotype III, there was a sequential emergence of lineages E,
D, A and B. The tMRCA of lineage C, wherein the majority of the Indian isolates clustered,
dated to the period 1991–1999.
DENV-4: DENV-4 has five genotypes, including sylvatic as GIV and GI with three lineages
(A–C).56 Though this serotype was rarely reported after the 1970s in India, it was reported
in Delhi in 2003.62,63,64 A similar re-emergence of DENV-4, GI in Brazil in 2008 after three
decades was reported by Melo et al.65 However, genotypes I, II, and III of DENV-4 have
been detected yearly in Thailand since 1963.66 The MCC tree based on E gene sequences
(n=54) of DENV-4 isolates from India (period 1961 to 1965, 1979 and 2009) and global
representatives56 showed that the Indian isolates were distributed into two genotypes, GI
and GV (Figure 2b). Recent Indian DENV-4 isolates belonged to genotype GI. The old Indian
isolates from the 1960s along with one Thailand isolate from 1963 clustered independently,
and based on the high diversity from the other DENV-4 genotypes, the cluster was assigned
48
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Phylodynamics of dengue viruses in India vis-à-vis the global scenario
Figure 2: Maximum clade credibility (MCC) tree of E-gene sequences under the relaxed
uncorrelated exponential clock with constant population size. The names of DENV
isolates include GenBank accession number, reference to country origin and year of
sampling. The branches are coloured according to the respective geographical region.
Ancestral states with their probabilities are shown at key nodes (labelled) in brackets and
the scale bar indicates time in years (a) DENV-3 (b) DENV-4.(Ref. 56)
(a)
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Phylodynamics of dengue viruses in India vis-à-vis the global scenario
(b)
50
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Phylodynamics of dengue viruses in India vis-à-vis the global scenario
the new genotype, GV. The mean substitution rate was 6.9 x10-4 subs/site/year (95% HPD
limits: 4.1x10-4 – 1x10-3, Table 1). The estimated tMRCA for all genotypes of DENV-4 was
about 158 years with respect to the latest isolates of 2009 (1851 with 95% HPD: 1718–1930)
(Figure 2b), which matched with earlier reports.44 GI and GV, which contained Indian isolates,
had a tMRCA 1847–1935. The tMRCA for GV, which was populated exclusively with Indian
isolates from 1960s and one isolate from Thailand (1963) was 1863–1944. The absence of
recent isolates suggests that the GV is an extinct genotype. GI (tMRCA 1868–1943) branched
into the three lineages, A, B and C. All the Indian isolates from 1979 to 2009 clustered within
lineage A (tMRCAs dating to 1929–1956) along with Sri Lankan isolates.
Phylogeography and migration pattern analyses
Phylogeography studies allow us to reconstruct the spatiotemporal spread of the virus and thus
they can be used to uncover the factors that influence the patterns of population dynamics
and spatial diffusion. In such studies, the spatial information of the sequences is used to
infer the most probable ancestral geographic region/country at different internal nodes of the
tree by fitting a standard continuous-time Markov chain (CTMC) model with the Bayesian
stochastic search variable selection (BSSVS) in BEAST.67 The MCMC tree thus obtained is
used as an input in software such as SPREAD 1.0.368 to visualize and analyse the dispersion
pathways. The Bayes factor (BF) test available in SPREAD can be further applied to identify
well-supported rates of transitions between the different geo-regions.
DENV-1: Currently, knowledge about the phylogeography of DENV-1 is mainly limited
to studies done for a particular country or region (America by Allicock et al.,21 Brazil by
Drumond et al.22 and Asia by Sun and Meng23). Therefore, the knowledge about DENV-1
phylogeography is mainly elaborative for those regions. A work based on data from 45 distinct
geographic locations isolated during the period 1944 to 200945 analysed the worldwide
spread of DENV-1. Though the study revealed the demographic history of the major DENV1 genotypes circulating in the Asian and South Pacific regions, the source of dispersal into
the Caribbean could not be ascertained unanimously probably because of missing temporal
data from certain countries. Several studies45,23 as well as our studies42 based on E-gene
sequences of DENV-1 isolates of global and Indian representatives covering a broader time
span (1944–2011) revealed that the most probable ancestral geographical location for
DENV-1 was Southeast Asia (Figure 3a). The ancestral state for the different genotypes except
the Cosmopolitan genotype was also found to be from Southeast Asia. This result inferring
Southeast Asia as a main source population for the dispersion of the virus, corroborates with
earlier reports4 that suggested that the Southeast Asian region is the setting that began the
global dengue pandemic, as a consequence of the ecological disruption during and after
the Second World War. India was determined to be the ancestral state of the Cosmopolitan
genotype,42 which was in support to a result by Sun and Meng.23 Further, the ancestral state
for all the major nodes in the Cosmopolitan genotype was also found to be India.42 The
America lineage within the Cosmopolitan genotype is seen to have two clusters (Figure 1a),
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Phylodynamics of dengue viruses in India vis-à-vis the global scenario
Figure 3: Maps showing significantly non-zero transition rates (Bayes factor >3 for DENV1, -2 and -4; and BF>12 for DENV-3) that are frequently invoked to explain the diffusion
process of (a) DENV-1 (b) DENV-2 (c) DENV-3 (4) DENV-4. Darker the colour gradient,
stronger is the support for the corresponding rate.(Refs 42,56)
which had India as the ancestral state, indicative that there may have been at least two
separate introductions of the virus from India to the American region. The earlier introduction
to the Caribbean region was estimated to have happened around 1971, while the latter reintroduction was estimated to be around 1981. The tMRCA estimate obtained by Allicock
et al.21 based on 109 DENV-1 genotype V American isolates corroborates our estimate of
the first introduction into the Caribbean region. India seems to have played a central role in
dispersion of the virus to the Caribbean region as also indicated by significant Bayes factor
(Figure 3a). The role of mosquitoes in the propagation and dissemination of dengue viruses
can be emphasized considering that the outer branches of the cluster of Indian and America
lineages include two mosquito isolates. Within the Cosmopolitan genotype, several migration
events corresponding to the India II lineage were found to have occurred from India to other
Southeast and East Asian countries (that is, Thailand, Singapore, South Korea, etc.) since
the 1970s. This implies that these countries as popular tourist destinations may be playing
an important role in virus dissemination. Export of the virus was also observed earlier from
India to Africa in the Afro-India lineage. The estimated time frame being around 1952 most
likely reflects the movements between Africa and Asia after the Second World War.
52
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The earliest possible introduction of the virus to the American region appears to be
from East Asia ~1940s in the form of the Asian genotype. The Asian genotype virus also
entered India from East Asia around 2000, but does not seem to have got established in the
country. Introduction of the virus to Sri Lanka also appears to be from West Asia as supported
by significant migration link between these regions. A previous study69 suggested that the
dengue virus was introduced in West Asia due to pilgrimage, tourism or by migrant labour
from Southeast Asia and Africa. Our results confirm this conclusion with strong supports to
the links between these regions. Geographical proximity is one of the factors that play an
important role in viral dispersal, as indicated by significant transitional pathways between
North, Central, South America and Caribbean islands (Figure 3a). The Caribbean region
spread the virus to South and Central America, which further spread it to North America.
The same is true for Oceania, Asian and African regions.
DENV-2: In case of DENV-2, the only available reports have investigated the
phylogeography in a restricted geographic area (for Caribbean basin by Foster et al.,24
Vietnam by Rabaa et al.,25 Brazil by Drumond et al.,26 and Peru by Cruz et al.27). From our
own phylogeography studies of DENV-2 with a global dataset,42 West Africa was estimated
to be the most probable ancestral location for the sylvatic strains of DENV-2. This result is
supported by the fact that the African region is considered as the original habitat of Aedes
sp. mosquitoes70 which are the principle vectors in dengue transmission.71 Based on the
available data, it was not possible to accurately pinpoint the ancestral location for human
DENV-2, though Southeast Asia bears the highest probability in our study. The geographical
ancestor for the Asian and Asian/American genotypes was found to be Southeast Asia
(Figure 1b). The ancestral strain for the Cosmopolitan genotype was also most probably
located in Southeast Asia. Notably, the ancestral state for the American genotype was
determined to be India, though with a lower state probability. The BSSVS analysis indicated
that Southeast Asia, East Asia, Oceania and India have played a central role in the dispersal
of DENV-2 (Figure 3b). These regions showed significant transmission links with the other
regions, irrespective of their geographical proximity. This is supported by earlier reports,6
which suggested global epidemiology and that the transmission dynamics of dengue viruses
were changed dramatically in Southeast Asia during the Second World War. This led to
geographical expansion of the disease, as epidemics expanded westward from Southeast
Asian countries to India and Sri Lanka, and eastward to China.72 India is at the core of the
viral diffusion process showing significant migration links with regions like South-Central/
East Asia, Oceania, West Asia, East Africa and even South/Central America. Significant links
between India and South/Central America as well as the maximum probability of India as
the ancestral location of the American genotype, suggests a spread from India to America
rather than what was previously thought.50 This hypothesis is strongly supported by the
very high ancestral state probability for India at the node with mean root age in the 1940s
(Figure 1b). This time frame coincides with the period of the Second World War, supporting
the conclusion that transmission dynamics of dengue viruses were changed dramatically
in Southeast Asia during and after the Second World War. The links with highly significant
Bayes factors viz. Oceania-India/Caribbean, Central America-South/North America and East
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Phylodynamics of dengue viruses in India vis-à-vis the global scenario
Asia-West Africa-South America is also important in this regard (Figure 3b). Further, frequent
migration of DENV-2 from Caribbean islands to the American mainland had been reported
by Pires Neto et al.73 The same is reflected in significant links between Caribbean North/
Central/ South America. One subgroup of the Cosmopolitan genotype had Southeast Asia as
the ancestral location while the other subgroup had India as the geographical origin with very
high probability. This shows that the virus has dispersed from India to countries in regions
including South-Central Asia, East Asia, West Asia, and Oceania since 1950s and 1960s.
Specifically, two separate introductions into West Asia were noted from India in the 1990s
and in 2004, most likely by pilgrims. Movement of the virus from India to the Southeast Asian
countries was also noted in the 2010s. Increased urbanization and movement of people has
caused hyperendemicity of dengue virus in various countries.74 This is evident from shared
significant links between different regions over the globe (Figure 3b).
DENV-3: Global phylogeography for DENV-3 is not well understood. Araújo et al.28
investigated the phylogeography of three main genotypes separately. Their migration pattern
analysis of the main DENV-3 genotypes showed that genotype I was mainly confined to the
maritime portion of Southeast Asia and South Pacific, genotype II stayed within continental
areas in Southeast Asia, while genotype III spread across Asia, East Africa and into the
Americas. Reconstruction of the ancestral states by phylogeographic analysis using sequences
representative of all five genotypes in our study56 could not resolve the common ancestral
state of all DENV-3 genotypes as the state probability was very low (Figure 2a). On the other
hand, the most parsimonious ancestral state was determined to be Indonesia for GI, Thailand
for GII, Caribbean (CAR) for GIV and Philippines for GV. The ancestral state of GIII, which
was predicted to be India, differed from the earlier prediction of Sri Lanka (1967–1979).28
Within GIII, there was a sequential emergence of lineages E, D, A and B with Sri Lanka
as the ancestral state, while India was the suggested ancestral state for lineages F and C.
During 1981–1988 an introduction into India from Sri Lanka, which evolved into lineage C
during 1991–1999 was suggested. Therefore, two events, one exportation from India (preDHF period) and one importation from Sri Lanka (post-DHF period), occurred. Movement
of DENV-3 between the two countries was supported by a high BF value (Figure 3c). It is
possible that additional events have been masked by the paucity of data from India during
1970–2000. During the latter period (1999–2003) the virus was likely to have been exported
from India to Saudi Arabia, Africa and China. BF analysis provided significant evidence for
movement of the virus between India and West Asia. It has been suggested that pilgrimage
to Haj, which was subsidized by the Indian government since 1993, might be instrumental
in the importation of viruses to West Asia.69 Investigations in Bhutan during the 2006–2007
outbreaks indicated introduction of lineage C from northern India.75 Broadcasting of the virus
from India to Cambodia was also indicated with a significant BF value. On the other hand,
Bangladesh and Myanmar were populated with GII viruses from Southeast Asia as suggested
earlier.76 Further, dispersal of the virus from Sri Lanka to Africa and Central America was also
supported by significant values of BF.
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Phylodynamics of dengue viruses in India vis-à-vis the global scenario
DENV-4: Limited studies exist on the global phylogeography of DENV-4 as well. In
studies carried out by our group,56 India was predicted to be the ancestral state for the entire
DENV-4 serotype albeit with low probability (Figure 2b). Earlier reports77,63 had placed GIV
(sylvatic) at the root of DENV-4 based on phylogenetic analysis. The addition of data on
Indian isolates from the 1960s and the use of phylogeography analysis56 placed India at the
root of DENV-4 viruses during 1719–1931, a period that coincides with movement of people
between Africa and Asia. Phylogeography by Villabano and Zanotta,29 which did not have
the data from India, showed Malaysia/Thailand as the ancestor state for DENV-4. India was
also the suggested common ancestor for GIII and GIV (sylvatic) genotypes and for GI/GV
and GII genotypes.56 GI represented currently circulating viruses from India and Southeast
Asia. India was predicted to be the ancestral state at almost all nodes within GI indicating
that viruses from India possibly spread to Thailand, Sri Lanka, Cambodia and the Philippines.
Lineage A of GI had the Philippines as the ancestral state while lineages B and C had India
as the ancestor. The Philippines thus probably exported the virus to Japan and Thailand. GV
shared a common ancestor (India, 1863–1944) with a Thailand isolate, implying movement
of viruses from India to Thailand.
Further, Indonesia was suggested as the ancestral state of GII, containing viruses from
the Pacific region, and Indonesia may also have spread the virus to the Americas via the
Caribbean. Migration pattern analysis revealed fewer transitions and BF values much lower
than that observed for DENV-3 (Figure 3d). The highest BF values were for the transitions
between South America/Caribbean, India/Thailand and South America/Central America.
Concluding remarks and implications
Documentation of the serotype-specific record of DENV spread has important implications
for understanding patterns in dengue hyperendemicity and disease severity as well as for
vaccine design and deployment strategies.30 This review is an attempt to provide an overview
of the global evolutionary dynamics of the four serotypes of DENV with emphasis on the
role played by India. As noted in our studies, the population of dengue viruses in India has
undergone major changes since the 1960s with either genotype or lineage changes. The
viruses circulating in India in 1950s and causing mild disease were either replaced or evolved
into lineages/genotypes with greater virulence and/or transmissibility.16 Genotype shifts for
DENV-2 (American to Cosmopolitan) and DENV-4 (genotype V to I) and lineage changes for
DENV-1 (India III/ Afro-India to India I/II of Cosmopolitan genotype) and DENV-3 (F to C/D
of genotype III) were noted. Thus, new introductions, in situ evolution along with limited
recombination56 have contributed to diversity and the dengue evolutionary dynamics in
the country.
Estimates of the evolutionary rates revealed no significant differences among the DENV
serotypes (Table 1). Phylogeography studies for DENV-1 inferred that the cosmopolitan
genotype, circulating in India, West and East Africa, Caribbean region, East and Southeast
Dengue Bulletin – Volume 39, 2016
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Phylodynamics of dengue viruses in India vis-à-vis the global scenario
Asia, originated in India around the 1940s.42 India was also estimated to be the probable
geographical origin for the American genotype of DENV-2, circulating in India, South and
Central America, and Caribbean regions. The introduction of the genotype into India was
most likely to have occurred around the 1910s while the time span of the exportation of
this genotype was around 1940s. Further, India was also determined to be the ancestral
source for a subgroup of the Cosmopolitan genotype of DENV-2. The more recent dispersal
between Southeast Asian (including India) and East Asian countries was noted for both
DENV-1 and DENV-2 after the 1960s. On the other hand, for both DENV-3 and DENV-4,
the transportation of viruses between Sri Lanka and India was evident during the 1970s and
1980s which correlated to human movements during the Sri Lankan civil war.56 The probable
role of exchange of viruses between India and Sri Lanka in the evolution of virulent strains
of DENV-3 genotype III, which originated in India, is also important. Though the origin
of DENV-3 could not be ascertained, interestingly, our studies revealed that DENV-4 may
have originated in India. This corroborates with a report that dengue virus separated into
distinct serotypes independently because of geographical partitioning of different primate
populations.44
India thus continues to play a crucial role in the establishment, evolution and global
dispersal of the four DENV serotypes. The existence of DENV in India and the major
mosquito vector species for DENV transmission since early times is well known.78,79,15
The unprecedented population growth, increased population density, unplanned and
uncontrolled expanding urbanization, climatic factors, water storage pattern in houses
and waste management practices, coupled with increased density of the vector mosquito,
infestation of new geographical areas by vector mosquitoes and inadequate mosquito control
measures, have contributed to the establishment and evolution of the DENV serotypes in
the country.80,81,82,50 India’s role during the Second World War and its strategic location at
the tip of the Indian Ocean facilitating global movements in the aftermath of the war may
have been significant for the propagation of the virus.42 In recent times increased air travel
as a consequence of trade and tourism has further contributed to the dissemination of
DENV viruses. So also, the emergence of diversity of the DENV genotypes in more recent
times, coincides with human population growth, urbanization, massive human movement,
and with the reports of the first cases of DHF in Asia.83 Overall several factors, other than
geographic proximity, also affect the continual dispersion and reintroduction of new DENV
variants in different regions and understanding of these should help in the management and
control of DENV spread.
Acknowledgments
The authors thank Dr Cecilia D., Dr J. Patil and Mr A.M. Walimbe for their contributions and
vital roles in the studies undertaken at the NIV, Pune. We also acknowledge the financial
support from ICMR, Government of India, New Delhi.
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Phylodynamics of dengue viruses in India vis-à-vis the global scenario
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[36] Kurukumbi M, Wali JP, Broor S, Aggarwal P, Seth P, Handa R, et al. Seroepidemiology and active
surveillance of denguefever/dengue haemorrhagic fever in Delhi. Indian J Med Sci. 2001 Mar;55(3):149–
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of the envelope gene of dengue virus Type 1.Virology. 2002;303:110–9.
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viruses reveals the role of India. Infection, Genetics and Evolution. 2014;22:30–9.
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[44] Twiddy SS, Holmes EC, Rambaut A. Inferring the rate and time scale of dengue virus evolution. Mol
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replacement of American genotype dengue type 2viruses I India (1956–2005): selection pressure and
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[52] Lewis JA, Chang GJ, Lanciotti RS, Kinney RM, Mayer LW, Trent DW. Phylogenetic relationships of
dengue-2 viruses. Virology 1993;197, 216–24.
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[53] Cardosa J, Ooi MH, Tio PH, Perera D, Holmes EC, Bibi K, et al. Dengue virus serotype 2 from a sylvatic
lineage isolated from a patient with dengue hemorrhagic fever. PLoS Negl Trop Dis. 2009;3(4):e423.
[54] de A Zanotto PM, Gould EA, Gao GF, Harvey PH, Holmes EC,. Population dynamics of flaviviruses
revealed by molecular phylogenies. Proc Natl Acad Sci. USA.1996;93:548–53.
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2001. Emerg Infect Dis. 2004;10:719–22.
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the continued emergence of sylvatic dengue virus and its impact on public health. Nat Rev Microbiol.
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Dis. 2006;12(2):352–353.
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virus type 4 (genotype I) in India. Epidemiol Infect. 2011;139(6):857–61.
[64] Cecilia D, Kakade MB, Bhagat AB, Vallentyne J, Singh A, Patil JA, et al. Detection of Dengue-4 virus
in Pune, Western India after an absence of 30 years–its association with two severe cases. J Virol.
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[65] Melo FL, Camila MR, Paolo M, Zanotto A. Introduction of dengue virus 4 (DENV-4) genotype I into
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Arabia: 1994 to 2006. Trop Med Int Health. 2008;13(4):584–92.
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Aedesaegyptis populations revealed by Mitochondrial DNA. PLoS Negl Trop Dis. 2013;7(4):e2175.
[71] Gaunt MW, Sall AA, de Lamballerie X, Falconar AK, Dzhivanian TI, Gould EA. Phylogenetic relationships
of flaviviruses correlate with their epidemiology, disease association and biogeography. J Gen Virol.
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type 1 and 2 dengue viruses in Brazil from 1988 to 2001. Braz J Med Biol Res. 2005;38(6):843–852.
[74] Weaver SC, Vasilakis N. Molecular evolution of dengue viruses: contributions of phylogenetics to
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[75] Dorji T, Yoon IK, Holmes EC, Wangchuk S, Tobgay T, Nisalak A. Diversity and origin of dengue virus
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[76] Podder G, Breiman RF, Azim T, Thu HM, Velathanthiri N, Mai le Q, et al. Origin of dengue type 3
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61
Association of dengue symptoms with
haematological parameters: a retrospective study of
10 hospitals in India
BK Tyagia#, S Karthigai Selvia, Vidya Chellaswamya, NK Arorab, Donald S Shepardc,
Yara A Halasac, Mukul Gabab, Deoki Nandand, Vivek Adhishd, T Mariappana,
P Philip Samuela, R Paramasivana, and the INCLEN Study Groupe
a
Centre for Research in Medical Entomology (ICMR), Madurai, Tamil Nadu, India
International Clinical Epidemiology Network (INCLEN) Trust International, New Delhi, India
b
Brandeis University, Waltham, MA, USA
c
National Institute of Health and Family Welfare, New Delhi, India
d
INCLEN Study Group: Harish Pemde (Lady Hardinge Medical College and KSCH Hospital,
New Delhi, India), Anurag Tomar (National Institute of Medical Sciences, Jaipur, Rajasthan, India),
Varadarajan Poovazhagi (Madras Medical College, Chennai, Tamil Nadu, India), Pawan Kumar
(Kasturba Medical College, Manipal, Karnataka, India), Ashok Mishra (JA Group of Hospitals
and GR Medical College, Gwalior, Madhya Pradesh, India),VK Srivastava (Integral Institute of
Medical Sciences and Research, Lucknow, Uttar Pradesh, India), Basanta Kumar Behera (Kalinga
Institute of Medical Sciences, Bhubaneswar, Odisha, India), Ranbir L Singh (Regional Institute
of Medical Sciences, Imphal, Manipur, India), Bhadresh R Vyas (MP Shah Medical College, GG
Hospital, Jamnagar, Gujarat, India), Pallavi Shelke (LTM Medical College and General Hospital,
Mumbai, Maharashtra, India).
e
Abstract
The clinical diagnosis of dengue is challenging because of dynamic clinical presentations. This study
was designed to describe the clinico-haematological parameters by assessing (i) the incidence of
thrombocytopenia in dengue infection, and (ii) the association between bleeding manifestations
with platelet count and severity of dengue infection. A multicentre study was conducted at national
level between 2010 and 2012 among 10 medical colleges cum tertiary care hospitals from 10
states across five regions in India. Data collected from these selected hospitals were compared.
Platelet count of <100 000/l was observed in 881 (73.36%) dengue fever (DF) cases, 121 (85.82%)
dengue haemorrhagic fever (DHF) cases and 66 (75.86%) dengue shock syndrome (DSS) cases, in
which 52.53% was reported among children. There was not much difference in the severity level of
thrombocytopenia in all age groups. The percentages of developing haemorrhagic manifestations in
patients with DF, DHF and DSS were 26.69%, 68.60% and 50.65%, respectively; there were 38.70%
occurring in patients with platelet count <50 000. The patients with a raised haematocrit of >40%
#
E-mail: [email protected]; [email protected]
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Association of dengue symptoms with haematological parameters: a retrospective study of 10 hospitals in India
and thrombocytopenia (platelet count <50 000) were observed to be marginally at risk of getting
haemorrhagic symptoms. There were patients with severe thrombocytopenia (platelet <50 000)
who had no prior bleeding whereas some patients with normal platelet value (>100 000) had
bleeding manifestations. The haemorrhagic manifestation was significantly related to the severity of
thrombocytopenia in DF cases, but there was no significant association found between the bleeding
symptoms and the degree of thrombocytopenia among the patients progressing to DHF/DSS as
57.14% and 35.29% of patients having platelet count >100 000/l had bleeding manifestations.
The changing clinical pattern of disease shows the heterogeneity in severity of dengue infection as
the clinical bleeding manifestations have no direct relationship with the degree of platelet count
especially in case of DHF/DSS.
Keywords: Dengue, clinical presentation, haemorrhagic manifestation, thrombocytopenia, India.
Introduction
Dengue with its two deadly manifestations, that is, dengue haemorrhagic fever (DHF) and
dengue shock syndrome (DSS), has emerged as one of the major arboviral infections in the
world in terms of morbidity, mortality and economic burden.1,2 The infection is by now viewed
as a global epidemic with recorded prevalence in more than 125 countries.3 Worldwide an
estimated 3.6 billion people (over 50% of the world’s population)4 are at risk of infection
with more than 50 million new infections occurring annually; between 250 000 and 500 000
had severe infection and required hospital admission and there were 20 000–25 000 deaths,
mainly in children.5 Although the global burden of the disease is uncertain, the increasing
incidence with geographical expansion and changing disease patterns is alarming both
for public health and the global economy. India represents significantly a larger burden,
accounting for nearly 34% of the global burden of apparent dengue infection, with regular
reporting of dengue outbreaks compared to other countries.6,7 The cost of dengue illness
was estimated as high as US$1.1 billion or US$0.88 per capita and the direct medical cost
of care accounted for US$545 million or US$0.43 per capita in 2012 in India.7 There is
currently no effective vaccine or antiviral drug for dengue but early detection and proper
prognostication may reduce adverse complications and lower fatality rate.
Clinical presentation of dengue fever shows heterogeneity in severity along a wide
spectrum of signs and symptoms. Typically, it may be subclinical or may manifest a range from
a self-limiting fever to a severe form, DHF, which may progress to shock (DSS) and finally,
death. Despite rapid advancement in dengue laboratory tests, the availability and accessibility
of diagnostic facilities and adhering to universal diagnostic guidelines was limited in India.
As per the guidelines of World Health Organization (WHO), the diagnosis and laboratory
criteria including the isolation of dengue virus/demonstration of fourfold change/detection of
viral genomic sequence is not being performed to confirm DF/DHF/DSS in India and most
dengue diagnosis is primarily made based on clinical and other laboratory recognition. The
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Association of dengue symptoms with haematological parameters: a retrospective study of 10 hospitals in India
clinical diagnosis of DHF/DSS is not easy in the early phase of illness which requires the
presence of four criteria, including haemorrhagic manifestations and thrombocytopenia as
per WHO case definition.8 In recent decades, several studies have reported the conflicting
association between the platelet count and the presence or the magnitude of bleeding
manifestation and bleeding tendency that did not differentiate DF and DHF.9–14 Although
thrombocytopenia and bleeding manifestation are the key diagnostic criteria of DHF, it is also
commonly observed in mild DF and many patients progress to DHF/DSS without having any
bleeding manifestations. The clinical diagnosis of dengue is challenging because of dynamic
clinical presentations on the one hand and difficulty in reliability in terms of differentiating
dengue from other febrile illness clinically, on the other hand. A retrospective study was
conducted to understand the dengue infection in the population across different regions in
India over six years (2006–2011). The present communication highlights the observation
on the clinico-haematological parameters and their role in prediction of severity of dengue
infections, especially with an intent to assess (i) the incidence of thrombocytopenia in dengue
infection, and (ii) the association between bleeding manifestations with platelet count and
severity of dengue infection.
Material and methods
Study design
This study was part of a cross-sectional, hospital-based retrospective study conducted at
national level between 2010 and 2012 in India. The sample of 10 medical colleges cum
tertiary care hospitals was selected from 10 states across five regions in India to understand
the range of dengue illness in the concerned state and region. Out of the selected samples,
two hospitals were paediatric hospitals and remaining were general hospitals. The selection of
study sites, sampling procedures, study framework and methodology were published earlier.7,15
The medical records of the patients who were hospitalized during January 2006 through
December 2011 with a clinical discharge diagnosis of patients with dengue/DHF/DSS (ICD10
code A90) formed the sample frame. A systematic random sample of 1665 medical records of
hospitalized patients discharged with diagnosis of dengue was reviewed and analysed. A data
extraction instrument was developed to collect the required data from the medical records.
The collection tool was focused on (1) socio-demographic details; (2) date of admission
and discharge; (3) referral facility; (4) admission and discharge diagnosis; (5) patient’s
report of ambulatory visit/hospitalization prior to hospitalization at study sites; (6) patient’s
report of date of onset of illness; (7) setting (casualty/ICU/ward/private room); (8) length
of stay (nights) and total duration of illness through discharge; (9) signs and symptoms;
(10) patient’s temperature and blood pressure measurements at admission and discharge;
(11) haematological and biochemical profile; and (12) reclassification of dengue cases as
per the WHO classification.
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Association of dengue symptoms with haematological parameters: a retrospective study of 10 hospitals in India
Laboratory and haematological profile
The performance status of serological investigations such as IgM, IgG capture ELISA and
NS1 antigen along with tourniquet test were retrospectively collected and recorded.
Additionally, haematological parameters including haemoglobin (Hb), total leukocyte count
(TLC), haematocrit (HCT), platelet count and liver function tests such as serum aspartate
aminotransferase (AST) and serum alanine aminotransferase (ALT) were also recorded. Along
with this details of those patients who underwent chest X-ray and ultrasound examination
of the abdomen were also recorded.
Statistical analysis
The SPSS version 16.0 was used for statistical analysis. Chi-square or Fisher’s exact test
were used to assess the statistical difference between categorical variables among dengue
groups. Comparisons of means of continuous variables were performed using ANOVA and
Kruskal-Wallis Tests. Relative Risk (RR) was calculated to evaluate the risk exposure between
two groups. Correlations were analysed through Pearson’s coefficient. A p-value of less than
0.05 was considered as significant for all analyses.
Results
Disease presentation of dengue cases
A total of 1665 medical records were randomly sampled from 10 medical hospitals, in which
data from 1541 medical records were reviewed and included for the analysis. Among 1541
cases, 1302 (84.49%), 147(9.54%) and 92 (5.97%) had provisional discharge diagnosis of DF,
DHF and DSS, respectively, in which 0.7% of cases have reported co-infection with other
febrile illnesses. A dengue serological test was done for 1182 (76.70%) patients, in which
about 943 (79.78%) were found to be seropositive to dengue. The primary infection with
IgM positive was 658 (55.67%) whereas secondary infection with IgM and IgG both were
positive in 169 (14.30%) patients. Only IgG positive was detected in 85 (7.19%) patients,
which contributed about 21.49% of secondary infections in our study. A case fatality risk (CFR)
in our study was 4.61% with 71 patients’ deaths. The mortality appears greatest with 3.18%
(49 patients) in the first 24–48 hours of their hospitalization, in which 28 patients (1.82%)
died before they had the opportunity to undergo diagnostic investigations. Though geriatric
population (age >60) contributed 36 (3.75%) cases of hospitalization, they understandably
exhibited a high mortality rate of 14.29%. Thus the geriatric population was also proved to
be at a risk equal to that of children in terms of dengue mortality.
Dengue Bulletin – Volume 39, 2016
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Association of dengue symptoms with haematological parameters: a retrospective study of 10 hospitals in India
Duration of illness and utilization of health care services
The infected patients normally do not seek professional help at tertiary hospital at onset
of infection, but wait until the disease has worsened. About 311 (20.18%) patients were
treated in primary or secondary care units and referred at the point where hospitalization is
required for tertiary care management. About 21.64%, 59.71% and 18.65% patients sought
professional help for hospitalization at a tertiary care study site at 0–3, 4–8 and >8 days
respectively (Figure 1) with an average (SD) of 6.51(±5.24) days after the onset of illness,
including an average of 2.81 nights of hospital stay and 1.38 ambulatory visits that may have
taken place either at primary or secondary health care facilities. Only 174 (11.29%) cases
sought health care facilities within 48 hours from onset of the disease. The average duration
of hospitalization and total duration of illness until discharge was observed as 5.65 (±4.12)
and 12.16 (±6.86) nights, respectively.
Socio-demographic characteristics
Table 1 summarizes the socio-demographic characteristics of the hospitalized dengue patients.
Overall sex ratio (male: female) for dengue cases was 1.76:1 (64% and 36%, respectively).
The data collected from two paediatric hospitals (n=581) indicated that number of cases
in the age group of 0–1, 1–4 and 5 and above years were 76 (13.08%), 140 (24.10%) and
365 cases (62.82%), respectively, in which the high incidence of 10.53% of dengue death
Figure 1: Percentage of dengue patients admitted at study sites (n=1539)
Percentage of dengue patients
18.0
16.0
14.0
12.0
10.0
8.0
6.0
4.0
2.0
0.0
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
Duration of illness before hospitalization into study sites
66
15 More
than
15
days
Dengue Bulletin – Volume 39, 2016
Association of dengue symptoms with haematological parameters: a retrospective study of 10 hospitals in India
was reported among the infants (0–1 years). The mean (±SD) age of the patients was 6.51
(±4.52) years. The data from the general hospitals revealed that a maximum number of 534
(55.63%) cases were in the age group of 15–44 years, followed by <15 years (29.48%). The
age distribution was not statistically significant among dengue groups and mean age was
observed as 24.79 (±17) years.
Laboratory investigation
The median platelet counts in DF, DHF, and DSS were 60 000, 47 000 and 40 000,
respectively (p=0.001). The mean Hct values across the groups do not show a difference
statistically (p=0.582). More than 40% of haematocrit was observed in 198 (31.58%) cases.
The mean ALT in DF, DHF and DSS was 136.71U/L, 361.31U/L and 243.22U/L, respectively
(p=0.032). About 59.75% and 15.98% of patients had elevation of ALT 40–200 and above
200 U/L, respectively. A statistically significant association was not found with regard to AST
between the dengue groups. Elevation of AST >200 U/L was found in 25.63% of dengue
patients. The basic characteristic of subjects is shown in Table 1.
A platelet count of <100 000/l was observed in 881 (73.36%) DF, 121 (85.82%) DHF
and 66 (75.86%) DSS, in which 52.53% was reported among children. Of the 1068 (74.74%)
patients with thrombocytopenia (platelet count <100 000), 184 (12.88%) had severe
thrombocytopenia (platelet count <20 000), followed by 428 (29.95%) who had moderate
thrombocytopenia (platelet count 20 000–50 000). Though the severity of thrombocytopenia
was found to be high in age group <15 years, it was also equivalently reported in other
age groups (>15 years). A statistically significant association was found between the age,
haematocrit rise, serologically positive cases and platelet group except between the sex and
platelet group (p-value 0.176).
Clinical presentation
The development of haemorrhagic manifestations as seen in patients with DF, DHF, and
DSS were 26.69%, 68.60% and 50.65%, respectively, with 38.70% occurring in patients
with platelet count <50 000. The patients with a raised haematocrit of >40% and
thrombocytopenia (platelet count <50 000) were observed to be marginally at risk of getting
haemorrhagic symptoms. There were 22 and 282 dengue patients who developed severe
thrombocytopenia (platelet count <10 000 and platelet <50 000, respectively) without
prior bleeding whereas some patients with normal platelet value (>100 000) had bleeding
manifestations. The bleeding manifestation was not statistically associated with age groups
(p-value 0.051) and was commonly reported in both groups (Table 3).
Table 2 and Figure 2 show the association between the platelet count and dengue
classification with presence of bleeding symptom. Ironically, the haemorrhagic manifestation
was significantly related to the severity of thrombocytopenia in DF cases, but there was
Dengue Bulletin – Volume 39, 2016
67
68
100 (22.7)
289 (65.5)
6.81 ± 4.566
1-4
5 and above
Mean ± SD
90 (10.5)
32 (3.7)
45-60
>60
Haemoglobin (g/dL)
Haematological
Male (n, %)
Sex
11.427 ± 2.73
849 (65.2)
24.65 ± 16.765
490 (56.9)
15-44
Mean ± SD
162 (18.8)
72 (8.4)
1-4 years
5-14 years
15 (1.7)
<1
Age group (Year) ^^(n, %)
52 (11.8)
DF (n = 1302)
Mean ± SD
<1
Age group (Year) ^(n, %)
Demographic
Patient profiles
11.143 ± 2.69
81 (55.1)
27.37 ± 17.05
1 (1.7)
13 (21.7)
29 (48.3)
13 (21.7)
3 (5.0)
1 (1.7)
5.34 ± 4.204
43 (49.4)
31 (35.6)
13 (14.9)
DHF (n =147)
Mean ± SD
11.901 ± 2.66
53 (57.6)
23.79 ± 21.57
3 (7.7)
4 (10.3)
15 (38.5)
13 (33.3)
3 (7.7)
1 (2.6)
5.91 ± 4.373
33 (62.3)
9 (17.0)
11 (20.8)
DSS (n = 92)
Mean ± SD
1397
983
960
36
107
534
188
78
17
581
365
140
76
No. of
patients
0.138
0.024*
0.226
0.016*
P-value
Table 1: Patient profiles by types of dengue infection: clinical dengue fever (DF), dengue haemorrhagic fever (DHF) and
dengue shock syndrome (DSS)
Association of dengue symptoms with haematological parameters: a retrospective study of 10 hospitals in India
Dengue Bulletin – Volume 39, 2016
Dengue Bulletin – Volume 39, 2016
320 (26.6)
84 796 ± 79 313
> 100 000
Mean ± SD
0-40 units
AST (U/L)
Median
Mean ALT (SD)
134 (23.6)
71
136.71 ± 249.66
82 (15.1)
321 (59.0)
>40-200 units
>200 units
141 (25.9)
0-40 units
ALT (U/L)
Biochemical
36.76 ± 7.55
166 (32.6)
Above 40 gm.
Mean haematocrit(SD)
343 (67.4)
0-40 gm.
Haematocrit (PCV), (%)
60 000
389 (32.4)
50 000-100 000
Median
492 (41.0)
DF (n = 1302)
Mean ± SD
< 50 000
Platelet (/µL)
Patient profiles
9 (14.1)
93
361.31 ± 129.20
9 (14.5)
44 (71.0)
9 (14.5)
36.09 ± 8.66
21 (30.9)
47 (69.1)
47 000
66 450 ± 64 335
20 (14.2)
48 (34.0)
73 (51.8)
DHF (n =147)
Mean ± SD
8 (16.7)
88
243.22 ± 567.81
13 (28.9)
24 (53.3)
8 (17.8)
35.79 ± 6.72
11 (22.0)
39 (78.0)
44 000
73 370 ± 73 779
21 (24.1)
19 (21.8)
47 (54.0)
DSS (n = 92)
Mean ± SD
151
651
651
104
389
158
627
198
429
1429
1429
361
456
612
No. of
patients
0.032*
0.582
0.001**
P-value
Association of dengue symptoms with haematological parameters: a retrospective study of 10 hospitals in India
69
70
38 (2.9)
87
12 (8.2)
85
239.70 ± 467.98
21 (32.8)
34 (53.1)
DHF (n =147)
Mean ± SD
21 (22.8)
97.5
397.73 ± 1140.4
17 (35.4)
23 (47.9)
DSS (n = 92)
Mean ± SD
^Paediatric hospital; ^^General hospital; *Significant at 5% level **Significant at 0.5% level ***Significant at 0.1% level
Dead (n, %)
Case management
Median
169.93 ± 263.36
136 (24.0)
>200 units
Mean AST (SD)
297 (52.4)
DF (n = 1302)
Mean ± SD
>40-200 units
Patient profiles
71
679
679
174
354
No. of
patients
0.0001***
0.259
P-value
Association of dengue symptoms with haematological parameters: a retrospective study of 10 hospitals in India
Dengue Bulletin – Volume 39, 2016
Dengue Bulletin – Volume 39, 2016
119/138(86.23)
Dengue serology positive cases (n, %)
51/173 (29.48)
269/331 (81.27)
285/334 (85.33)
221 (34.05)
235 (30.1)
294/456 (64.5)
9/16 (56.25)
19 (21.84)
23/41 (56.10)
48 (34.04)
72/260 (27.69)
389 (32.39)
104/317 (32.81)
456 (31.91)
50 000/μl to
100 000/μl
61/170 (35.88)
189 (29.12)
239 (30.6)
281/428 (65.7)
15/28 (53.57)
30 (34.48)
30/41 (73.17)
48 (34.04)
72/252 (28.57)
350 (29.14)
117/321 (36.45)
428 (29.95)
20 000/μl to
50 000/μl
*Significant at 1% level **Significant at 0.5% level ***Significant at 0.1% level
48/102(47.06)
97 (14.95)
15 and above
Haematocrit ≥ 40%
87 (11.2)
115/184(62.5)
5/11 (45.45)
17 (19.54)
17/20 (85.00)
25 (17.73)
39/108 (36.11)
<15 years
Age
Male (n, %)
Gender
No. of DSS cases with bleeding
symptoms
No. of DSS cases
No. of DHF cases with bleeding
symptoms
No. of DHF cases
No. of DF cases with bleeding
symptoms
142 (11.82)
61/139 (43.88)
No. of patients with bleeding (%)
No. of DF cases
184 (12.88)
<20 000/μl
No. of cases of dengue infection
Characteristic
Platelet count
102/146 (69.86)
22/98 (22.45)
88 (13.56)
103 (13.2)
128/191 (67.0)
4/10 (40.00)
12 (13.79)
6/8 (75.00)
9 (6.38)
22/96 (22.92)
170 (14.15)
32/114 (28.07)
191 (13.37)
100 000/μl to
150 000/μl
120/136 (88.24)
15/79 (18.99)
54 (8.32)
116 (14.9)
95/170 (55.9)
2/7 (28.57)
9 (10.34)
2/6 (33.33)
11 (7.80)
13/95 (13.68)
150 (12.49)
17/108 (15.74)
170 (11.90)
Above 150 000/
μl
895
197
649
780
913
35
87
78
141
218
1201
331
1429
Total
0.000***
0.000***
0.001**
0.176
0.749
0.055
0.006*
0.001**
p- value
Table 2: Association of bleeding manifestation, gender, age groups and haematocrit value with platelet counts
Association of dengue symptoms with haematological parameters: a retrospective study of 10 hospitals in India
71
Association of dengue symptoms with haematological parameters: a retrospective study of 10 hospitals in India
Table 3: Association of bleeding to age, PCV, platelet count and dengue infection
Characteristics
Bleeding
Non-bleeding
N
RR (95% of C.I.)
p-value
Age, n
<15 years
187
424
611
15 and above
172
303
475
> 40.0 %
116
184
300
< 40.0 %
44
102
146
< 50 000/μL
178
282
460
>50 000/μL
153
386
539
237
651
888
DHF
83
38
121
DSS
39
38
77
0.845 (0.714-1.001)
0.051
1.283 (0.965-1.706)
0.078
1.363 (1.142-1.627)
0.001*
PCV, n
Platelet count, n
Disease category, n
DF
0.000**
* Significant at 0.5% level ** Significant at 0.1% level
no significant association found between the bleeding symptoms and the degree of
thrombocytopenia among the patients progressing to DHF/DSS, as 57.14% and 35.29%
of patients having platelet count >100 000/l had bleeding manifestations. Haematemesis,
melena, epistaxis and gum bleeding except petechial rash were significantly more common
in adults when compared to children (Table 4).
Limitation
This study has some unavoidable limitations, since the study was conducted at tertiary care
units only, the frequency of thrombocytopenia was observed to be high as the clinicians
typically treated patients whose condition was severe in nature and who had often been
referred by primary/secondary care units. At the same time, the effectiveness of the
study was directly influenced by the availability, completeness, accuracy and systematic
recording of patient’s medical/laboratory investigations history in the medical records as the
retrospectively collected data seemed to be inadequate, especially in documenting the course
of pre-hospitalization, missing values/lack of notifying regarding clinical observations during
hospital stay and the strategy of treating severe bleeding (platelet transfusion). Another likely
72
Dengue Bulletin – Volume 39, 2016
Association of dengue symptoms with haematological parameters: a retrospective study of 10 hospitals in India
Figure 2: Association of bleeding manifestation with platelet counts by
types of dengue infection
No.of DF cases with bleeding symptoms
% of patients with bleeding manifestation
100
No.of DHF cases with bleeding symptoms
90
No.of DSS cases with bleeding symptoms
80
70
60
50
40
30
20
10
0
<20,000/µl
20,000/µl to
50,000/µl
50,000/µl to
100,000/µl
100,000/µl to
150,000/µl
Above
150,000/µl
Platelet count
limitation is the absence of dengue diagnostic testing and laboratory investigations of some
dengue patients. These bottlenecks were, however, overcome by inclusion of both private
and public facilities from all regions of India, thereby facilitating a better understanding of
the study parameters.
Discussion
This study highlights the association between the haematological parameters with bleeding
manifestations and severity of dengue infection. The demographic profile of the patients
revealed that the proportion of dengue cases for the age group of 15–44 was highest, which
is consistent with other Indian studies.16,17 The geriatric population exhibited lowest infection
incidence but registered highest mortality rate (14.29%), followed by paediatric (0–1 year)
who contributed about 11.81% in accordance with other similar observations.18 The mean
age of the dengue cases (admitted in general hospitals) was 24.79 (±17) years, indicating
that the majority of cases are in productive working age. It indicates that the adults were
infected eccentrically compared to that of children, which is corroborated by other studies.19,21
Dengue Bulletin – Volume 39, 2016
73
74
48/447 (10.74)
561/780 (71.92)
71/343 (20.70)
Other bleeding sites^
Platelet count <100 000 cells/cum (%)
Haematocrit ≥ 40%
127/284 (44.72)
507/649 (78.12)
37/321 (11.53)
63/290 (21.72)
63/276 (22.83)
46/264 (17.42)
Adults
198/627
1068/1429
85/768
91/576
122/601
140/623
N
^Other bleeding sites include epistaxis, gum bleeding, haematuria etc; *Significant at 1% level **Significant at 0.1% level
28/286 (9.79)
59/325 (18.15)
Malena
Haematemesis/ Blood in vomits
94/359 (26.18)
Children
Petechial rash, ecchymoses or purpura
No of patients with
Bleeding disorder
1.434 (1.275-1.614)
0.921 (0.867-0.977)
0.932 (0.622-1.396)
0.451 (0.298-0.682)
0.795 (0.579-1.092)
1.503 (1.097-2.059)
RR (95% of C.I.)
0.000**
0.007*
0.731
0.000**
0.156
0.01*
p-value
Table 4: Patients with clinical bleeding and laboratory features by comparing children and adults with dengue infection
Association of dengue symptoms with haematological parameters: a retrospective study of 10 hospitals in India
Dengue Bulletin – Volume 39, 2016
Association of dengue symptoms with haematological parameters: a retrospective study of 10 hospitals in India
Although the thrombocytopenia is one of the predicting components in measuring severity
of disease or a bleeding tendency, it was also commonly observed in DF. As compared to
DF patients, patient with DHF/DSS have lower platelet counts. The bleeding tendency was
also significantly observed in DF, although it was characteristically observed in DHF patients.
Statistical analysis showed a significant association between haemorrhagic manifestations and
the degree of thrombocytopenia, but only in context with DF cases. As disease progresses
to DHF/DSS, the relationship between the degree of thrombocytopenia and bleeding
manifestations becomes less pronounced. There are some patients who developed severe
thrombocytopenia (platelet level <10 000) without bleeding manifestations, whilst others
had bleeding manifestations with a platelet count of >100 000.22,23 In our analysis, platelet
counts were not very much supportive in predicting severity of dengue infection or a bleeding
tendency, suggesting that there are likely other important factors, apart from the platelet
count, which also play a role in determining severity and bleeding tendency in dengue
infection.22,24 A high haematocrit value was significantly associated with the decreasing value
of thrombocytopenia but only a weak correlation was observed.
In summary, although the severity of thrombocytopenia and development of bleeding
tendency is characteristically demonstrated in patients with DHF/DSS, it has been also
commonly observed at significant level in DF patients. Furthermore, the clinical bleeding
manifestations have no direct relationship with the degree of platelet count, especially in case
of DHF/DSS. The changing clinical pattern of disease shows the heterogeneity in severity, on
the one hand, and the necessity for further clinico-haematological research to comprehend
the role of platelets in pathogenesis of dengue infection, on the other.
Acknowledgements
Authors are thankful to the Secretary, Department of Health Research, Government of India,
and the Director General, Indian Council of Medical Research, New Delhi, for permission
and encouragement. Authors are also thankful to various medical and health institutions
across the country for providing help at all levels of this project.
Conflict of interest
The authors declare that they don’t have any conflict of interest.
References
[1] Gubler DJ. Epidemic dengue/dengue hemorrhagic fever as a public health, social and economic problem
in the 21st century. Trends Microbiol. 2002;10:100-103.
[2] World Health Organization. Global strategy for dengue prevention and control 2012-2020. Geneva:
WHO, 2012.
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Association of dengue symptoms with haematological parameters: a retrospective study of 10 hospitals in India
[3] Ferreira GL. Global dengue epidemiology trends. Rev Inst. Med Trop Sao Paulo. 2012;54(18):S5–6.
[4] ME, Letson GW, Margolis HS. Estimating the global burden of dengue. In: Abstract Book: Dengue
2008. Proceedings of the 2nd International Conference on Dengue and Dengue Haemorrhagic Fever.
Phuket, 2008.
[5] World Health Organization, Regional Office for South-East Asia. Comprehensive guidelines for
prevention and control of dengue and dengue haemorrhagic fever. New Delhi: WHO, 2011.
[6] Bhatt S, Gething PW, Brady OJ, Messina JP, Farlow AW, Moyes CL, et al. The global distribution and
burden of dengue. Nature. 2013;496(7446):504-7.
[7] Shepard DS, Halasa YA, Tyagi BK, Adhish SV, Nandan D, Karthiga KS, et al., Economic and disease
burden of dengue illness in India. Am J Trop Med Hyg 2014;91(6):1235-42.
[8] World Health Organization. Dengue hemorrhagic fever: diagnosis, treatment, prevention and control.
Geneva: WHO, 1997.
[9] Balmaseda A, Hammond S, Perez M, Cuadra R, Solano S, Rocha J, et al. Short report: assessment of
the World Health Organization scheme for classification of dengue severity in Nicaragua. Am J Trop
Med Hyg. 2005;73:1059–62.
[10] Bandyopadhyay S, Lum LC, Kroeger A. Classifying dengue: a review of the difficulties in using the
WHO case classification for dengue haemorrhagic fever. Trop Med Int Health. 2006;11(8):1238–55.
[11] Anon Srikiatkhachorn, Robert V. Gibbons, Sharone Green, Daniel H. Libraty, Stephen J. Thomas,
Timothy P. Endy, et al. Dengue Hemorrhagic Fever: the sensitivity and specificity of the WHO definition
in identifying severe dengue cases in Thailand, 1994-2005. Clin Infect Dis. 2010;50(8):1135–1143.
[12] Daniel R, Rajamohanan, Philip AZ. A study of clinical profile of dengue fever in Kollam, Kerala, India.
Dengue Bull. 2005;29:197-202.
[13] DeepinderKaurChhina, OmeshGoyal, PrernaGoyal, Raj Kumar, SandeepPauri&RajooSingh Chhina.
Haemorrhagic manifestations of dengue fever & their management in a tertiary care hospital in north
India. Indian J Med Res. 2009; 129:718-720.
[14] Makroo RN, Raina V, Kumar P, Kanth RK. Role of platelet transfusion in the management of dengue
patients in a tertiary care hospital. Asian J Transl Sci. 2007;1: 4-7.
[15] Halasa YA, Dogra V, Arora N, Tyagi BK, Nandan D, Shepard DS. Overcoming data limitations: design
of a multi-component study for estimating the economic burden of dengue in India. Dengue Bull.
2011;34:1-14.
[16] Kumar A, Rao CR, Pandit V, Shetty S, Bammigatti C, Samarasinghe CM. Clinical manifestations and
trend of dengue cases admitted in a tertiary care hospital, Udupi district, Karnataka. Indian J Community
Med. 2010;35:386-90.
[17] Gupta E, Dar L, Narang P, Srivastava VK, Broor S. Serodiagnosis of dengue during an outbreak at a
tertiary care hospital in Delhi. Indian J Med Res. 2005;121:36-8.
[18] Guzman MG, Kouri G, Bravo J, Valdes L, Vazquez S, Halstead SB. Effect of age on outcome of secondary
dengue 2 infections. Int J Infect Dis. 2002;6:118–124.
[19] Goh KT. Dengue- a re-emerging infectious disease in Singapore. Ann Acad Med Singapore. 1997;26:664670.
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[20] Sumarmo. Dengue haemorrhagic fever in Indonesia. Southeast Asian J Trop Med Public
Health. 1987;18:269-274.
[21] Rahman M, Rahman K, Siddque AK, Shoma S, Kama AHM, Ali KS, et al. First outbreak of dengue
hemorrhagic Fever, Bangladesh. Emerg Infect Dis. 2002;8:738-740.
[22] Narayanan M, Aravind MA, Thilothammal N, Prema R, Sargunam CS, Ramamurty N. Dengue fever
epidemic in Chennai-a study of clinical profile and outcome. Indian Pediatr. 2002;39:1027–33.
[23] Sharma S, Sharma SK. Clinical profile of DHF in adults during 1996 outbreak in Delhi, India. Dengue
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[24] Mendez A, Gonzalez G. Dengue haemorrhagic fever in children: ten years of clinical experience.
Biomedica. 2003;23:180–193.
Dengue Bulletin – Volume 39, 2016
77
Estimation of burden using active dengue sentinel
surveillance and fever surveillance
Zinia T Nujuma#, Achu Thomasa, Vijayakumar Ka, Thomas Mathewa, Saran S Pillaia
a
Medical College, Thiruvananthapuram, Kerala, India
Abstract
The State of Kerala in India is now hyperendemic for dengue. Thiruvananthapuram district reports
the maximum number of cases in the state. The present surveillance mechanisms rely mostly on
passive surveillance. This paper tries to estimate the burden of dengue in the district and state using
one component of active surveillance, namely sentinel surveillance, in a representative sample of
hospitals along with the fever surveillance data.
The proportion of dengue among acute febrile illness obtained by two cross sectional studies in
2011 and 2012 in Thiruvananthapuram district were projected on the fever surveillance reports
of 2006–2013 for the state and the district. The population reported in the Census 2011 was used
as denominator to calculate the incidence per 100 000.
The average incidence of dengue is estimated to be 1369 per 100 000 in the district and 1514 per
100 000 in the state, if 20% of fevers are dengue. If a lower proportion of 2.8%, obtained from
2011 study, is applied, the average estimated incidence for the state and district will be 212 and
192/100 000, respectively. Only 1–10% of the estimated cases are being reported in the state. In
the district the reported cases are only 5-40% of the real burden.
The estimated burden of disease in Kerala is high. The reported cases are only the tip of the iceberg.
The paper tries to highlight the relevance and possibilities of using good quality data for making
estimation of disease burden, citing the example of dengue.
Keywords: Dengue, incidence, iceberg, Kerala, surveillance, Thiruvananthapuram.
Introduction
Dengue is one of the most serious and fast emerging tropical mosquito-borne disease. The
burden of this most important arboviral disease is 465 000 DALYs across the globe.1 India is
heading to transform into a major hyperendemic niche for dengue infection.2 Kerala State
in India, is now hyperendemic for dengue with presence of multiple serotypes, high rates of
#
E-mail: [email protected]
78
Dengue Bulletin – Volume 39, 2016
Estimation of burden using active dengue sentinel surveillance and fever surveillance
coinfection and local genomic evolution of viral strains.3 The district of Thiruvananthapuram
reports maximum number of cases in the state.4 Active disease surveillance based on strong
health information systems is one of the salient features of the global strategy for control
of dengue fever/ dengue haemorrhagic fever (DF/DHF). The surveillance system comprises
passive surveillance, active surveillance and event-based surveillance.5 The present policies
in most health systems rely on passive surveillance or event-based surveillance. This paper
tries to estimate the burden of dengue in the district and the state, using one component
of active surveillance, namely sentinel surveillance, in a representative sample of hospitals
along with the fever surveillance data.
Methods
Two cross sectional studies were conducted in the outpatient (OP) and casualty departments
of primary, secondary and tertiary health care institutions of Thiruvananthapuram. The first
study was conducted during the period February to July 2011 and covered pre-monsoon and
monsoon seasons. The second study was conducted from January to December 2012. The
details of these studies are available from previous publications.6,7 Patients more than 5 years
old, with acute febrile illness were recruited. Among them, those who had a confirmatory
evidence of the etiology of fever other than dengue (for instance, urinary tract infection)
were excluded. RT-PCR was used as the confirmatory test for dengue in patients with fever
of less than or equal to five days and serology was used when the patients had fever of more
than five days. From these studies, the proportion of dengue among acute undifferentiated
febrile illness was calculated. The number of fever cases during the years 2006–2013 for
Thiruvananthapuram district and Kerala State were obtained from the fever surveillance data
reports of the Directorate of Health Services and the State Disease Control and Monitoring
Cell reports. The proportion of dengue from the two cross sectional studies was projected
to the total fever cases in the district and the state, to obtain the number of dengue cases
for the corresponding years. The population of the district and the state reported in the
Census 2011 was used as denominator to calculate the incidence/ 100 000. Using the
reported number of cases during these years, the percentage of estimated cases reported
was calculated. The incidence of infection was calculated using an apparent to symptomatic
dengue ratio of two and four.
Results
In the cross sectional study done in 2011, only 2.8% (95% CI 0.5-5.1), that is, 7/254 acute
febrile illnesses were dengue. In the study conducted in 2012, among the 851 cases of acute
febrile illness, 20.4% [95% CI: 17.8–23.3] were positive for dengue. The average estimated
annual number of fever cases in Thiruvananthapuram and Kerala from 2006 to 2013 was
226 501 and 2 528 956, respectively. The average number of dengue cases estimated using
the 2012 study findings is 505 791 for the state (Table1) and 45 300 for the district (Table 2).
Dengue Bulletin – Volume 39, 2016
79
Estimation of burden using active dengue sentinel surveillance and fever surveillance
Table 1: The estimates of dengue for the State of Kerala using 2012 findings
Total fever
Estimated
number of
dengue
Reported
number
Incidence
of Dengue
Incidence of
infection
(I:S -2)
Incidence of
infection
(I:S -4)
2013
3 029 138
605 827
7911
1814.52
3629.05
7258.10
2012
2 406 629
481 325
4056
1441.63
2883.25
5766.51
2011
1 927 684
385 536
1304
1154.73
2309.46
4618.91
2010
1 621 641
324 328
1019
971.40
1942.80
3885.60
2009
3 575 855
715 171
657
2142.02
4284.04
8568.08
2008
2 224 086
444 817
726
1332.28
2664.56
5329.12
2007
3 136 941
627 388
1417
1879.10
3758.20
7516.40
2006
2 309 672
461 934
2503
1383.55
2767.10
5534.19
Year
Table 2: The estimates of dengue for Thiruvananthapuram district using 2012 findings
Year
Total fever
Estimated
number of
dengue
Reported
number
Incidence
of dengue
Incidence of
infection
(I:S -2)
Incidence of
infection
(I:S -4)
2013
353 806
70 761
4188
2139.56
4279.11
8558.22
2012
269 570
53 914
2477
1630.16
3260.32
6520.64
2011
195 072
39 014
865
1179.65
2359.30
4718.60
2010
184 012
36 802
656
1112.77
2225.54
4451.07
2009
226 113
45 222
290
1367.36
2734.73
5469.45
2008
134 689
26 937
503
814.50
1629.00
3258.00
2007
270 697
54 139
800
1636.97
3273.95
6547.90
2006
178 050
35 610
1150
1076.71
2153.43
4306.86
It is 70 811 and 6342 for the state (Table 3) and the district (Table 4) if the 2011 study
findings are applied. The average incidence of dengue is estimated to be 1369 per 100 000
in the district and 1514 per 100 000 in the state, if 20% of fevers are dengue. If the result
of the 2011 findings is applied, the average estimated incidence for the state and district
will be 212 and 192/100 000, respectively. The percentage of estimated cases reported is
shown in Figures 1 and 2. The average incidence of dengue infections was estimated to
80
Dengue Bulletin – Volume 39, 2016
Estimation of burden using active dengue sentinel surveillance and fever surveillance
Table 3: The estimates of dengue for the State of Kerala using 2011 findings
Year
Total fever
Estimated
number of
dengue
Reported
number
Incidence
of Dengue
Incidence of
infection
(I:S -2)
Incidence of
infection
(I:S -4)
2013
3 029 138
84 815
7911
254.03
508.07
1016.13
2012
2 406 629
67 385
4056
201.83
403.66
807.31
2011
1 927 684
53 975
1304
161.66
323.32
646.65
2010
1 621 641
45 405
1019
136.00
271.99
543.98
2009
3 575 855
100 123
657
299.88
599.77
1199.53
2008
2 224 086
62 274
726
186.52
373.04
746.08
2007
3 136 941
87 834
1417
263.07
526.15
1052.30
2006
2 309 672
64 670
2503
193.70
387.39
774.79
Table 4: The estimates of dengue for Thiruvananthapuram using 2011 findings
Year
Total fever
Estimated
number of
dengue
Reported
number
Incidence
of Dengue
Incidence of
infection
(I:S -2)
Incidence of
infection
(I:S -4)
2013
353 806
9906
4188
299.54
599.08
1198.15
2012
269 570
7547
2477
228.22
456.44
912.89
2011
195 072
5462
865
165.15
330.30
660.60
2010
184 012
5152
656
155.79
311.58
623.15
2009
226 113
6331
290
191.43
382.86
765.72
2008
134 689
3771
503
114.03
228.06
456.12
2007
270 697
7579
800
229.18
458.35
916.71
2006
178 050
4985
1150
150.74
301.48
602.96
Dengue Bulletin – Volume 39, 2016
81
Estimation of burden using active dengue sentinel surveillance and fever surveillance
Figure1: Percentage of estimated cases of dengue reported in the state
Figure 2: Percentage of estimated cases of dengue reported in the district
82
Dengue Bulletin – Volume 39, 2016
Estimation of burden using active dengue sentinel surveillance and fever surveillance
Table 5: Age distribution of study subjects and positive cases
2011 study
Age group
Dengue positive
N=7
5–10
2012 study
Dengue negative
N=247
Dengue positive
N=174
Dengue negative
N=675
0 (0%)
5 (2%)
14 (8.0%)
52 (7.7%)
11–20
1 (14.3%)
55 (22.3%)
39 (22.4%)
67 (24.7%)
21–30
2 (28.6%)
57 (23.1%)
33 (19.0%)
31 (19.4%)
31–40
3 (42.9%)
55 (22.3%)
30 (17.2%)
123 (18.2%)
41–50
1 (14.3%)
38 (15.4%)
27 (15.5%)
87 (12.9%)
51–60
0 (0%)
21 (8.5%)
19 (10.9%)
74 (11.0%)
>60
0 (0%)
16 (6.5%)
12 (6.9%)
41 (6.1%)
be 3030-6060/100 000 for the state and 2739-5479/100 000 for the district in the worst
case scenario. Using the better case scenario, it would be 424-848/100 000 for the state and
384-767/100 000 for the district. The age distribution of the cases is shown in Table 5. All
age groups studied are affected in 2012 study, with the 11–20 year age group most afflicted.
Discussion
The proportion of dengue among acute febrile illness obtained as 20.4% and used for the
estimation of incidence is comparable with other studies.8–13 The first global estimates of total
dengue virus infections were based on an assumed constant annual infection rate among a
crude approximation of the population at risk,10% in 1 billion14 or 4% in 2 billion,15 yielding
figures of 80–100 million infections per year worldwide in 1988.15,16 This was revised to
50–100 million infections,16 although larger estimates of 100–200 million have also been
made.17 If 50–100 million cases occur worldwide, taking the denominator as 7 billion, the
incidence of dengue globally will be 700- 1000/100 000 population. India contributes to 34%
of the global burden, an estimated 47–97 million cases annually. Using these estimates, the
incidence/100 000 population will be 3900–7000, for India.18 The estimated incidence of
dengue from this study, although slightly higher than the estimated worldwide incidence, is
close to the estimates for the country. Estimates of incidence in other parts of the world place
the average annual risk of dengue at 612 cases per 100 000 (urban 727 and rural 217).19
A review of 38 cohort studies from 19 countries,18 which calculated the actual incidence, has
obtained a mean incidence of 129.7/1000 person year (standard deviation ±132). In a major
epidemic in Malaysia in 1998, the estimates were as low as 123/100 00020 and in Indonesia
it was 37/100 000 in 2012.21 Therefore, the estimates for India and that obtained in our
Dengue Bulletin – Volume 39, 2016
83
Estimation of burden using active dengue sentinel surveillance and fever surveillance
study are higher than many other nations. Infection with any of the four dengue serotypes
can be asymptomatic in 65–90%.22,23–25 The number of asymptomatics is three times more
than symptomatics. In Asians, the figures are 204.4 million (151.8–273.0) and 66.8 million
(47.0–94.4), respectively, and thus the inapparent to symptomatic (I:S) ratio is 3.20 Hence,
we chose to find the ratio of 2 and 4 for estimation in this study. A recent seroprevalence
study in Singapore showed a ratio of 23 asymptomatic cases to each reported clinical case.18
The mean I:S obtained in a review of 38 cohort studies was 4.3 (standard deviation ± 2.8).18
Thus there exists a wide variation in the report ratios of inapparent to symptomatic infections.
Passive surveillance using case definitions is labour intensive. It is also limited by the
low specificity, non-uniformity in the case definitions used and inconsistency in reporting
standards.5,26 It is especially difficult in diseases such as dengue with nonspecific clinical
manifestations. This results in underreporting/overreporting and it weakens the surveillance
systems. Effective fever surveillance is easy to establish. A web-based reporting system may
improve reporting completeness.27 It has collateral benefits for estimation of burden of
other diseases that manifest as fever. The opportunities and challenges of acting beyond the
traditional surveillance systems in favour of syndromic surveillance have been reviewed.26
The limitations of the study are the following. Children less than 5 years were excluded
from testing, but extrapolation is done to the entire population and it could be an
overestimation. However, this is not a major concern because <5 years is a small percent of
the population and does not include the peak age of symptomatic disease. Coexistence of
dengue fever with other causes of acute febrile illness may not have been picked, since those
with a definitive diagnosis of cause of fever were excluded. The estimations could be lower
than actual, if such phenomenon exists. IgM remains positive for three months; therefore,
the use of a single value might not always reflect that the present episode of fever is due
to dengue. The time points of fever surveillance and active sentinel surveillance of dengue
in this study are different. The number of samples collected was not stratified proportional
to the number of fever cases during each month. Since the district of Thiruvananthapuram
reports the maximum number of cases of dengue, the projection for the state may be a
worst case scenario. The projections are dependent on the validity and quality of the fever
surveillance in the state.
Conclusions
The estimated burden of dengue in the State of Kerala and the district of Thiruvananthapuram
are high. The reported cases represent only the tip of the iceberg. The paper tries to highlight
the relevance and possibilities of using good quality data for making estimation of disease
burden, citing the example of dengue. It adds further to the need of good quality fever
surveillance systems. Similar studies need to be done in different geographical regions to
estimate the real burden of the disease.
84
Dengue Bulletin – Volume 39, 2016
Estimation of burden using active dengue sentinel surveillance and fever surveillance
References
[1] Gubler DJ, Kuno G. Dengue and dengue haemorrhagic fever. New York: CABI Publishing, 1997.
[2] Lall R, Dhanda V. Dengue haemorrahagic fever and the dengue shock syndrome in India. Natl Med
J India. 1996;9:20.
[3] Anoop M, Aneesh I, Thomas M, Sairu P, Nabeel A K, Unnikrishnan R, Sreekumar E. Genetic
characterization of dengue virus serotypes causing concurrent infection in an outbreak in Ernakulam,
Kerala, South India. Ind J Exp Biol. 2010;48(8):849-57.
[4] State Bulletin, Thiruvananthapuram. Integrated disease surveillance project. State Surveillance Unit,
Directorate of Health Services, Government of Kerala, 2010.
[5] World Health Organization, Regional Office for South-East Asia. Comprehensive guidelines for
prevention and control of dengue and dengue haemorrhagic fever. Revised and expanded edition.
New Delhi: WHO-SEARO, 2011.
[6] Zinia TN, Vijayakumar K, Pradeep Kumar AS et al. Performance of WHO probable case definition
of dengue in Kerala, India, and its implications for surveillance and referral. Dengue Bulletin. 2012;
36:94-104.
[7] Nujum ZT, Thomas A, Vijayakumar K, Nair RR, Pillai MR, Indu PS, et al. Comparative performance of
the probable case definitions of dengue by WHO (2009) and the WHO-SEAR expert group (2011).
Pathogens and Global Health. 2014;108(2):103-110.
[8] Ahmed S, Ali N, Ashraf S, Ilyas M, Tariq WU, Chotani RA. Dengue fever outbreak: a clinical management
experience. Journal of The College of Physicians and Surgeons - Pakistan.2008;18(1):8-12.
[9] Low JG, Ooi EE, Tolfvenstam T, et al. Early dengue infection and outcome study (EDEN) – study design
and preliminary findings. Ann Acad Med Singapore. 2006;35:783-9.
[10] Vijayakumar TS, Chandy S, Sathish N, Abraham M, Abraham P, Sridharan G. Is dengue emerging as a
major public health problem? Indian J Med Res. 2005;121:100-7.
[11] Ukey PM, Bondade SA, Akulwar SL. Study of seroprevalence of dengue fever in Central India. Indian
J of Community Med. 2010;35(4):517-19.
[12] Kumar R, Tripathi P, Tripathi S, Kanodia A, Pant S, Venkatesh V. Prevalence and clinical differentiation
of dengue fever in children in northern India. Infection. 2008 Oct;36(5):444-9.
[13] Sharma Y1, Kaur M, Singh S, Pant L, Kudesia M, Jain S. Seroprevalence and trend of dengue cases
admitted to a government hospital, Delhi – 5 Year Study (2006-2010): a look into the age shift. Int J
Prev Med. 2012 Aug;3(8):537–543.
[14] Halstead SB. Pathogenesis of dengue: challenges to molecular biology. Science 1988;239:476–81.
[15] Monath TP. Yellow fever and dengue-the interactions of virus, vector and host in the re-emergence of
epidemic disease. Semin Virol. 1994;5:133–45.
[16] Rigau-Pérez JG, Clark GG, Gubler DJ, Reiter P, Sanders EJ, Vorndam AV. Dengue and dengue
haemorrhagic fever. Lancet. 1998; 352: 971–7.
[17] Beatty M E, Letson G W, Margolis H S. Estimating the global burden of dengue. Am J Trop Med Hyg.
2009;81(1):231.
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[18] Bhatt S, Gething PW, Brady OJ, Messina JP, Farlow AW, Moyes CL, et al. The global distribution and
burden of dengue . Nature. 2013 Apr 25;496(7446):504-7.
[19] Matthew J. Thompson, Susan M. Skillman, Ronald Schneeweiss, L. Gary Hart, Karin Johnson and
the Pacific Islands Continuing Clinical Education Program (PICCEP) Study Team. The University of
Washington Pacific Islands Continuing Clinical Education Program (PICCEP): Guam Conference on
structure and content of continuing clinical education programs in the U.S.-Associated jurisdictions.
Pacific health dialogue. 2011;17(1):119-28.
[20] Jamaiah I, Rohela M, Nissapatorn V, Maizatulhikma MM, Norazlinda R, Syaheerah H, et al. Prevalence
of dengue fever and dengue hemorrhagic fever in hospital Tengku Ampuan Rahimah, Klang, Selangor,
Malaysia. Southeast Asian J Trop Med Public Health. 2005;36(4):196-201.
[21] Muhadir A. Epidemiology of dengue in Indonesia. Dengue vaccine meeting, Brazilia, Brazil 9-11 April,
2013. http://www.denguevaccines.org/sites/default/files/files/Day%201_5_6_1_Indonesia_AMuhadir.
pdf – accessed 13 April 2016.
[22] Quader AJ, Gandham P, Nandeshwar AJ. Screening for dengue infection in clinically suspected cases
in a rural teaching hospital. J Microbiol Biotech Res. 2013;3(2):26-9.
[23] Waterman SH, Novak RJ, Sather GE, Bailey RE, Rios I, Gubler DJ. Dengue transmission in two Puerto
Rican communities in 1982. Am J Trop Med Hyg. 1985;34:625–32.
[24] Hii YL, Rocklöv J, Ng N, Tang CS, Pang FY, Sauerborn R. Climate variability and increase in incidence
and magnitude of dengue incidence in Singapore. Global Health Action 2009 Nov;2.
[25] Sissoko D1, Ezzedine K, Giry C, Moendandzé A, Lernout T, D’Ortenzio E, et al. Seroepidemiology of
Dengue Virus in Mayotte, Indian Ocean, 2006. PLoS One. 2010 Nov 30;5(11):e14141.
[26] May L, Chretien JP, Pavlin JA. Beyond traditional surveillance: applying syndromic surveillance to
developing settings – opportunities and challenges BMC Public Health. 2009,9:242
[27] World Health Organization. Types of Surveillance and their Strengths and Weaknesses for Nine Epidemic
Diseases. Dengue. Years Covered, 1955–1999. Geneva. http://www.who.int/csr/resources/publications/
surveillance/surveillance/en/index5.html - accessed 13 April 2016.
86
Dengue Bulletin – Volume 39, 2016
Identification of key containers of
Aedes breeding – a cornerstone to control
strategies of dengue in Delhi, India
B.N. Nagpala#, Sanjeev Kumar Guptaa, Arshad Shamima, Kumar Vikrama,
Anushritaa, Himmat Singha, Rekha Saxenaa, V.P. Singha, Aruna Srivastavaa,
Babita Bishtc, N.R. Tulib, R.N. Singhc and Neena Valechaa
a
National Institute of Malaria Research (NIMR), New Delhi
Municipal Corporation of Delhi (MCD)
b
c
New Delhi Municipal Corporation (NDMC)
Abstract
The present study is based on five years’ data (December 2007–November 2012) with the objective
to study whether Aedes breeding takes place throughout the year and to identify so-called key
containers for Aedes breeding in Delhi, India. Larvae collected from 250–300 randomly selected
localities of Delhi were brought to the laboratory and habitat-wise rearing was done till emergence,
to identify the key container preferred by Aedes aegypti. During non-transmission season, highest
positivity was observed in overhead tanks (positivity 46.5%; Container Index: 3.21) and curing
tanks (positivity 16.9%; Container Index: 4.96). There was only a threefold rise in container indices
of overhead tanks and curing tanks from non-transmission to transmission season whereas in other
containers the rise was more than fivefold. Independent ‘t’ test carried out on positivity of various
breeding habitats during both seasons showed that overhead tanks, curing tanks and cemented
pits were not significantly different (p>0.05). It was concluded that overhead tank acts as key
container of Aedes breeding in Delhi as it shows a consistent breeding throughout the study period.
The rest of the containers do play intermittent roles in supporting the breeding of Aedes mosquito
and hence need separate attention while reforming control strategies.
Keywords: Dengue, Aedes aegypti, key container, container index.
Introduction
Dengue is the fastest spreading vector-borne viral disease and is now endemic in over 100
countries. At present half of the world’s population is living in areas at risk for dengue.1
In India, the first outbreak of dengue was observed from Vellore in 1956 and first dengue
#
E-mail: [email protected]
Dengue Bulletin – Volume 39, 2016
87
Identification of key containers of Aedes breeding – A cornerstone to control strategies of dengue in Delhi, India
haemorrhagic fever (DHF) outbreak was observed from Kolkata in 1963.2 In 2013, more
than 75 000 dengue cases were recorded from India, with 193 deaths.3 Besides this, dengue
penetrated in states reporting sporadic cases earlier, such as Odisha (7132 cases, six deaths),
Gujarat (6272 cases, 15 deaths), Karnataka (6408 cases, 12 deaths), Kerala (7938 cases, 29
deaths), Assam (4526 cases, two deaths) and Uttar Pradesh (1414 cases, five deaths). Almost
all the states of the country are reporting dengue cases, including Delhi. Delhi witnessed
dengue outbreaks during 1967, 1970, 1982, 1988, 1990, 1992, 1996 and 2003.4–12
Aedes aegypti, the primary vector of dengue in most part of the world, is well adapted
to urbanized areas, especially the surroundings of human dwellings, and breeds often in
man-made containers.13 Aedes aegypti can breed in the lid of a small bottle or in big storage
containers such as overhead tanks. On the basis of the proximity to human dwelling, source
and the use of the water, Aedes breeding can be classified in two broad categories viz.
domestic and peri-domestic. Domestic breeding habitats were defined as human-filled
receptacles (in and around human dwellings), for instance, overhead tanks, coolers and
water storage containers, whereas peri-domestic breeding habitats are discarded receptacles
(far from human dwellings), such as solid waste (dump types, disposable plastic/ thermacol
glasses, broken earthen pots etc.), bird pots, cemented pits etc., normally filled by rain.14
Entomological research has shown that in most areas there are a relatively small number
of containers that consistently serve as the primary producers of Aedes aegypti, termed as
key containers, with other containers playing minor roles in mosquito production,15 which
may vary from place to place.16
Aedes aegypti control programmes could be more cost effective and sustainable by
concentrating efforts to control mosquito breeding in key containers and by rationalizing
manpower and insecticide use in transmission season.17 Aedes aegypti population dynamics
are influenced by social risk factors that vary by season and lagged climate variables that
vary by locality.18
National Institute of Malaria Research (NIMR), under the aegis of Indian Council of
Medical Research (ICMR), has been conducting a longitudinal study in collaboration with
Municipal Corporation of Delhi (MCD) and New Delhi Municipal Corporation (NDMC) on
Aedes breeding survey in Delhi since 2007 with an underlying hypothesis that Aedes breeding
is found throughout the year. The current study also aimed to identify key containers for
breeding of Aedes aegypti in Delhi.
88
Dengue Bulletin – Volume 39, 2016
Identification of key containers of Aedes breeding – A cornerstone to control strategies of dengue in Delhi, India
Materials and methods
Study area
The present study was carried out in Delhi, the national capital of India, that lies in the
latitude 28.38 N and longitude 77.12 E on the bank of river Yamuna. As per 2011 Census,
the population of Delhi is around 16 million spread over an area of around 1483 sq km.
with population density of about 11 000 per sq. km. About 93% of the population resides
in the urban area of state and all areas are likely to be urbanized soon in coming years.
Larval surveys
Aedes breeding survey was carried out by NIMR throughout the year in different localities of
Delhi since 2006. The present study is based on five years’ data collected between December
2007 and November 2012. During the period, about 250–300 randomly selected localities
of Delhi were surveyed by a team of five or six field workers from NIMR in collaboration with
MCD and NDMC, using pipette or dipper depending on container type, as per WHO norms.
Larvae collected from field sites were brought to the laboratory and habitat-wise rearing
was done till emergence, to identify the key container preferred by the dengue vector, that
is, Aedes aegypti. Houses were selected randomly from different income groups and each
potential breeding site in the house was checked thoroughly. Besides houses, government
offices, schools, nurseries, parks, picnic spots, police stations, bus depots, dispensaries,
hospitals, etc. were also surveyed from time to time.
Overhead tanks (plastic and cemented tanks fixed on the terrace of house), water
storage containers, curing tanks (cemented tanks built at construction sites), coolers and
flower pots were identified as five major types of domestic containers, and bird pots, mud
pots, pits (cemented) and solid waste (dump tyres, disposable plastic/thermocol glasses etc.)
were identified as four major types of peri-domestic containers in Delhi. On the basis of
Aedes breeding and number of cases recorded by MCD, June to November months were
identified as transmission season and December to May months were identified as nontransmission season.
On an average four breeding sites were found in each house and 60 houses were surveyed
per day. Working approximately 20 days per month, about 5000 containers were surveyed in
a month. Over five years, a total of 284 248 containers were checked. Container-wise data
was pooled on monthly basis and container index was calculated using following formula:
Container Index (CI) =
Dengue Bulletin – Volume 39, 2016
Containers Positive
Containers Checked
x 100
89
Identification of key containers of Aedes breeding – A cornerstone to control strategies of dengue in Delhi, India
Statistical analysis
The data were entered in Excel 2007 and statistical analysis was done by SPSS software
package (Version 20).
Results
Out of 284 248 breeding habitats surveyed during the period (December 2007 to November
2012), 46% and 54% containers were checked during transmission and non-transmission
season, respectively. A total of 23 593 habitats were found positive with container index of
8.30. During the five years of study period Container Index was observed in the range of
8.4–16.2 (average Container Index: 13.45) during transmission season whereas the same was
in the range of 2–3 (average Container Index: 2.3) during non-transmission season (Table 1).
Seasonal prevalence of habitats
Month-wise container index of domestic containers, that is, overhead tanks, water storage
containers, curing tanks, coolers and flower pots, and peri-domestic containers, that is,
bird pots, mud pots, cemented pits and solid waste, are shown along with their images
in Figure 1 (a-i). Variation in container indices is consistent with the variation observed in
average rainfall (Figure 1 (a-i)) except the container indices of overhead tanks, curing tanks
and cement pits. The variation observed in cemented pits was minor as compared to overhead
tanks and curing tanks (Figure 1 a,b & h). Other containers did not vary significantly during
non-transmission season as apparent by Figure 1 (c-g & i).
Table 1: Container Index during transmission and non-transmission season (2007–2012)
Transmission season
Period
Checked
Non-transmission season
+ve
CI
Period
Checked
+ve
CI
Jun'08–Nov'08
27 752
4414
15.9
Dec'07–May'08
25 882
528
2
Jun'09–Nov'09
29 454
3851
13.1
Dec'08–May'09
24 901
798
3.2
Jun'10–Nov'10
29 580
4790
16.2
Dec'09–May'10
25 071
632
2.5
Jun'11–Nov'11
36 450
4995
13.7
Dec'10–May'11
27 393
582
2.1
Jun'12–Nov'12
29 082
2441
8.39
Dec'11–May'12
28 683
562
2
Total
152 318
20 491
13.5
Total
131 930
3102
2.4
G. Total
Checked
284 248
+ve
23 593
CI
8.3
90
Dengue Bulletin – Volume 39, 2016
Identification of key containers of Aedes breeding – A cornerstone to control strategies of dengue in Delhi, India
5.0
100
0.0
0
200
10.0
100
0.0
0
300
250
200
150
100
50
0
30.0
20.0
10.0
0.0
200
10.0
100
0.0
0
Bird Pots (CI)
Avg. Rainfall
Container Index
20.0
Mud Pots (CI)
Rainfall (mm)
300
(h)
300
20.0
200
10.0
100
0.0
0
Cemented Pits (CI)
Container Index
300
250
200
150
100
50
0
40.0
30.0
20.0
10.0
Avg. Rainfall
Dec
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
0.0
Solid Waste (CI)
Dengue Bulletin – Volume 39, 2016
Avg. Rainfall
30.0
50.0
(i)
Avg. Rainfall
40.0
(f)
30.0
Rainfall (mm)
Dec
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
100
Dec
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
(g)
10.0
Avg. Rainfall
Dec
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Container Index
0
Flower Pots (CI)
200
Rainfall (mm)
20.0
(e)
20.0
50.0
300
0.0
300
Water Storage Containers (CI)
Container Index
30.0
Avg. Rainfall
30.0
(d)
Avg. Rainfall
Dec
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Container Index
Cooler (CI)
Rainfall (mm)
(c)
Curing Tanks (CI)
Rainfall (mm)
200
0
0.0
Rainfall (mm)
10.0
100
5.0
Rainfall (mm)
300
Dec
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
15.0
200
10.0
(b)
Avg. Rainfall
Rainfall (mm)
Overhead Tanks (CI)
300
15.0
Dec
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
0
20.0
Dec
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
0.0
Container Index
100
5.0
Container Index
200
10.0
Rainfall (mm)
15.0
(a)
Container Index
300
20.0
Dec
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Container Index
Figure 1: Seasonal prevalence in (a) overhead tanks (b) curing tanks (c) coolers
(d) water storage containers (e) flower pots (f) mud pots (g) bird pots
(h) cemented pits (i) solid waste
Avg. Rainfall
91
Identification of key containers of Aedes breeding – A cornerstone to control strategies of dengue in Delhi, India
Transmission season
During transmission season a total of 152 318 containers were checked, 77.7% of which were
domestic whereas remaining 22.3% containers were peri-domestic. Difference in domestic
and peri-domestic containers during transmission season was tested by independent t test.
The independent samples t test was associated with a statistically significant difference (p
<0.05) for both the containers, t (8) = 3.12, p = 0.01. Among 20 491 containers found
positive, domestic containers and peri-domestic containers contributed 64.9% and 35.1%
positivity, respectively. Container Index was observed highest in solid waste (29.07%) followed
by mud pots (18.25%) and cemented pits (16.61%). Maximum positivity was observed
in water storage containers (26.2%) followed by overhead tanks (16.1%) among domestic
containers whereas solid waste (18.1%) and cemented pits (6.5%) were two major positive
peri-domestic containers (Table 2).
Non-transmission season
During non-transmission season a total of 131 930 containers were checked, 84.2% of which
were domestic whereas remaining 15.8% containers were peri-domestic. The difference
in domestic and peri-domestic containers during non-transmission season was tested by
Table 2: Number and proportion of habitats checked and positive with Container Index
during transmission season
Type of
container
Domestic
Habitat
n
OHT
92
%
n
%
%
21%
3303
16%
10.33
7837
5%
1000
5%
12.76
Cooler
27 975
18%
2104
10%
7.52
Containers
39 963
26%
5375
26%
13.45
Flower pot
10 684
7%
1515
7%
14.18
Mud pot
7220
5%
1318
6%
18.25
Bird pot
5842
4%
821
4%
14.05
Cemented pits
8042
5%
1336
7%
16.61
12 795
8%
3719
18%
29.07
152 318
100%
20 491
100%
13.45
Solid waste
G. total
Container
Index
Positive
31 960
Curing tanks
Peri-domestic
Checked
Dengue Bulletin – Volume 39, 2016
Identification of key containers of Aedes breeding – A cornerstone to control strategies of dengue in Delhi, India
Table 3: Number and proportion of habitats checked and positive with Container Index
during non-transmission season
Type of
container
Domestic
Peri-domestic
Habitat
Checked
n
Container
Index
Positive
%
n
%
%
Overhead tanks
44 936
34%
1441
47%
3.21
Curing tanks
10 581
8%
525
17%
4.96
Cooler
12 909
10%
204
7%
1.58
Containers
30 945
24%
303
10%
0.98
Flower pot
11 762
9%
16
1%
0.14
Mud pot
4608
4%
111
4%
2.41
Bird pot
5123
4%
136
4%
2.65
Cemented pits
7611
6%
263
9%
3.46
Solid waste
3455
3%
103
3%
2.98
131 930
100%
3102
100%
2.35
G. total
independent t test. The independent samples t test was associated with a statistically significant
difference (p <0.05) for both the containers t (8) = 6.44, p = 0.001. Out of 3102 containers
found positive, domestic and peri-domestic containers contributed 80.2%and 19.8%
positivity, respectively. Among domestic containers, maximum positivity and Container Index
was observed in domestic containers, that is, overhead tanks (positivity 46.5%; Container
Index: 3.21) and curing tanks (positivity 16.9%; Container Index: 4.96) (Table 3). On the
basis of highest positivity during non-transmission season, overhead tanks and curing tanks
were identified as key containers for breeding of Aedes aegypti in Delhi.
Comparison of breeding habitats during non-transmission and
transmission season
A t test was performed to compare individual containers in transmission and non-transmission
season and p values were found significant for all the individual tests (Table 4). Analysis of
Variance (ANOVA) was performed to ascertain any difference among container indices of
various breeding habitats during transmission and non-transmission seasons and it was also
found significant, F (17) = 11.23, p <0.05.
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Identification of key containers of Aedes breeding – A cornerstone to control strategies of dengue in Delhi, India
Among domestic containers, overhead tanks and curing tanks showed consistent breeding
behaviour as there is only a threefold rise in container indices from non-transmission to
transmission season whereas water storage containers, flower pots and coolers showed
seasonal breeding behaviour as there is a more than fivefold rise in Container Index (Table 4,
Figure 2). All peri-domestic containers, that is, mud-pots, bird pots, cemented pits and solid
waste also show seasonal breeding behaviour as an increase is observed in Container Index
of more than fivefold from non-transmission season to transmission season. On the basis of
consistency in breeding behaviour, overhead tanks and curing tanks were re-identified as
key containers.
To test the null hypothesis for difference in positivity of various breeding habitats checked
during transmission and non-transmission seasons, an independent t test was performed. The
independent samples t test was associated with a statistically significant difference (p <0.05)
for coolers, water storage containers, flower pots, bird pots, mud pots and solid waste. The
three containers, namely overhead tanks, curing tanks and cemented pits, were not found
significantly different (p >0.05) for both the seasons (Table 5). As there is no significant
difference in overhead tanks, curing tanks and cemented pits, it could be hence inferred that
the breeding in these habitats does not change during transmission and non-transmission
season and, therefore, can be considered as key containers.
Table 4: Habitat-wise container index during transmission
and non-transmission season (2007–2012)
Type of
container
Domestic
Peri-domestic
94
Breeding
habitat
Container Index
Nontransmission
Transmission
Change
(folds)
P value
(significant
if ≤ .05)
OHT
3.21
10.33
3↑
<.05
Curing tanks
4.96
12.76
3↑
<.05
Cooler
1.58
7.52
5↑
<.05
Containers
0.98
13.45
14↑
<.05
Flower pot
0.14
14.18
104↑
<.05
Mud pot
2.41
18.25
8↑
<.05
Bird pot
2.65
14.05
5↑
<.05
Cemented pits
3.46
16.61
5↑
<.05
Solid waste
2.98
29.07
10↑
<.05
Dengue Bulletin – Volume 39, 2016
Identification of key containers of Aedes breeding – A cornerstone to control strategies of dengue in Delhi, India
Figure 2: Comparison in container index of breeding habitat during transmission and
non-transmission season
Domestic
Solid Waste
Cemented Pits
Bird Pot
Mud pot
Transmission
Flower pot
Cooler
Curing Tanks
OHT
Non Transmission
Containers
35.00
30.00
25.00
20.00
15.00
10.00
5.00
0.00
Peri-Domestic
Table 5: Independent t test for various breeding containers for Aedes aegypti checked
during the study
t-test for equality of means
Habitat
t
Sig.
(2-tailed)
df
95% Confidence Interval
of the difference
Lower
Upper
Overhead tanks
1.887
8
0.096
-82.644
827.444
Curing tanks
1.731
8
0.122
-31.551
221.551
Coolers
4.606
8
0.002
189.73
570.267
Water storage containers
3.756
8
0.006
391.66
1637.14
2.58
8
0.033
31.817
567.783
Bird pots
3.265
8
0.011
40.231
233.769
Mud pots
2.415
8
0.042
10.918
471.882
Cemented pit
2.053
8
0.074
-26.477
455.677
Solid waste
5.623
8
0.000
426.62
1019.78
Flower pots
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Identification of key containers of Aedes breeding – A cornerstone to control strategies of dengue in Delhi, India
Figure 3: No. of months breeding habitats found positive during Transmission and
Non Transmission Season
35
Non-Transmission
No. of Months
30
Transmission
25
20
15
10
Flower Pot
Solid Waste
Bird Pot
Cooler
Mud Pot
Cement Pits
Water Storage
Containers
Curing Tank
0
Overhead Tanks
5
It was also observed that during five years (30 months each in transmission and nontransmission season) overhead tanks were found positive almost every month (29 out of 30
months) whereas curing tanks (20 out of 30 months) and cemented pits (11 out of 30 months)
were not found positive consistently (Figure 3). Non-consistent behaviour of cemented pits
and curing tanks during non-transmission season revealed that overhead tank was the only
key container of Aedes breeding in Delhi.
Discussion
In our study overhead tanks were identified as key container of Aedes in Delhi as breeding
was observed in overhead tanks throughout the period of five years. A study carried out by
Sharma et al., 2005, during the year 2000 in different localities of Delhi identifies overhead
tanks and cement tanks as breeding foci for Aedes aegypti.19 Identification of key containers
was also carried out in different parts of India and the world. Roof gutters were identified
as key container for Aedes aegypti in Australia20 whereas plastic drums, metal drums and
plastic containers were identified key sites for breeding of Aedes aegypti in the Philippines.21
In India, cement tanks were identified as key breeding habitats for Aedes aegypti in desert as
well as semi-arid areas of Rajasthan.22 A study carried out in Delhi by Katyal et al. reported
that cement tanks and non-removable clay jars acted as mother foci during winter months
in 1964.23 Delhi has witnessed rapid unplanned urbanization, resulting in high-density
population areas with inadequate systems of water and solid waste management which
have provided excellent breeding places for Aedes aegypti mosquitoes.24 Population density
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Dengue Bulletin – Volume 39, 2016
Identification of key containers of Aedes breeding – A cornerstone to control strategies of dengue in Delhi, India
and water storage practices have a direct relationship with prevalence of Aedes aegypti.25,26
Further study is needed to know whether control of the breeding of Aedes aegypti in key
habitats during non-transmission season would arrest the breeding in secondary habitats
and dengue transmission.
Conclusion
Breeding of Aedes mosquitoes was observed round the year in overhead tanks, a domestic
breeding site; it can hence be considered as a key container of its breeding in Delhi. Overhead
tanks maintain breeding of Aedes in non-transmission season which amplifies multi-fold in
secondary containers, especially solid wastes, during transmission season. Identification of key
containers will help the authorities to take timely and focused interventions and reformulate
control strategies of Aedes breeding in a sustainable and environment friendly manner.
Acknowledgments
Authors are thankful to Indian Council of Medical Research for the funding of this intramural
study. We are also thankful to MCD and NDMC for providing support in field work. We are
thankful to the entire field staff of NIMR for assistance in field work. Special thanks are due
to Mr. Mritunjay Prasad Singh and Ashoo Sharma for data management. This paper bears
the NIMR publication screening committee approval no. 032/2015.
Declaration
Authors state that this article has not been published and will not be submitted for publication
elsewhere if accepted for publication in the WHO Dengue Bulletin.
References
[1] World Health Organization. Dengue and severe dengue. Geneva: WHO, 2016. http://www.who.int/
mediacentre/factsheets/fs117/en/ - accessed 13 April 2016.
[2] Yadava RL, Narsimham MVVL. Dengue/DHF and its control in India. Dengue News. 1992;17:3–8.
[3] National Vector Borne Disease Control Programme. Dengue cases and deaths in the country since
2009. Delhi, India, NVBDCP - http://nvbdcp.gov.in/den-cd.html - accessed 13 April 2016.
[4] Balaya S, Paul SD, D’Lima LV, Pavri KM. Investigations on an outbreak of dengue in Delhi in 1967.
Indian J Med Res.1969;57:767–774.
[5] Dinesh P, Pattanayak S, Singha P, Arora DD, Mathur PS, Ghosh TK. An outbreak of dengue fever in
Delhi—1970. J Commun Dis. 1972;4:13-18.
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Identification of key containers of Aedes breeding – A cornerstone to control strategies of dengue in Delhi, India
[6] Rao CV, Bagchi SK, Pinto BD, Ilkal MA, Bharadwaj M, Shaikh BH, Dhanda V, Dutta M, Pavri KM.
The 1982 epidemic of dengue fever in Delhi. Indian J Med Res. 1985;82:271-275.
[7] Acharya SK, Buch P, Irshad M, Gandhi BM, Joshi YK, Tandon BN. Outbreak of Dengue fever in
Delhi. Lancet. 1988;24(2):1485–1486.
[8] Srivastava VK, Suri S, Bhasin A, Srivastava L, Bharadwaj M. An epidemic of dengue hemorrhagic fever
and dengue shock syndrome in Delhi-A clinical study. Ann Trop Pediatr. 1990;10:329-334.
[9] Kabra SK, Verma IC, Arora NK, Jain Y, Kalra V. Dengue epidemic in children in Delhi. Bull. WHO.
1992;70:1051-1058.
[10] Sharma RS, Panigrahi N, Kaul SM. Aedes aegypti prevalence in hospitals and schools, the priority sites
for DHF transmission in Delhi. Dengue Bull. 1999;23:109-112.
[11] Sharma RS, Joshi PL, Tiwari KN, Katyal R, Gill KS. Outbreak of dengue in National Capital Territory of
Delhi, India during 2003. Journal of Vector Ecology. 2004;30(2):337-338.
[12] Gupta E, Dar L, Kapoor G, Broor S. The changing epidemiology of dengue in Delhi. India. Virol J.
2006;3:1–5.
[13] Zuhriyah L, Habibie IY, Baskoro AD. The Key Container of Aedes aegypti in Rural and Urban Malang,
East Java, Indonesia. Health and the Environment Journal. 2012;3(3):51-58.
[14] Kamgang B, Ngoagouni C, Manirakiza A, Nakouné E, Paupy C, Kazanji M. Temporal patterns of
abundance of Aedes aegypti and Aedes albopictus (Diptera: Culicidae) and Mitochondrial DNA Analysis
of Ae. albopictus in the Central African Republic. PLoS Negl Trop Dis. 2013;7(12):e2590.
[15] Sinh Vu N. Key container and key premise indices for Ae. aegytpi surveillance and control. In: Linda
S. Lloyd, eds. Best practices for dengue prevention and control in the Americas. Strategic Report.
2013;7:51-56.
[16] Salamat MSS, Cochon KL, Crisostomo GCC, Gonzaga PBS, Quijano NA, Torio JF, Villanueva AA.
Entomological Survey of Artificial Container Breeding Sites of Dengue Vectors in Batasan Hills, Quezon
City. Acta Medica Philippina. 2013;47(3):63-68.
[17] Chadee DD. Key premises, a guide to Aedes aegypti (Diptera: Culicidae) surveillance and control. Bull.
Entomol Res.2004;94(3):201-207.
[18] Stewart IAM, Ryan SJ, Beltrán E, Mejía R, Silva M, Muñoz Á. Dengue Vector Dynamics (Aedes aegypti)
influenced by climate and social factors in Ecuador: implications for targeted control. PLoS one.
2013;8(11):e78263.
[19] Sharma RS, Kaul SM, Sokhay J. Seasonal fluctuations of dengue fever vector, Aedes aegypti (Diptera:
Culicidae) in Delhi, India. Southeast Asian J Trop Med Public Health. 2005;36(1):186-190.
[20] Montgomery BL, Ritchie SA. Roof gutters: a key container for Aedes aegypti and Ochlerotatus
notoscriptus (Diptera: Culicidae) in Australia. Am J Trop Med Hyg. 2002;67(3):244-246.
[21] Edillo FE, Roble ND, Otero II ND. The key breeding sites by pupal survey for dengue mosquito vectors,
Aedes aegypti (Linnaeus) and Aedes albopictus (Skuse), in Guba, Cebu City, Philippines. Southeast Asian
J Trop Med Public Health. 2012;43(6):1365-1374.
[22] Sharma K, Angel B, Singh H, Purohit A, Joshi V. Entomological studies for surveillance and prevention
of dengue in arid and semi-arid districts of Rajasthan, India. J Vector Borne Dis. 2008;45:124–132.
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[23] Katyal R, Singh K, Kumar K. Seasonal variations in Aedes aegypti population in Delhi, India. Dengue
Bulletin. 1996;20:78–81
[24] World Health Organization. Report on global surveillance of epidemic-prone infectious diseases - dengue
and dengue haemorrhagic fever. Geneva: WHO, 2000. http://www.who.int/csr/resources/publications/
dengue/CSR_ISR_2000_1/en/index2.html - accessed 13 April 2016.
[25] Kalra NL, Kaul SM, Rastogi RM. Prevalence of Aedes aegypti and Aedes albopictus – Vectors of Dengue
and Dengue haemorrhagic fever in North, North-East and Central India. Dengue Bulletin. 1987;2:84-92.
[26] Vikram K, Nagpal BN, Pande V, Srivastava A, Saxena R, Singh H, et al. Detection of dengue virus in
individual Aedes aegypti mosquitoes in Delhi, India. J Vector Borne Dis. 2015;52:129–133.
Dengue Bulletin – Volume 39, 2016
99
A comprehensive report of dengue activity
in Kolkata, India – a four-year profile
Tanuja Khatun, Shyamalendu Chatterjee#
ICMR Virus Unit, Kolkata, West Bengal, India
Abstract
Dengue is a perpetual public health problem in Kolkata, India. Every year it strikes either in a
portion or the whole of the city in the form of an outbreak of acute febrile illness. Two clinical forms
of dengue infection have been recognized – dengue fever, a relatively mild, self-limiting febrile
illness, and dengue haemorrhagic fever/dengue shock syndrome (DHF/DSS), a severe infection
with vascular and haemostatic abnormalities that can lead to death – which are not unknown in
this city, especially in the rainy season. In Kolkata, although sporadic cases are reported round
the year, mainly the infection flares during monsoon and persists up to autumn. Thus, the city has
become an endemic zone of dengue. Blood samples from such patients are routinely referred
to the ICMR Virus Unit, Kolkata, for the diagnosis of dengue infection as it is an Apex Referral
Laboratory of National Vector Borne Disease Control Programme, Delhi, for the detection of
dengue in eastern India. Here we report the status of dengue infection since 2011 to 2014 by
performing serological detection of dengue specific IgM antibody by ELISA method and molecular
diagnosis by Reverse Transcriptase Polymerase Chain Reaction (RT-PCR) test followed by nested
PCR for the determination of serotype. During this period a total of 2686 samples were received
from different medical colleges and hospitals of this city. Only 980 (36.48%) samples were positive
to IgM antibody by ELISA method. A total of 573 dengue IgM negative acute samples having
≤4 days of illness were selected for isolation of virus through tissue culture system using C6/36
cell line. Subsequently these 573 samples, irrespective of the appearance of Cyto Pathic Effect
(CPE) in tissue culture, were subjected to RNA extraction, RT-PCR followed by nested PCR for
molecular detection of dengue serotype. Only 104 (18.15%) samples were RT-PCR positive of
which 62 samples had monotypic infection with Dengue-1(D1), Dengue-2 (D2), Dengue-3 (D3);
38 samples had dual infection with any two of the four serotypes; three samples had infection
with D1, D3 and Dengue-4 (D4); and only one sample had the infection with D1, D2 and D3.
During the entire study period significant incidences of DHF were observed in the patients infected
with multiple serotype. Females were much more affected than the males. The highly affected
age group was 0–10 years, followed by 11–20 and 21–30 years. Although this four-year study
establishes the concurrent circulation of all the dengue serotypes in Kolkata, with majority of D3,
the epidemiology of dengue still remains unpredictable.
Keywords: Dengue, serotype, Kolkata.
#
E-mail: [email protected]
100
Dengue Bulletin – Volume 39, 2016
A comprehensive report of dengue activity in Kolkata, India – a four-year profile
Introduction
The Indian scenario with mosquito-borne diseases such as dengue is interesting and intriguing.
Dengue viruses are members of the genus Flavivirus of the family Flaviviridae, which consists
of four antigenetically distinct serotypes named D1, D2, D3 and D4 that do not offer cross
protection.1 Dengue viral infection can either cause dengue fever (DF), a relatively mild,
self-limiting febrile illness that is known to be endemic in India, or dengue haemorrhagic
fever (DHF)/dengue shock syndrome (DSS), which can be life threatening and responsible for
a high mortality rate, especially in children.2 The epidemiology of DF and DHF is changing
fast3 and has increased dramatically in recent decades.4,5 In India, dengue was first isolated in
1946 and since then many epidemics have been reported from many parts of the country.6–9
DHF was first reported from Kolkata in 1963 and again in 1964. Subsequently, DHF cases
have been reported from many parts of the country, including Delhi.10–19 Timely and correct
diagnosis is very crucial for patient management as no definite vaccine has been developed
against all dengue serotypes. Since 2000, Indian Council of Medical Research (ICMR) Virus
Unit, Kolkata, is engaged for the systematic investigation for the detection of dengue infection
in Kolkata and its suburbs;20 prior to that, no such systematic record is available. This paper
deals with a comprehensive report from ICMR Virus Unit on dengue cases from 2011–2014
including the currently circulating serotype, and establishes dengue endemicity in this city.
Materials and method
Geographic and meteorological data
Kolkata (22082’N, 88080’E) is the capital of West Bengal and the seventh-largest metropolitan
city in area and population in the world. Approximately 7.5% of the total population of
India lives in this state. The city is served by an international airport and a seaport. It also
has two big and busy railway stations that serve as the gateways of the city. The railroads
cover almost all the districts, some of which situated at the border of Bangladesh. Frequent
infiltration of citizens from both the countries takes place crossing the border, which may
facilitate the emergence of dengue infection in the state along with Kolkata. The main
seasons are summer, monsoon and winter. Summer begins in March with temperatures of
38–45°C, followed by monsoon which lasts up to September. A high humid temperature
prevails in these two seasons, which is favourable for viral growth. The breteau index of the
vector mosquito Aedes agypti is moderately high in Kolkata, which serves as the principal/
potential vector for dengue.
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A comprehensive report of dengue activity in Kolkata, India – a four-year profile
Patient and clinical samples
The ICMR Virus Unit Kolkata functions as an Apex Referral Laboratory for the detection of
dengue infection in the eastern part of India. For this reason, blood samples from clinically
suspected dengue cases along with a short history of illness and duly signed consent form of
patients are routinely referred to the ICMR Virus Unit from outpatient departments (OPD)
and indoor of different medical colleges as well as different hospitals and private practitioners
for the detection of dengue infection, if any. The clinically suggestive features that are initially
considered for the diagnosis of dengue infection are: high fever, usually sharp and sudden
onset with or without chill, flushing of the face, suffused eyes/retro-orbital pain, nausea/
vomiting, malaise/joint pain, generalised skin rash, prostration headache and enlarged
lymph nodes. In this study, apart from fever, any two of these criteria were considered. The
samples after excluding the possibilities of prokaryotic and bacterial infection by investigation
at respective hospitals were referred to ICMR Virus Unit. This study was duly approved by
the institutional ethical committee.
Sample collection
Approximately 5ml blood samples of clinically suspected cases were collected by venous
puncture by the health workers and medical technicians. During these four years of study
period, a total of 2686 samples were thus received along with a short history of illness and
duly signed consent from the patient/ patient’s guardian maintaining the cold chain for the
detection of dengue infection, if any. The sera/serum were separated by centrifugation at
1500 rpm for 10 minutes at 4°C and kept at -80°C in aliquots until tested.
Methods employed for the diagnosis of dengue virus infection were serological method
by detecting dengue specific IgM antibody by enzyme linked immunosorbent assay (ELISA),
virus isolation through tissue culture technique using C6/36 cell line and molecular methods
by RNA extraction followed by RT-PCR and Nested PCR which is a very sensitive method.
Serology
All the 2886 samples were tested for the detection of dengue IgM antibody by dengue
specific IgM capture ELISA (Mac ELISA) method, using a kit (prepared by National Institute
of Virology, Pune, India). The prescribed protocol OD measured at 450nm using an ELISA
reader (thermo scientific multi scan EX) was followed.
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A comprehensive report of dengue activity in Kolkata, India – a four-year profile
Virus isolation
For this purpose out of 2686 samples only 573 dengue IgM negative acute serum samples
having ≤ 4 days of illness were screened. Virus isolation was carried out in the C6/36 cell
line to observe CPE following the method described elsewhere.20 Uninfected cell line was
used as negative control and cell lines infected with dengue virus 1 to 4 (obtained from the
National Institute of Virology, Pune, India) were included as positive controls in each run.
RNA extraction
Attempts were made to isolate the viral RNA from the tissue culture fluid which produced
CPE in tissue culture, negative control, and four positive controls and directly from the rest
of the screened samples using a Qiagen viral isolation kit (Qiagen, GmbH, Hilden, Germany)
with a slight modification of the manufacture’s protocol.
RT-PCR/Complementary DNA synthesis
Reverse transcription and amplification were conducted in a single reaction tube by the
procedure describe by Lanciotti et al. using a highly conserved primer pair, D1 (forward)
and D2 (reverse).20,21
Nested PCR
The nested PCR assay employed in this study could distinguish the four dengue serotypes
by the size of the products as described by Lanciotti et al.20,21 This includes a step of second
round PCR/nested PCR using the primer D1 and four serotype specific primers, TS1, TS2,
TS3 and TS4.20,21
Agarose Gel Electrophoresis:
RT-PCR and Nested PCR products were analysed by running 1.5% agarose gel stained with
ethidium bromide and examined under ultraviolet light using a digital gel documentation
system. The expected size of the external RT-PCR products is 511bp. The expected size
of nested PCR product is 482bp for D1, 119bp for D2, 290bp for D3 and 392bp for D4.
Result
During the four years of study period, out of 2686 total samples, highest number of cases
were referred in the year 2012 followed by 2014, 2011 and 2013. A total of 2686 blood/
serum samples were tested for dengue virus specific IgM antibody, of which 980 (36.48%)
Dengue Bulletin – Volume 39, 2016
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A comprehensive report of dengue activity in Kolkata, India – a four-year profile
were positive. A total of 573 dengue IgM negative acute samples having ≤4 days of illness
were screened for RT-PCR test, of which 104 (18.15%) were positive by producing prominent
band at 511bp in 1.5% agarose gel electrophoresis (Table 1).
Table 1: Year-wise distribution of dengue positive cases by ELISA and RT-PCR methods.
Elisa test
Year
Number
tested
Number
positive
RT PCR test
Percentage
positivity
Number
tested
Number
positive
Percentage
positivity
2011
350
13
3.71
60
1
1.66
2012
1278
488
38.18
171
4
2.33
2013
160
43
26.87
149
51
34.22
2014
898
436
48.55
193
48
24.87
Total
2686
980
36.48
573
104
18.15
Amongst 2686 samples, 1649 sera were from male and 1037 sera were from female
patients, of which 411 (24.9%) male and 569 (54.9%) female were positive to dengue IgM
antibody. Similarly, out of 573 screened samples, 104 were positive by RT-PCR of which 39
were male (6.81%) and 65 were female (11.34%). See Figure 1 (a) and (b).
All the 573 screened samples were subjected to tissue culture for the isolation of
virus. Up till now only nine samples produced prominent CPE after fourth passage, which
were identified by RTPCR/Nested PCR method as DEN3-2, DEN2-3, DEN1+DEN2-2 and
DEN1+DEN3-2. Others are still under passage.
Figure 1(a) & (b): Sex-wise distribution of dengue positive cases by
ELISA and RT-PCR methods.
300
Figure 1(a) : ELISA
Figure 1(b): RT-PCR
250
40
200
Female
150
Male
100
Female
Male
20
10
50
0
0
2011 2012 2013 2014
104
30
2011 2012 2013 2014
Dengue Bulletin – Volume 39, 2016
A comprehensive report of dengue activity in Kolkata, India – a four-year profile
Highest number of positivity was observed in the age group of 0–10 years (48.09%),
followed by the age group of 11–20 (43.15%), 21–30 (39.97%), 31–40 (38.38%), 41–50
(35.48%) and 51+ (24.01%). The age wise dengue positive cases are presented in Table 2.
For the detection of the serotype 104 RT-PCR positive samples were further subjected
to nested PCR. The nested PCR revealed that 62 samples had monotypic infection with D1,
D2, D3; 38 samples had dual infection with any two of the four serotypes; three samples
had infection with D1, D3 and D4; and only one sample had the infection with D1, D2
and D3. Thus all the four serotypes are circulating in the city of Kolkata. See Table 3 and
Figures 2 and 3.
Table 2: Age- and year-wise distribution of dengue positive cases by
ELISA and RT-PCR method
Year
0–10
11–20
21–30
31–40
41–50
51+
2011
01
02
05
04
00
2
2012
122
92
127
73
47
31
2013
18
26
27
12
06
05
2014
36
107
170
96
46
29
Total
177
227
329
185
99
67
Table 3 & Figure 2: Serotype distribution shows monotypic and
multiple infection during 2011–2014
Table 3
Serotype
Number detected
Figure 2: Serotype distribution
3%
D1
19
D2
07
D3
36
D4
00
D1+D2
10
D1+D2
D1+D3
21
D1+D3
D1+D4
07
D1+D2+D3
01
D1+D3+D4
03
Dengue Bulletin – Volume 39, 2016
1%
7%
D1
18%
D2
D3
20%
7%
D4
D1+D4
10%
34%
D1+D2+D3
105
A comprehensive report of dengue activity in Kolkata, India – a four-year profile
Figure 3: Dengue specific RT-PCR followed by Nested PCR products were analysed by
running 1.5% agarose gel electrophoresis stained with ethidium bromide.
Lane L-100bp plus DNA ladder, Lane1-Dengue positive control, Lane 2-19: dengue
positive samples. The expected size of nested PCR product is 482bp for D1,
119bp for D2, 290bp for D3 and 392bp for D4
Discussion
Over the years, dengue fever has become an important arboviral infection in different
geographical regions of the world that support the growth of mosquitoes. Its range exceeds
over 100 tropical and subtropical countries with more than 2.5 billion people at the risk
of infection.22 In India, D1 and D4 was first was reported in 196423,24 and D3 in 1968.25
DHF was first reported from Kolkata.26,27 Till date several reports of DF and DHF have been
reported from different states in India.28–34 The city of Kolkata is now a known dengue
endemic zone; frequent outbreaks of DF and DHF have been occurring since the last two
centuries. In Kolkata, DF was first reported in 1824 and after that several epidemics of DF
were recorded in 1836, 1906 and 1911.35 In this present four-year study, the detection of
IgM antibody to dengue virus by ELISA test in 980 samples out of 2686 cases and molecular
detection of dengue specific RNA in 104 samples out of 573 cases, proves the continuous
circulation of dengue virus in Kolkata. According to the sex wise distribution of the suspected
cases (Figure 1 (a) & (b)) there was a significant higher incidence of dengue IgM sero positivity
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A comprehensive report of dengue activity in Kolkata, India – a four-year profile
in females and not in males. This may be explained by the fact that the female individual
usually resides at home at the day time and gets exposed to the mosquitoes (Aedes aegypti)
as it is domestic and peri-domestic in nature.
A significant higher incidence of dengue IgM sero positivity was observed in the age
group of 0–10 years, followed by 11–20 years (Table 2), which is similar to the observation
made by earlier works at different times and from different parts of India. Out of 573 acute
samples, only nine produced prominent CPE. RT-PCR test with 573 samples yielded only
104 (18.15%) prominent band, at par with the control. Out of 104 samples only 62 (59.6%)
had mono typic infection with different dengue serotype and 38 (36.5%) had dual infection,
while three samples had infection with D-1, D-3 and D-4 serotype. Only one sample had
infection with D-1, D-2 and D-3. Patients with multiple serotype infection had the history
of either biphasic or tri-phasic illness with fever and some of them had haemorrhage
manifestation, particularly in the younger and young adult age group. In Kolkata, detection
of multiple serotype in same patients has already been reported elsewhere.20,36 This may be
due to the lack of any protective antibody in them.
In this study a total of [2686-(980+104)] = 1602 samples with a history of five to seven
days’ febrile illness were truly dengue negative, possibly due to the unprotected transportation
that might have damaged the IgM antibody/viral titre or due to the presence of other different
etiological agents responsible for dengue-like illness. The present study establishes the coconcurrency of all the four dengue serotypes in the city of Kolkata. Such types of study
involving year-round and decade-wide observation in Kolkata have established the same
observation elsewhere.20 The highest incidence of dengue cases in the young and young adult
population is possibly due to the lack of any immunity and protecting antibody. Although
all the serotypes are in circulation in the city of Kolkata, D-3 proved to be the dominating
serotype. The co-circulation of all the serotypes is a definite indication of impending outbreaks
of DHF at any time in Kolkata, posing a major public health problem for the city.
Conclusion
This scenario on the dengue status over the four-year period reported from Kolkata may
be no different from other parts of India, as the climatic and demographic features are the
same and so is the risk. While concluding, the authors desire to convey that the proposed
study has two fold interests. First, it is informative, because this work being in its infancy
needs to be introduced to the profession and secondly, here is an invitation to those who
feel inspired to help in this mission.
Dengue Bulletin – Volume 39, 2016
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A comprehensive report of dengue activity in Kolkata, India – a four-year profile
Author’s contribution
TK and SC participated in the conception and design of the study.TK carried out the clinical
assessment, immune assays and molecular testing; all authors carried out analysis and
interpretation of the data and drafted the manuscript. All authors read and approved the
final manuscript. SC is guarantor of the paper.
Acknowledgement
The authors convey their sincere thanks to the staff members of ICMR virus unit for their
help. They also gratefully acknowledge the help received from National Institute of Virology
for providing the kit for the detection of IgM antibody and the virus strains of all the four
serotype of dengue viruses. The co-operation and help received from the doctors of all the
medical colleges and hospitals are thankfully acknowledged for sending the samples from
suspected cases. The authors expressed their gratitude to the Officer-In-Charge, ICMR Virus
Unit, for allowing them to carry out the work in this department.
Financial assistance
We received all financial help from the National Vector Borne Disease Control Programme,
Delhi; Indian Council of Medical Research New Delhi; and Department of Bio Technology,
New Delhi to carry out the work at ICMR Virus Unit Kolkata.
Conflict of interest
The first author is a senior research fellow and the corresponding author is a Scientist D at
ICMR Virus Unit. The authors have no financial and competing interests that are affected
by the materials in the manuscript.
Reference
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[4] World Health Organization. Dengue hemorrhagic fever: diagnosis, treatment, prevention and control.
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[5]
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resources/publications/dengue/CSR_ISR_2000_1/en/ - accessed 15 April 2016.
[6] Balaya S, Paul SD, D’Lima LV, Pavri KM. Investigation of an outbreak of dengue in Delhi in 1967. Indian
J Med Res. 1969 Apr;57(4):767-74.
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1965 epidemic of febrile illness in Nagpur city, Maharashtra State, India. Bull World Health Organ.
1972;46(2):173-9.
[8]
Padbidri VS, Dandawate CN, Goverdhan MK, Bhat UK, Rodrigues FM, D’Lima LV, et al. An investigation
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Dec;61(12):1737-43.
[9]
Karamchandani PV. Study of 100 cases of dengue fever in Madras penitentiary. Indian Med Gazette.
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[10] Ghosh SN, Pavri KM, Singh KR, Sheikh BH, D’lima LV, Mahadev PV, et al. Investigations on the outbreak
of dengue fever in Ajmer City, Rajasthan State in 1969. Part I. Epidemiological, clinical and virological
study of the epidemic. Indian J Med Res. 1974 Apr;62(4):511-22.
[11] Chouhan GS1, Rodrigues FM, Shaikh BH, Ilkal MA, Khangaro SS, Mathur KN, et al. Clinical and
virological study of dengue fever outbreak in Jalore city, Rajasthan 1985. Indian J Med Res. 1990
Nov;91:414-8.
[12] Seth P, Broor S, Dar L, Sengupta S, Chakraborty M. Dengue outbreak in Delhi laboratory diagnosis. In:
Sarma PL, Sood OP, eds. Dengue outbreaks in Delhi. Gurgaon: Ranbaxi Science Foundation, 1996.
pp. 28–30.
[13] S. Broor, L. Dar, S. Sengupta, M. Chakaraborty, JP. Wali, A. Biswas, SK. Kabra, Y. Jain, P. Seth: Recent
dengue epidemic in Delhi, India. Factors in the emergence of arbovirus disease. JE. Saluzzo, B. Dodet,
Eds. 1997. Page-123-128. Elsevier, Amsterdam, The Netherlands.
[14] Broor S, Dar L, Sengupta S, Xess I, Seth P. The first major outbreak of dengue hemorrhagic fever in
Delhi, India. Emerging Infectious Diseases. 1999;5(4):589–90.
[15] Myers RM, Varkey MJ, Reuben R, Jesudass ES. Dengue outbreak in Vellore, southern India, in 1968,
with isolation of four dengue types from man and mosquitoes. Indian Journal of Medical Research.
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[16] Banik GB1, Pal TK, Mandal A, Chakraborty MS, Chakravarti SK. Dengue haemorrhagic fever In Calcutta.
Indian Pediatr. 1994 Jun;31(6):685-7.
[17] Cherian T, Ponnuraj E, Kuruvilla T, Kirubakaran C, John TJ, Raghupathy P. An epidemic of dengue
haemorrhagic fever & dengue shock syndrome in and around Vellore. Indian J Med Res. 1994
Aug;100:51-6.
[18] Kaur H, Prabhakar H, Mathew P, Marshalla R, Arya M. Dengue haemorrhagic fever outbreak in OctoberNovember 1996 in Ludhiana, Punjab, India. Indian J Med Res. 1997 Jul;106:1-3.
[19] Kurukumbi M, Wali JP, Broor S, Aggarwal P, Seth P, Handa R, et al. Seroepidemiology and active
surveillance of dengue fever/dengue haemorrhagic fever in Delhi. Indian J Med Sci. 2001 Mar;55(3):14956.
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[20] Chatterjee S, Khatun T, Sarkar A, Taraphdar D. An overview of dengue infections during 2000–2010
in Kolkata, India.2013. Dengue Bulletin WHO. 2013;37:77-86.
[21] Lanciotti RS, Calisher CH, Gubler DJ, Chang GJ, Vorndam AV. Rapid detection and typing of dengue
viruses from clinical samples by using reverse transcriptase polymerase chain reaction. Journal of Clinical
Microbiology. 1992;30:545–51.
[22] Dash PK, Parida MM, Saxena P, Kumar M, Rai A, Pasha ST, Jana AM. Emergence and continued
circulation of Dengue-2 (genotype IV) virus strains in northern India. J Med Virol. 2004;74:314-22.
[23] Carey DE, Myers RM, Reuben R. Dengue types 1 and 4 viruses in wild- caught mosquitoes in south
India. Science. 1964;143:131-2.
[24] Myers RM, Carey DE, Rodrigues FM, Klontz CE. The isolation of type 4 virus from human sera in south
India. Indian J Med. Res. 1964;52:559-65.
[25] Myers RM, Varkey MJ, Reuben R, Jesudass ES. Dengue outbreak in Vellore, southern India, in 1968,
with isolation of four dengue types from man and mosquitoes. Indian J Med Res. 1970 Jan;58(1):24-30.
[26] Aikat BK, Konar NR, Banerjee G. Hemorrhagic fever in the Calcutta area. Indian J Med Res. 1964
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[27] Sarkar JK, Chakraborty SK, Sarkar RK. Sporadic cases of hemorrhagic and/ or shock during dengue
epidemics. Trans Royal Soc Trop Med Hyg. 1972;66:875-877.
[28] Kaur H, Prabhakar H, Mathew P, Marshalla R, Arya M. Dengue Haemorrhagic fever outbreak in OctoberNovember 1996 in Ludhiana, Punjab, India. Indian J Med Res. 1997 Jul;106:1-3.
[29] Agarwal R, Kapoor S, Nagar R, Misra A, Tandon R, Mathur A, et al. A clinical study of the patients with
dengue Haemorrhagic fever during the epidemic of 1996 at Lucknow, India. Southeast Asian J Trop
Med Public Health. 1999 Dec;30(4):735-40.
[30] Kabilan L, Balasubramanian S, Keshava SM, Thenmozhi V, Sekar G, Tewari SC, et al. Dengue disease
spectrum among infants in the 2001 dengue epidemic in Chennai, Tamil Nadu, India. J Clin Microbiol.
2003 Aug;41(8):3919-21.
[31] Padbidri VS, Adhikari P, Thakare JP, Ilkal MA, Joshi GD, Pereira P, et al. The 1993 epidemic of
dengue fever in Mangalore, Karnataka state, India. Southeast Asian J Trop Med Public Health. 1995
Dec;26(4):699-704.
[32] Barua HC, Mahanta J. Serological evidence of DEN-2 activity in Assam and Nagaland. J Comm
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[33] Cherian T, Ponnuraj E, Kuruvilla T, Kirubakaran C, John TJ, Raghupathy P, et al. An epidemic of
dengue haemorrhagic fever & dengue shock syndrome in and around Vellore. Indian J Med Res. 1994
Aug;100:51-6.
[34] Kurukumbi M, Wali JP, Broor S, Aggarwal P, Seth P, Handa R, et al. Sero epidemiological and active
surveillance of dengue fever/dengue haemorrhagic fever in Delhi. Indian J Med Sci. 2001;55:149-156.
[35] Hati AK. Studies on dengue and dengue haemorrhagic fever (DHF) in West Bengal State, India. Journal
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[36] Sarkar A, Taraphdar D, Chatterjee S. Molecular typing of dengue virus circulating in Kolkata, India in
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Impact of dengue vaccination:
a public health perspective
Tikki Panga, Daniel Goh Yam Thiamb, Maria Rosario Capedingc,
Sri Rezeki Hadinegorod, Sutee Yoksane, Terapong Tantawichienf,
Zulkifli Ismailg, Usa Thisyakornh and Tippi K. Maki
a
National University of Singapore
National University Hospital, Singapore
b
Research Institute for Tropical Medicine, The Philippines
c
University of Indonesia, Indonesia
d
Mahidol University, Thailand
e
g
KPJ Selangor Specialist Hospital, Malaysia
f,h
Chulalongkorn University, Thailand
Sanofi Pasteur, Singapore
i
Abstract
From a public health perspective, dengue control is an ongoing challenge and is now the most
important mosquito-borne viral disease globally. The incidence of dengue has increased 30-fold
in the past 50 years with nearly half of the world’s population at risk. The annual economic cost
of dengue in Asia is estimated at US$ 2 billion (exclusive of costs for preventive and vector control
efforts). Prevention, the key strategy for dengue management, remains a challenge due to lack
of awareness and sustainable vector interventions. After decades of research for vaccine against
dengue, one candidate – a chimeric tetravalent dengue vaccine – has completed all three phases
of clinical trials and significantly reduced (by 80-90%) the incidence of severe dengue disease and
number of hospitalizations. Other promising candidate vaccines are likely to be available in the
near future. Much preparatory advocacy work is needed for their introduction in order to reach
high coverage rates, equitable access and sustainable funding for a new vaccination programme.
Sophisticated tools including mathematical modelling studies will also help determine the cost
effectiveness and impact on dengue disease incidence in each epidemiological setting. The key
drivers of success for any public health action are knowledge, social movement and political
commitment. The Asian Dengue Vaccination Advocacy (ADVA) group is working to facilitate policy
and implementation dialogues among dengue experts and public health leaders to support dengue
vaccine introduction in Asian countries.
Keywords: Immunization programmes; dengue; vaccine; immunization; public health programme; health
policy; dengue in Asia; ADVA.
#
E-mail: [email protected]
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Impact of dengue vaccination: A public health perspective
Introduction
The incidence of dengue, caused by viruses spread by the Aedes mosquito vector, has
increased 30-fold in the past 50 years. An estimated 390 million cases occur every year in
more than 100 countries, mostly in the developing world, and 40% of the world’s population
is at risk.1 Each year, an estimated half a million people contract severe dengue, often
accompanied by bleeding and shock, and require hospitalization. The annual economic cost
of dengue illness in Asia is estimated at US$ 2 billion, not including the costs of preventive
and vector control efforts.2,3 Unfortunately, the situation is likely to remain grim in the coming
years. Increased urbanization, travel and migration, the pressures of globalization, and global
warming are likely to maintain dengue transmission at high levels and continue to result in
major outbreaks in affected countries.
Control of dengue is a complex challenge
From a public health perspective, dengue control remains both a challenge and an enigma.
For a start, it is widely accepted that the true burden of disease is significantly underestimated
by 3- to 25-fold.4 There is a suggestion that in India the burden is underestimated 300-fold.3
In the absence of anti-viral treatment for severe dengue disease, the mainstays of dengue
control have been to reduce the mosquito vectors that transmit the dengue virus, and a high
level of public awareness and community involvement in the fight against dengue. While
vector control remains a key strategy, it has not always been effective. Singapore, for example,
spent about US$ 0.5 billion over the past decade on control programmes5 and has successfully
reduced the Aedes premises index to very low levels, yet still experiences major outbreaks of
dengue. To add to the challenges in controlling dengue, and after decades of research for an
effective vaccine to prevent dengue, there is currently one vaccine candidate so far, which has
completed all three phases of clinical trials. In spite of these challenges, what is clear is that
we need to fight dengue on many fronts through an integrated and inter-sectoral approach,
which includes good clinical case management, integrated surveillance (both entomological
and disease monitoring), with effective field-laboratory-clinic coordination, sustained vector
control and community participation, engagement and ownership.
Strategies to control dengue
Countries affected by dengue around the world are guided by a strategy developed by the
World Health Organization (WHO), the WHO Global Strategy for Dengue Prevention &
Control (2012-2020).1 The strategy is composed of five technical pillars: timely, accurate
diagnosis and appropriate case management; integrated surveillance and outbreak
preparedness; sustainable vector control; future vaccine implementation; and basic,
operational and implementation research. It is hoped that such a strategy will help to achieve
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three key objectives: reducing dengue mortality by ≥ 50% by 2020, reducing dengue
morbidity by ≥ 25% by 2020 and obtaining a true estimate of disease burden by 2015.
Arguably, and with regard to achieving the first two objectives, the availability of an effective
vaccine to prevent dengue would be very valuable.
Promising candidate vaccines on the horizon
Historically, the search for an effective dengue vaccine has been ongoing for more than
80 years, since the earliest attempt by Blanc and Caminopetros in 1929. More recently,
vaccine research by Professors Natth Bhamapravati and Sutee Yoksan at Mahidol University
in Thailand, catalysed research through their commitment and energy to develop a vaccine.6
Several promising candidate vaccines are now under investigation. Among them are live
attenuated vaccines, chimeric, and inactivated viruses, DNA and subunit vaccines.7 The
chimeric tetravalent dengue vaccine manufactured by Sanofi-Pasteur, which has a three-dose
regimen, each dose given six months apart, has completed all phases of clinical trials and is
now licensed or under review for licensure in several endemic countries. This vaccine has
undergone extensive testing in 30 000 participants in 10 endemic countries in Asia8 and Latin
America9 with good efficacy and safety data. Importantly, the vaccine significantly reduced
(by 80-90%) the incidence of severe dengue disease and the number of hospitalizations.
The cost-saving impact of this effect for the population and the health care delivery system is
likely to be considerable. Sophisticated mathematical modelling studies have also indicated
that the said vaccine will have a considerable impact on dengue disease incidence as well
as being cost-effective. The vaccine has reached licensure or is under the review process by
several national regulatory authorities.
Underscoring the importance of the problem, at least three to four other vaccine
manufacturers also have dengue vaccines, which are being evaluated in various phases of
testing, including Takeda GlaxoSmithKline/Fiocruz/Walter Reed , NIH/Butantan and Merck.10
These vaccines may become available in the coming years.
While promising candidate vaccines are likely to be available in the near future, much
preparatory advocacy work is needed to prepare for their introduction in order to reach
high coverage rates, equitable access and sustainable funding for the new vaccination
programme.11 As an example, the Asian Dengue Vaccination Advocacy (ADVA) group is a
regional initiative established in 2011 consisting of independent scientific and educational
experts, which aims to disseminate information and make practical recommendations about
how to prepare for dengue vaccine introduction in ASEAN countries.12 A new global alliance
called Partnership for Dengue Control, established in 2013, will facilitate policymaking
dialogue among dengue experts and public health leaders to support synergies and integration
of innovative tools against dengue, ensuring the most effective strategies will be used.13
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Impact of dengue vaccination: A public health perspective
The policy context – towards implementation of a
dengue vaccine
If a vaccine to prevent dengue seems attractive as an intervention with potentially good
public health impact, what information and knowledge would be needed before a policy
is formulated and implemented?
In general terms, when a policy maker is faced with making a policy decision he/she is
usually interested in getting answers to three questions: Can it work? Will it work? Is it worth it?’
To answer the first question, there is strong evidence from the clinical trials that the vaccine
can work, particularly in reducing the severity of disease and in those who were previously
exposed. The answer to the second question is a little problematic as the vaccine in question
is a brand new intervention. Mathematical modelling studies, an important component of the
Dengue Vaccine Initiative agenda,14 are helping to assess the projected impact from dengue
vaccine immunization against infection, disease and transmission in different epidemiological
settings. The modelling simulations also indicated that the effectiveness of the vaccine is
significantly increased if initial routine vaccination is supplemented with ‘catch up’ campaigns
with additional age groups.15 Economic analysis including mathematical modelling methods,
will also help answer the third question, which relates to cost effectiveness. The economic
burden of dengue is substantial. Under certain assumptions, including a certain threshold
for the cost of completing the regimen, vaccination is expected to be cost effective.16
In addition to the above, however, there are important additional considerations to be
taken into account before a policy is developed and implemented: (1) there is a clear need
for robust diagnostic tools to help in good case identification and management; (2) integrated
surveillance and accurate burden estimates are crucial; (3) impact estimates by mathematical
modelling and rigorous evaluation of an integrated vaccination programme should be carried
out; (4) the vaccine should achieve adequate coverage, which includes roll out and targeted
catch-up campaigns; (5) attention should be given to public acceptance and the potential of
using the vaccine during epidemics; (6) integration with existing vector control programmes
is crucial; (7) successful implementation is dependent on robust health systems within the
country with the flexibility and capacity to integrate new technologies and/or adapt existing
ones; (8) equitable, affordable and sustainable access to the vaccine is an important goal; and
(9) policies must be supported by adequate and sustained programme financing, particularly
for low-income countries.
With regard to programmatic considerations for the vaccine itself, there are additional
technical features, which could also influence successful implementation. This includes the
desirability of having a heat-stable vaccine with simple routes of administration, fewer doses
and flexible dosing schedules.
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What is really needed to make it happen?
From a public health perspective, however, the successful implementation of a dengue
vaccine programme is also dependent on a set of higher-level factors, which goes beyond the
technical and economic considerations. Articulated by Professor Prawase Wasi of Thailand
as the concept of “the triangle that moves the mountain”17, it proposes that the key drivers
of success, the three corners of the triangle, are knowledge, social movement and political
commitment.
Knowledge plays a particularly important role, especially knowledge that informs policymaking. In the words of Julio Frenk, “There is a pathway from good science to publication to
evidence, and to programmes that work. In this way research becomes an inherent part of
problem-solving and policy implementation.” But without social mobilization and movement
and political commitment, knowledge alone is unlikely to be sufficient.
Conclusion
A safe and effective dengue vaccine would be a major public health tool for dengue prevention
and control, to be integrated with existing surveillance, vector control methods and other
innovative tools under development. Implementation is a collective responsibility requiring
political will and commitment, trust, community ownership, sound research, and sustained
and dedicated resources. All stakeholders must play a stronger advocacy role to ensure
that evidence-based knowledge and new public health tools are translated into policy and
practice, and that programmes are monitored and evaluated for impact. Importantly, we
must plan early and act soon to accelerate introduction of dengue vaccine(s) in countries
with the highest disease burdens.15 The need to seize the moment is not simply a public
health imperative but also a moral and ethical imperative.
Disclaimer: This article has not been published, and, if accepted for publication in the
Bulletin, will not be submitted for publication elsewhere without the agreement of WHO,
and the right of republication in any form is reserved by the WHO Regional Offices for
South-East Asia (SEARO) and the Western Pacific (WPRO).
Corresponding Author:
Prof Tikki Pang (Pangestu)
Visiting Professor
Lee Kuan Yew School of Public Policy,
National University of Singapore,
469C Bukit Timah Road,
SINGAPORE 259772
Email: [email protected]
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[9] Villar L, Dayan GH, Arredondo-García JL, Rivera DM, Cunha R, Deseda C. Efficacy of a tetravalent
dengue vaccine in children in Latin America. N Engl J Med. 2015 Jan 8;372(2):113-123.
[10] DVI January 2015 Newsletter. http://www.denguevaccines.org/dvi-january-2015-newsletter - accessed
18 April 2016.
[11] Advocacy for Immunisation. Web resources developed by PATH and Johns Hopkins, powered by GAVI,
the Vaccine Alliance. http://advocacy.vaccineswork.org - accessed 18 April 2016.
[12] Thisyakorn U, Capeding MR, Goh DY, Hadinegoro SR, Ismail Z, Tantawichien T, et al. Preparing for
dengue vaccine introduction in ASEAN countries: recommendations from the first ADVA regional
workshop. Expert Rev Vaccines. 2014 May;13(5):581-587.
[13] Gubler DJ. The partnership for dengue control – a new global alliance for the prevention and control
of dengue. Vaccine. 2015 Mar 3;33(10):1233.
[14] Dengue Vaccine Initiative. Development of dengue vaccines: status review and future considerations.
Available at: http://www.denguevaccines.org/sites/default/files/APDPBreport_Seoul%20Nov%20
2014_10315.pdf - accessed 18 April 2016.
[15] Chao DL, Halstead SB, Halloran ME, Longini IM Jr. Controlling dengue with vaccines in Thailand. PLoS
Negl Trop Dis. 2012;6(10):e1876.
[16] Wasi P. Triangle that moves the mountain and health systems reform movement in Thailand. Human
Resources Development Journal. 2000;4:106–110.
[17] Pang T, Thiam DG, Tantawichien T, Ismail Z, Yoksan S. Dengue vaccine--time to act now. Lancet. 2015
May 2;385(9979):1725-1726.
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Dengue Bulletin – Volume 39, 2016
Book Review
Dengue and dengue haemorrhagic fever
(2nd Edition; Edited by Duane J. Gubler, Eng Eong Ooi,
Subash Vasudevan and Jeremy Farrar. 2014)
Dengue is one of the fastest transmitting arbovirus diseases; no longer confined to just one
region, it has expanded from country to country and region to region, taking a significant
number of lives every year. It is estimated that every year there are 390 million new infections
and 29 000 deaths due to dengue in over 128 countries. Dengue is caused by dengue viruses
(four serotypes-DENV-1, DENV-2, DENV-3 and DENV-4) belonging to the genus Flavivirus,
family Flaviviridae. The disease pattern and prevalence of dengue is dynamic and has gone
through continuous changes ever since its evolution. With the changing disease pattern and
the advancement of technology, the prevention, management, and research are continuously
changing and it is therefore essential to update knowledge about recent developments for
clinicians, researchers and managers. The book Dengue and Dengue Haemorrhagic Fever,
2nd edition, edited by Duane J. Gubler, Eng Eong Ooi, Subash Vasudevan and Jeremy Farrar,
which has nicely captured and compiled the updates from around the world and reports on
recent advances, is useful for all categories of readers.
The book runs into 606 pages divided into five parts (history and epidemiology, the
disease, the virus, virus-host interaction and dengue prevention). There are 29 excellent
articles (chapters) contributed by a number of eminent experts.
The book was published in 2014 with the intention that the authors’ research efforts
would deliver several promising prevention and control tools for dengue. The book was
successful in this regard; articles on economic burden study, surveillance, immunological
response, clinical management guidelines, and vector control help managers to analyse, plan
and adopt effective strategies for dengue prevention.
The first six chapters in the book clearly explain the evolution of dengue viruses, their
pattern of transmission and the disease burden. A nice comparison of the region to region,
recent challenges of intercontinental movements of dengue holds the attention of the readers
while the economic burden of the diseases should spur policy-makers to develop effective
strategies to address the situation.
The second part of the book “deals with the clinical side of the disease and explains
the pathogenesis, clinical features and management guidelines”. Here again, the regional
experience has been shown and evidence from clinicians’ practical experiences has been
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Dengue and dengue haemorrhagic fever
compiled that guides the reader to make a decision while handling any outbreak or simply
managing a case. The third and fourth parts are basically for the molecular scientist and
microbiologist who can gain insights into the immunological reactions of the human and other
hosts to the dengue viruses. At the same time, the final section makes a nice compilation
for students and researchers, providing good reference and evidence elaborating the recent
advancement on dengue preventions that is also another effective evidence for policy makers
and implementers. Chapter 25 highlights the example of yellow fever, which is emerging
again in recent days, and notes that yellow fever was controlled in Cuba by controlling the
vectors and sources; this is also a relevant example in today’s scenario.
The research-based articles identify the research gaps in their own field and suggest further
investigations to enable strong conclusions to be drawn. In the preface, Gubler quotes, “There
are still a number of unresolved issues related to Dengue viruses …” The book identifies
most of the areas where further work is required and advocates more research.
The chapters are distributed in an orderly manner; starting with the burden and
epidemiology of the disease, the book takes the readers to the proper surveillance, case
management, immunology, virus-host interaction and finally to the recent updates on dengue
prevention.
Readers can easily find the main and related topics of their interest. There is a consistent
flow of chapters following a common theme of generating more information about dengue.
Though the authors belong to different parts of the world, uniformity in the writing style and
the choice of simple wording can be seen throughout the book, and this makes it palatable
for all sets of readers. The scientific articles explain the technical terms and elaborate the
explanation in a brief way that helps a layman to understand the terms easily.
Most of the papers have used secondary sources and the authors did their analysis
with existing papers and documents on the recent developments (up until 2014). In the
preface, the editor describes the objective of the book and summarizes the key findings.
The referencing style has followed the international standard (APA) and helps the reader
find the references promptly. The graphs and charts used in the book are self-explanatory
and relevant to the articles; editors have maintained this uniformity throughout the articles
and this is much to be appreciated.
However, as the book makes clear, there are still many vague areas that need to be
clarified; examples include clinical case definition, virus biology and pathogenesis, animal
models and efficacy of existing vector control methods. As already pointed out by the editors,
there may be a few conflicting statements in the book, due to the large number of authors
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Dengue Bulletin – Volume 39, 2016
Dengue and dengue haemorrhagic fever
The editors have been very careful to include the most updated information on all aspects
of dengue.
This is a wonderful book available on dengue. For sure, this book will be extremely
useful to researchers, public health specialists, teachers and students as well as physicians.
Professor A. P. Dash
Vice Chancellor
Central University of Tamil Nadu
Thiruvarur - 610 101, India
Ex- Distinguished Scientist Chair
Formerly Regional Adviser, WHO/SEARO
Dengue Bulletin – Volume 39, 2016
119
Instructions for contributors
Instructions for contributors
Dengue Bulletin welcomes all original research papers, short notes, review articles, letters to
the Editor and book reviews which have a direct or indirect bearing on dengue fever/dengue
haemorrhagic fever prevention and control, including case management. Papers should not
contain any political statement or reference.
Manuscripts should be typewritten in English in double space on one side of white A4-size
paper, with a margin of at least one inch on either side of the text and should not exceed 15
pages. The title should be as short as possible. The name of the author(s) should appear after the
title, followed by the name of the institution and complete address. The e-mail address of the
corresponding author should also be included and indicated accordingly.
References to published works should be listed on a separate page at the end of the paper.
References to periodicals should include the following elements: name and initials of author(s);
title of paper or book in its original language; complete name of the journal, publishing house
or institution concerned; and volume and issue number, relevant pages and date of publication,
and place of publication (city and country). References should appear in the text in the same
numerical order (Arabic numbers in parentheses) as at the end of the article. For example:
(1) Kroeger A, Lenhart A, Ochoa M, Villegas E, Levy M, Alexander N, et al. Effective control
of dengue vectors with curtains and water container covers treated with insecticide in
Mexico and Venezuela: cluster randomised trials. BMJ 2006;332:1247–52.
(2) Dengue: guidelines for diagnosis, treatment, prevention and control. Geneva: World
Health Organization; 2009.
(3) Nathan MB, Dayal-Drager R. Recent epidemiological trends, the global strategy and public
health advances in dengue: report of the Scientific Working Group on Dengue. Geneva:
World Health Organization; 2006 (TDR/SWG/08).
(4) DengueNet database and geographic information system. Geneva: World Health
Organization; 2010. Available from: www.who.int/dengueNet [accessed 11 March 2010].
(5) Gubler DJ. Dengue and dengue haemorrhagic fever: Its history and resurgence as a global
public health problem. In: Gubler DJ, Kuno G (ed.), Dengue and dengue haemorrhagic
fever. CAB International, New York, NY,1997,1–22.
Figures and tables (Arabic numerals), with appropriate captions and titles, should be included
on separate pages, numbered consecutively, and included at the end of the text with instructions
as to where they belong. Abbreviations should be avoided or explained at the first mention.
Graphs or figures should be clearly drawn and properly labelled, preferably using MS Excel, and
all data clearly identified.
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Dengue Bulletin – Volume 39, 2016
Instructions for contributors
Articles should include a self-explanatory abstract at the beginning of the paper of not more
than 300 words explaining the need/gap in knowledge and stating very briefly the area and period
of study. The outcome of the research should be complete, concise and focused, conveying the
conclusions in totality. Appropriate keywords and a running title should also be provided.
Articles submitted for publication should be accompanied by a statement that they have not
already been published, and, if accepted for publication in the Bulletin, will not be submitted
for publication elsewhere without the agreement of WHO, and that the right of republication in
any form is reserved by the WHO Regional Offices for South-East Asia and the Western Pacific.
One hard copy of the manuscript with original and clear figures/tables and a computer
diskette/CD-ROM indicating the name of the software should be submitted to:
The Editor
Dengue Bulletin
WHO Regional Office for South-East Asia
Indraprastha Estate
Mahatma Gandhi Marg
New Delhi 110002, India
Telephone: +91–11–23370804
Fax: +91–11–23379507, 23370972
E-mail: [email protected]
Manuscripts received for publication are subjected to in-house review by professional experts
and are peer-reviewed by experts in the respective disciplines. Papers are accepted on the
understanding that they are subject to editorial revision, including, where necessary, condensation
of the text and omission of tabular and illustrative material.
Original copies of articles submitted for publication will not be returned. The principal author
will receive 10 reprints of the article published in the Bulletin. A pdf file can be supplied on request.
Dengue Bulletin – Volume 39, 2016
121
ISSN 0250-8362
The WHO Regional Office for South-East Asia publish the annual Dengue Bulletin.
All manuscripts received for publication are subjected to in-house review by
professional experts and are peer-reviewed by international experts in the
respective disciplines.
Dengue Bulletin
The objective of the Bulletin is to disseminate updated information on the
current status of dengue fever/dengue haemorrhagic fever infection, changing
epidemiological patterns, new attempted control strategies, clinical management,
information about circulating DENV strains and all other related aspects. The
Bulletin also accepts review articles, short notes, book reviews and letters to the
editor on DF/DHF-related subjects. To provide information for research workers and
programme managers, proceedings of national/international meetings are also
published.
2016
Volume 39, December 2016
Dengue
Bulletin
Volume 39, December 2016
WHO
I S SN 0250- 8362