Dengue Bulletin – Volume 38

Transcription

ISSN 0250-8362
The WHO Regional Office for South-East Asia, in collaboration with the Western
Pacific Region, jointly 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.
2014
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. Proceedings of national/international meetings
for information of research workers and programme managers are also published.
Volume 38, December 2014
Dengue
Bulletin
Volume 38, December 2014
South-East Asia Region
WHO
Western Pacific Region
I S S N 0250- 8362
South-East Asia Region
Western Pacific Region
The 38th edition of Dengue Bulletin is in your hands. As always, it has quality
articles from scientists from all over the world and on all aspects of dengue.
I am sure the cumulative information available in this volume of Dengue
Bulletin shall be useful to national authorities, dengue programme managers and
scientists. I also take this opportunity to invite technical articles and field
experiences on prevention and control of dengue for possible inclusion in the
39th edition of Dengue Bulletin that will be published in December 2015.
We now invite contributions for Volume 39 (2015). The deadline for receipt
of contributions is 30 June 2015. While preparing their manuscripts, contributors
are requested to please peruse the instructions given at the end of the Bulletin.
Contributions should either be sent, accompanied by CD-ROMs, 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: se_denguebulletin@who.int. Readers who want to
obtain copies of the Dengue Bulletin may write to the WHO Regional Offices in
New Delhi or Manila or the WHO country representative in their country of
residence.
Regional Adviser, Vector-Borne and Neglected
Tropical Diseases Control (RA-VBN), and
Editor, Dengue Bulletin
World Health Organization
Regional Office for South-East Asia
New Delhi-110002, India.
Contents
Acknowledgements................................................................................................... iii
Preface...................................................................................................................... v
1.
Epidemiological importance of container pupal index (CPI), for vector
surveillance and control of dengue in national capital territory (NCT) – Delhi,
India................................................................................................................. 1
J Nandi, Aditya Prasad Dash, PK Dutta, AC Dhariwal
2.
Pattern of dengue serotypes in four provinces of northern Thailand from
2003–2012..................................................................................................... 11
Punnarai Veeraseatakul, Sawalee Saosathan and Salakchit Chutipongvivate
3.
Estimation of the adjustment factor for hospitalized clinical cases
diagnosed and tested for dengue in Madurai, Tamil Nadu (India)..................... 20
Brij KishoreTyagi, Shanmugavel Karthiga, ChellaswamyVidya, Narendra KArora, Deoki Nandan,
Yara A Halasa, Jhansi Charles, N Mohan, Poovazhagi Varadarajan, T Mariappan, P Philip Samuel,
R Paramasivan, S Vivek Adhish, Mukul Gaba, R T Porkaipandianh and Donald S Shepard
4.
Dengue vectors survey at Punjab University, Lahore, Pakistan,
January 2012 – April 2014............................................................................... 33
Muhammad Saeed Akhtar, Ayesha Aithetasham, Mehwish Iqtedar,
Nasim Begum and Muhammad Akhtar
5.
Trends in dengue during the periods 2002–2004 and 2010–2012 in a
tertiary care setting in Trivandrum, Kerala, India............................................... 43
Henna AS, Ijas Ahmed K, Harilal SL, Saritha N, Ramani BaiJ T, Zinia T Nujum
6.
Evaluation of the efficacy of thermal fogging applied in closed premises on
dengue vector Aedes aegypti in Malaysia......................................................... 54
Nurulhusna AH, Khadijah K, Khadri MS, Roziah A,Muhamad-Azim MK, Mahirah MN,
Khairul-Asuad M, Ummi Kalthom, S and Lee HL
7.
Civil-military cooperation (CIMIC) for an emergency operation against a
dengue outbreak in the western province, Sri Lanka........................................ 64
HA Tissera, PC Samaraweera, BDW Jayamanne, WCD Botheju, NWAN Wijesekara,
MPPU Chulasiri, MDS Janaki, KLNSK De Alwis, P Palihawadana
Dengue Bulletin – Volume 38, 2014
i
8.
Dengue in South Asian sub-continent: how well have the surveillance
systems done?................................................................................................. 78
Ananda Amarasinghe, Anil K Bhola, Scott B Halstead
9.
Evaluation of sensitivity and specificity of commercially available dengue
rapid test kit in two hospitals in Colombo, Sri Lanka........................................ 84
Hasitha A Tissera, Dinindu P Kaluarachchi, Thilini D Jayasena, AnandaAmarasinghe,
Aravinda M de Silva, BuddikaWeerakoon, SunethraGunasena, Jayantha S D K Weeraman,
Duane Gubler, Annelies Wilder-Smith, Paba Palihawadana
10. Prevalence of dengue vector in relation to dengue virus infection in
central region of Nepal.................................................................................... 96
Bijaya Gaire, Komal Raj Rijal, Biswas Neupane, Pravin Paudyal, Ishan Gautam,
Megha Raj Banjara, Kouichi Morita and Basu Dev Pandey
11. The first tetravalent dengue vaccine is poised to combat dengue................... 108
Usa Thisyakorn, Maria Rosario Capeding & Sri Rezeki Hadinegoro
12. Trends of imported dengue fever cases in Japan, 2010 to 2013...................... 113
Meng Ling Moi, Akira Kotaki, Shigeru Tajima, Makiko Ikeda, Kazumi Yagasaki, Chang-kweng Lim,
Hitomi Kinoshita , Eri Nakayama, Yuka Saito, Ichiro Kurane, Kazunori Oishi, Masayuki Saijo,
Tomohiko Takasaki
13. Instructions for contributors........................................................................... 120
ii
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. Baruah, Kalpana
Joint Director
National Vector Borne Disease Control
programme
Sham Nath Marg
Delhi-110 054, India
2. Dash, Aditya P.
Former Regional Adviser VBN
190 Dharma Vihar, Jagamara
Bhubaneswar 751030, INDIA
3. Gubler, Duane J.
Professor, Emerging Infectious Diseases
Program
Duke-NUS Graduate Medical School
Singapore
4. Hoti, S.L.
Scientist
Regional Medical Research Centre
Nehru Nagar
Belgaum, India
5. Jambulingam, Purushothaman
Director Vector Control Research Centre
Medical Complex, Indira Nagar
Puducherry-605006, India
6. Kalayanarooj, Siripen
Queen Sirikit National Institute of Child Health
Bangkok, Thailand
7. Mourya, D.T.
Director
National Institute of Virology
Dr Ambedkar Road
Pune-411001, India
8. Nagpal, B.N.
Scientist
National Institute of Malaria Research
Sector 8, Dwarka
New Delhi-110 077, India
9. Sharma, R.S.
Additional Director
National Centre for Disease Control
New Delhi, India
10. Shepard, Donald S
Schneider Institutes for Health Policy
Brandeis University
Massachusetts, USA
11. Thisyakorn, Usa
Faculty of Tropical Medicine
Mahidol University
Bangkok 10400, Thailand
12. Tyagi, B K
Scientist and Director
Centre for Research in Medical Entomology
Chinnachokkikulam
Madurai-625002, India
13. Velayudhan, Raman
Vector Ecology and Management
Department of Control of Neglected Tropical
Diseases (HTM/NTD)
Geneva, Switzerland
14. Yadav, Dr Rajpal
Scientist-in-Charge
Vector Ecology and Management
Department of Control of Neglected Tropical
Diseases
Geneva, Switzerland
The quality and scientific standing of the Dengue Bulletin is largely due to the conscientious
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.
iii
Preface
The ongoing spread of dengue in the WHO South-East Asia Region
(SEAR) continues to be a major public health concern. Our Region
contributes to more than half of the global burden of dengue.
About 52% of the global population at risk resides in this Region.
The disease is endemic in 10 of the 11 Member States.
Dengue cases have been regularly reported in this Region since
2000. The Region was severely hit in 2010 with more than 350 000
cases and around 2000 deaths. The number of cases in 2013
surpassed even this figure, with Member States reporting almost
400 000 cases. Five of our Member States viz. India, Indonesia,
Myanmar, Sri Lanka and Thailand are among the 30 most highly endemic countries in the
world.
Up to June 2014, 76 492 cases have been reported from endemic countries in the Region
with 348 deaths. As many as 35 640 cases and 316 deaths were reported from Indonesia
alone during this period.
Dengue is also a major public health problem in several countries of the Western Pacific
Region which surround the South-East Asia Region. Malaysia, Philippines and Singapore
have reported thousands of cases this year. There are reports of dengue cases in the Pacific
islands including New Caledonia, French Polynesia and the Solomon islands.
To combat this rapidly growing viral infection, we must keep pace with the changing
epidemiology of dengue, especially the multiple ecological factors that influence the spread of
this disease. Being a vector-borne disease, ever increasing numbers and varieties of mosquitobreeding habitats are being created with rapid and poorly planned urbanization, globalization,
consumerism, poor solid waste and water management and increasing population movement
without adequate measures to prevent vector breeding. Climate change is also influencing
ecology that benefits vectors.
Proper case management has helped Member States in reducing the case-fatality ratio
to less than 0.5%. This is a commendable achievement. The objective now is to prevent
any deaths due to dengue. Substantial research is being undertaken to improve our case
management protocols and methods. Clinical trials for dengue vaccine are also in advanced
stages with optimistic outcomes. Availability of an efficacious and affordable dengue vaccine
shall provide a strong intervention in our fight against dengue.
v
WHO has been assiduously working through advocacy, normative functions and provision
of technical support to Member States against dengue. We continue to advocate to the
governments on the public health importance of vector-borne diseases, especially dengue
and its control, strengthening of public health systems in Member States including capacitybuilding and allocation of appropriate resources.
In accordance with its mandate of disseminating scientific information, WHO – through
the annual issues of Dengue Bulletin – has been providing a platform to scientists all over
the world to disseminate the peer-reviewed research and best practices in different settings
that can be used to improve public health response against dengue.
Dr Poonam Khetrapal Singh
Regional Director
WHO South-East Asia Region
vi
Epidemiological importance of container pupal
index (CPI) for vector surveillance and control of
dengue in national capital territory (NCT) – Delhi, India
J Nandia#, Aditya Prasad Dashb, PK Duttac, AC Dhariwala
a
Directorate of National Vector Borne Disease Control Programme, 22 Shamnath Marg,
Delhi 110054, India
Former Regional Adviser, WHO/SEARO, New Delhi
b
Ex- Associate Professor of Preventive and Social Medicine, Armed Force Medical College, Pune
c
Abstract
Dengue fever (DF) is endemic in National Capital Territory (NCT) Delhi. The disease vector, Aedes
aegypti is deeply entrenched in urban NCT Delhi and its surrounding National Capital Region
(NCR) as well. Vector population change with seasonal fluctuations of breeding indices, container
index (CI) and container pupal index (CPI) were positively correlated with proportion of breeding
habitats found positive for pupae as well as incidence of DF. Present communication descried the
potential the breeding containers with pupa in domestic environment identifying most productive
containers. This information can be used as a tool for vector surveillance. National institutions
engaged in vector-borne disease control and also teaching institutions are to formulate guidelines
on vectors surveillance and training module targeting potential containers. Incorporation of this
tool in national strategy for dengue control will be more meaningful interventions to reduce the
adult emergence in high risk localities by targeting most productive breeding containers in terms
of CPI. Seasonal productive containers in domestic and peri-domestic environment for pupae
require vigorous search during monsoon and post-monsoon months for elimination of productive
breeding habitats. CPI and proportion of containers positive with pupae should be the basis for
vector surveillance and disease control. Enormous population migration, rapid growth of urban and
peri-urban areas, water storage practices, lax behavior of communities towards weekly cleaning of
containers rendered NCT Delhi a high endemic zone of DF. An effective vector control method
based on CPI and seasonally most productive containers are to be targeted must be taken into
longitudinal vector surveillance programme to achieve objective of global strategies for dengue
prevention and control.
Keywords: Dengue fever; Container index; Seasonal productivity.
#
E-mail: nandi.nvbdcp@gmail.com
1
Epidemiological importance of CPI for vector surveillance and control of dengue in NCT - Delhi, India
Introduction
Dengue fever (DF) probably was reported in India in 1872 from Calcutta (now Kolkata),
West Bengal1. An epidemic of dengue hemorrhagic fever (DHF) was reported in July 1963
in Kolkata when more than 0.1 million people were affected, mostly children with 40% case
fatality rate in hospital admitted DHF cases2. Dengue fever (DF) has been a major arbo-viral
disease in NCT Delhi3. Outbreak of DF continued to occur since 1996 when highest number
of cases and deaths were reported4. All four serotypes of DF and many genotypes including
DENV-3, subtype-III, the virulent strain responsible for DHF and dengue shock syndrome,
were recorded circulating in NCT Delhi and its surrounding areas5,6. An outbreak of DF in
1988 in NCT Delhi recorded 33% mortality among children admitted in hospitals7.
Following the DHF outbreak in Kolkata, a reconnaissance survey of Aedes aegypti in
1964 described perennial breeding habitats and breeding behavior in Delhi8. Transmission of
DF is determined by the seasonal breeding propensity, container larval index and containers
positive for pupae of Aedes aegypti9. Earlier studies in NCT Delhi were mostly based on
traditional House Index (HI), Container Index and Breteau Index to measure to larval positive
containers. No survey on pupal positivity of containers were conducted in NCT Delhi, hence
this survey was taken up.
Anti-larval operations by source reductions during transmission months are to be
organized based on containers positivity with pupae and there classification in domestic
environment. The traditional House Index and Breteau Index approaches were less sensitive
in controlling the DF as the indices were to measure only larvae positive containers. The
pupae positive survey by the estimation of container pupal index per house would be useful
in targeting source reduction and more systematic survey methodologies10.
This communication is observed on breeding habitats and seasonal productive containers
in relation to positive for pupae and their implication in vector surveillance and control11.
Study area
The NCT Delhi is a narrow strip of indo-Gangetic plain, lying between 28025’ and 28053’ north
latitude and 76050’ and 77022’ east longitude. The NCT Delhi is divided in 14 administrative
zones implementing vector control strategies.
(1) Municipal Corporation of Delhi: 1399 sq.km.
zz
2
South Delhi Municipal Corporation comprising five zones namely South, Central,
West, Nazafgarh and Delhi Cantonment.
zz
East Delhi Municipal Corporation comprising two zones Shahdra (North) and
Shahdra (South).
zz
North Delhi Municipal Corporation comprising six zones City, Civil Lines, S.P. Ganj,
Karol Bagh, Rohini and Narela
(2) New Delhi Municipal Council : 42.74 sq. km. (Figure 1)
Besides these 14 administrative zones, seven independent agencies have also been
implementing vector control strategies. These independent agencies were:
(1) Delhi Cantonment Board: 42.89 sq. km.
(2) Jawaharlal Nehru University: restricted area
Figure 1: Map showing zones under Municipal Corporation of Delhi and New Delhi
Municipal Council
Delhi Cantt. Zone
NMDC
North Delhi Municipal
Corporation
South Delhi Municipal
Corporation
East Delhi Municipal
Corporation
3
(3) Zoological Park: restricted area
(4) Indian Institute of Technology: restricted area
(5) All India Radio: restricted area
(6) President’s Estate: restricted area
(7) Northern Railways: restricted area
NCT Delhi, in recent times, experienced a remarkable growth of population due to large
scale migration mostly from rural areas of various states of the country. The metro city also
witnessed a phenomenal vertical growth in residential building construction, commercial
complex, shopping malls and educational institutions leading to rapid urbanization that
exerted increased demand for civic amenities, particularly on water supply and solid waste
disposal.
Materials and methods
Reporting and case definition: Confirmed dengue cases from all over India are reported
to National Vector Borne Disease Control Programme (NVBDCP) monitoring vector-borne
diseases. Patients with clinical symptoms like sudden onset of high fever, severe body ache
and headache, myalgia, nausea, vomiting and rash with positive IgM in a single serum
specimen were considered as confirmed dengue cases. Clinical symptoms with lower
thrombocytopenia and leucopenia were also taken as confirmed cases of dengue fever. The
presence of both these two criteria with hemorrhagic manifestation and deaths were taken
as confirmed deaths due to dengue fever12.
Monthly surveillance of vector breeding habitats was carried out by Central Cross
Checking Organization (CCCO) under NVBDCP through search of various containers both
in domestic and peri-domestic human environment. Vector breeding habitats or containers
were searched on weekly basis in various localities of Municipal Corporation of Delhi and
New Delhi Municipal Council, Delhi including areas under seven independent agencies
implementing vector control strategies as detail in the study areas of NCT-Delhi. During the
two years survey (23 Months) 45 421 houses and 53 307 containers in January-February;
55 648 houses and 64 017 containers in March-April; 62 106 houses and 711 571 containers
in May-June; 55 713 houses and 76 481 containers in July-August; 45 109 houses and 71 850
containers in September-October and 60 229 houses and 69 031 containers in NovemberDecember were searched. The containers positive with larvae and the containers positive
with pupae were recorded.
4
Month-wise incidence of serologically confirmed dengue cases was also recorded. Bimonthly breeding indices for Container Index (CI) and container positive for pupae per house
were recorded and canalized. CPI was derived by calculation of total number of containers
positive with pupa divided by number of houses searched multiplied by 100.
Vector breeding habitats in domestic environment were classified to identify seasonal
productive containers on bi-monthly basis. These were in water vapour room coolers
(colloquially known as desert cooler); cement tanks; plastic drums/barrels and other big or
small plastic containers; earthen pots; metal containers; tyres; flower pots trays and overhead
tanks. Proportion of these containers positive with larvae and pupae were worked out on
bi-monthly basis for 23 months of two years, 2012 and 2013.
Results
During 2012 and 2013, a total of 7667 cases of DF were recorded. Incidence of dengue
fever was 0.05% in both January-February (4 cases) and March-April (5 cases) period,
increased to 0.2% in May-June (13 cases) summer months. The incidence of DF increased
from 0.2% in May-June period to 5.3% during July-August (404 cases) the monsoon months.
DF reached to peak at 79.4% in September-October (6093 cases) period in post monsoon
months. The incidence came down to 15.0% in November-December (1148 cases) period
at the beginning of winter.
Incidence of dengue fever, CI, CPI and proportion of pupae are given in Table 1.
Table 1: Incidence of dengue fever and corresponding container indices
% of dengue
fever
CI
CPI/House
% Container
positive for pupae
Jan-Feb
0.05
0.03
0.02
62.5
Mar-Apr
0.05
0.3
0.1
45.8
May-June
0.2
0.6
0.6
66.7
July-Aug
5.3
5.2
4.6
64.2
Sept-Oct
79.4
3.9
4.2
67.5
Nov-Dec
15.0
0.4
0.1
24.5
Months
Both the CI and CPI were lowest at 0.03 and 0.02 respectively in January-February.
During these two months, 0.05% dengue cases were reported. The proportion of containers
positive with pupae was 62.5.
5
Both CI and CPI were 0.3 and 0.1 respectively for the period of March-April with 0.05%
of dengue cases. Proportion of container positive for pupae was second lowest at 45.8 during
these two months, the onset of north Indian summer. During May-June, the incidence of
dengue cases increased to 0.2% as compared with 0.05% during previous four months
(January-April). The CI was 0.6 and CPI 0.4 during May-June, with containers positive with
pupae increased from 45.8% during March-April to 66.7 in May-June bi-monthly peak
summer months. Introduction of room coolers and increased trend of water storage practices
in domestic environment induced increased proportion of containers positivity with pupae.
Incidence of dengue positive cases was 5.3% in July-August period with CI 5.2 and
CPI 4.6. The incidence of dengue positive cases was at its peak during September-October
period with 79.4% when CI was 3.9 and CPI 4.2. Proportion of containers positive with
pupae decreased marginally to 64.2% in July-August period but again increased to 67.5% in
September-October period when the incidence of dengue cases was at its peak. The increased
proportion of container positivity for pupae was due to spread of breeding infestation to
varieties of containers in domestic and peri-domestic human habitations.
The incidence of DF decreased to 15% with CI at 0.4, CPI at 0.1 and proportion of
container positive with pupae was lowest at 24.5.
Seasonal productivity of containers in domestic environment
During January-February (two months period) 80% of plastic drums, barrels and similar other
plastic containers big or small were found positive with pupae.
In March-April period, 57.3% of plastic containers and similar other big or small plastic
containers with 17.1% metal/scraps containers together formed 74.4% positive for pupae.
Room coolers formed 12.3%; 51.1% of plastic drums, barrels and similar other plastic
containers big or small were found positive with pupae, 12.7% of metal containers/scraps
together made 76.1% of containers positive of pupae in May-June period. Room coolers
(13.2), plastic drums, barrels and similar other plastic containers big or small (34.6), metal /
scraps containers (14.9) and trays used for flower pots (11.4), constituted 74.1% positive for
pupae in July-August bi-monthly period. During September-October period, room coolers;
plastic drums, barrels and similar other plastic containers; earthen pots and metal / scraps
containers formed 82.5% positive for pupae in and around domestic and peri-domestic
situation. Gradual rising trend of breeding of Aedes aegypti was evident from proportion
of room coolers positive for pupae increased from 8.4% in March-April period to 14% in
September-October period. Proportion of containers positive for pupae only decreased to
72.3% in November-December period when 38.5% of plastic drums, barrels and similar
other plastic containers, 16.9% earthen pots and the metal / scraps containers found positive
for pupae (Table 2).
6
Seasonal positivity of containers with pupae:
Table 2: Proportion of containers and types positive for pupae
Months
Overall
proportion
of all
positive
containers
Type of container
Room
coolers
Plastic drum,
barrel similar
other big
or small
containers
Earthen
pots
Metal/
scraps
Flower
pot
trays
Total
Jan-Feb
62.5
0
80.0
0
20.0
0
100.0
Mar-Apr
45.8
8.4
57.3
0
17.1
0
82.8
May-June
66.7
12.3
51.1
10.8
12.7
7.1
94.0
July-Aug
64.2
13.2
34.6
9.6
14.9
11.4
83.7
Sept-Oct
67.5
14.0
32.3
15.2
21.0
4.6
87.1
Nov-Dec
24.5
7.7
38.5
16.9
16.9
1.5
81.5
Abundance of different types of containers positive for pupae, their low mortality
indicated most productive vector population emergence and high transmission potential
during four months period i.e. July to October.
The positive co-relation (0.52) between CPI and proportion of containers positive for
pupae and strong positive correlation (0.9) between CI and CPI were suggestive of very high
breeding potentials of Aedes aegypti in domestic environments. Seasonal increasing trend of
CPI as well as proportion of dengue cases coincided with rainfall months (July to October)
when maximum precipitation occurred. The transmission peak of DF was in SeptemberOctober during the receding monsoon months.
Discussion
Dengue fever has been endemic with regular incidence in NCT-Delhi. Proliferation of
breeding of Aedes aegypti increased during July-August period and continued unabated with
higher containers with pupal infestation during September-October period. Importance of
association of rainfall and dengue outbreak was reported as a disease of monsoon by creating
more breeding sites13. Intensified pupal survey as an important tool for vector surveillance
has been highlighted14,15. Vector control in NCT region is heavily relied on source reduction,
chemical control as larvicidal in water collections and containers, focal thermal fogging in
and around houses with confirmed dengue cases. These anti-larval and anti-adult activities
were supported by health education campaign to enhance community awareness and
7
participation. All these efforts had limited success to either containment of breeding or
prevent occurrence of the disease.
India has been highly endemic for mosquito borne diseases16. NCT Delhi has been a
water scarcity zone. Water storage practices in innumerable varieties of containers were
common in every social stratum in NCT Delhi. Plastic drums/barrels and other similar
receptacles were most productive containers due to storage or collection of potable water
for domestic use and epidemiologically important17. Varieties of plastic containers formed
80% positive with pupae in January-February period were actually “mother foci” involved
in low level transmission18.
Health education messages were incomplete and weak as information to communities
were more towards weekly cleaning of room coolers leaving unconventional breeding
potentials in domestic and peri-domestic environment with prolific breeding potentials
were not targeted. In consideration of high CPI and percentage of highly preferred seasonal
breeding containers, an effective vector control approach is required. Population migration
has been the major concern for unplanned urbanization creating slums, often challenged
with acute scarcity of safe potable water. These factors, primary causes for water storage in
varieties of containers were highly productive for pupae, high emergence and man-mosquito
contact. Data analysis on rising larval, particularly container pupal index in monsoon months
was inadequate to organize effective vector control operations involving communities. Annual
disease incidence of DF has clearly demonstrated managerial inefficiency of surveillance
systems and implementation of strategies for dengue control.
Existing disease surveillance system in NCT Delhi has been oriented to seasonal planning
rather than anticipatory action to prevent recurrence to dengue fever by controlling or
prevention of proliferation of breeding potentials with high vector abundance in terms
of proportion of containers positive for pupae. Monsoon and post monsoon months, the
classical “dengue season” were associated with high proportion of containers positive with
pupae and CPI. Particular search would be required to detect/identify breeding habitats of
room coolers, plastic containers/drums/barrels and other small/medium or big discarded
containers, metal/scraps containers in and around human habitations responsible for highest
proportion of positivity of pupae and thus formed most productive containers.
Vector surveillance based on containers positive for pupae survey during monsoon
months to determine risk areas prone to recurrence or outbreak of dengue for planning
control strategies would be essential. Principles of integrated vector management involving
all strata of residential complexes in association with civic bodies are to be implemented for
effective vector control measures and sustainable achievements. Increasing trend of dengue
has been attributed to three most important factors (i) urbanization, (ii) globalization and
(iii) lack of effective mosquito control19.
8
Human migration in NCT Delhi laid to creation of more slums with acute shortage of
basic facilities for human settlement. Such conditions were identified responsible for emerging
vector-borne diseases in rapidly urbanized metropolitan cities20,21. First spreading dengue
virus has emerged as a major tropical arbo-viral disease. It has imposed a tremendous burden
and economic loss in countries endemic of the disease22.
Acknowledgements
The authors thankfully acknowledge the guidance from Mr N.L. Kalra, former Deputy Director,
NVBDCP, to improve the contents and the manuscript. The most sincere efforts of CCCO
staff are highly appreciated. Authors are grateful to Mr A. Negi, Mr R. Kumar, Mr D. Singh,
Mr A. N. Pandey, Mr A. A. Akhtar and Mr N. K. Jha for their contribution in the preparation
of figures, tables and the compilation of field data.
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R, Singh CP, Tiwari KN, Sekhar K, Rao PVL. Co-circulation of dengue virus serotypes in Delhi, India.
Implication for increased DHF/DSS. Dengue Bulletin. 2006;10:283-287.
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World Health Organ. 1992;70(1):105-8.
[8] Krishnamurthy BS, Kalra NL, Joshi GC, Singh NN. Reconnaissance survey of Aedes aegypti in Delhi.
Bull. Indian Soc. Mal. Commun. Dis. 1965;2(1):56-57.
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World Health Organization, 2003. Document No. TDR/IDE/DEN/03.1.
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[10]Focks DA, Alexender N. Multicountry study of Aedes aegypti pupal productivity survey methodology:
findings and recommendations.Geneva: WHO, 2006. Document No. TDR/IRM/DEN/06.1/2006. http://
www.who.int/tdr/publications/documents/aedes.pdf - accessed 17 December 2014.
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sites. Geneva: WHO, 2011. http://www.who.int/tdr/publications/ documents/sop-pupal-surveys.pdf accessed 17 December 2014.
[12]World Health Organization. Dengue guidelines for diagnosis, treatment, prevention and control. New
edition. Geneva: WHO, 2009.
[13]Li CF, Lim TW, Han LL, Feng R. Rainfall, abundance of Aedes aegypti and dengue infection in Selangor,
Malaysia. South East Asian J Trop Med Pub Health. 1985;16:560-8.
[14]Focks DA, Chadee DD. An epidemiologically significant surveillance method for Aedes aegypti: An
example using data from Trinidad. An. J. Trop. Med Hsg. 1997;56:1959-67. RMID:9080874.
[15]Arunachalam N, Tana Sasilowali, Espino F, Kittayapong P, Abeyewickreme. Eco-bio-social determinants
of dengue vector breeding : a multicentric study in urban and peri-urban Asia. Bulletin of the World
Health Organization. 2010;88:173-184.
[16]Alirol E, Getaz L, Stoll B, Chappuis F, Loutan L. Urbanization and infectious diseases in a globalised
world. www.thelancet.com/infection. 2011 Feb;11:131-41. - accessed 17 December 2014.
[17]Knox t, Nam VS, Yen NT, Kay B, Ryan P. Optimising surveillance for dengue vector immatures in large
water storage containers in Vietnam. Arbovirus Research in Australia. 2005;9:184-187.
[18]Chandler AC. Factors influencing the uneven distribution of Aedes aegypti in Texas cities. American
Journal of Tropical Medicines. 1945;25:145-149.
[19]Gubler DJ. Dengue, urbanization and globalization: the unholy trinity of the 21st century. Trop Med
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[20]Hofez PJ, Fenwick A, Savioli L, Molyneux DH. Rescuing the bottom billion through control of neglected
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Soc Trop Med Hsg. 2008 Jun;102(6):570-7. doi: 10.1016/j.trstmh.2008.02.015. Epub 2008 Apr 9.
10
Pattern of dengue serotypes in four provinces of
northern Thailand from 2003–2012
Punnarai Veeraseatakul,a# Sawalee Saosathana and Salakchit Chutipongvivateb
Regional Medical Sciences Center 1 Chiangmai, Department of Medical Sciences, Ministry of Public
Health, Chiangmai 50180, Thailand
a
Regional Medical Sciences Center 6 Chonburi, Department of Medical Sciences, Ministry of Public
Health, Chonburi 50180, Thailand
b
Abstract
Dengue virus infection is an epidemic prone infectious disease and currently a major health problem
in Thailand including four provinces of the northern region; Chiangmai, Lamphun, Lampang and
Mae Hong Son. This study determined the dengue serotype from dengue patients in these provinces
from January 2003 to December 2012, a total of 1,756 seropositive acute samples were tested
specifically for dengue serotype by reverse transcriptase polymerase chain reaction (RT-PCR).
Eight hundred and ninety five samples were positive RNA dengue virus, of which 40.3% were the
predominant dengue serotype DENV-1, followed by 37.7% DENV-2, 13.4% DENV-4 and 8.6%
DENV-3, respectively. Throughout 10 years, the pattern of predominant dengue serotypes showed
mainly switching between two serotypes; as a sequence from 2003 to 2005, DENV-2 was 59.7%,
70.3% and 44.1%, respectively. From 2006 to 2009, DENV-1 was 54.2%, 61.1%, 74.2% and
61.8%, respectively. From 2010 to 2011, DENV-2 was 59.3% and 81.8%. Lastly in 2012, DENV-1
was 44.3%. Our results indicated that all four dengue serotypes were circulating and coexisting
in this region and the predominant serotypes were not stable and changed between DENV-1 and
DENV-2. This pattern may occur continuously in northern Thailand, it was affected in the group
of non-immunity population to new predominant, to increasing of patient. This information will
be beneficial to surveillance system of dengue infection control.
Keywords: Dengue serotype; Northern Thailand.
Introduction
Dengue is a mosquito-borne viral infection and has become a major disease in Thailand and
a public health problem. In the past 25 years, the dengue outbreak occurred many times
with a high incidence rate per 100 000 population, the largest epidemic ever recorded was
shown in 1987 at 325.11 and the incidence rate per 100 000 population in the periods of
#
E-mail: : punnarai.v@dmsc.mail.go.th; Fax: 66-53-112192
11
Pattern of dengue serotypes in four provinces of northern Thailand from 2003–2012
1997, 1998, 2001, 2002, 2008 and 2010 were 167.21, 211.42, 224.43, 187.52, 141.78 and
183.59, respectively.2-4 Dengue virus is in the Flaviviridae family genus Flavivirus and is divided
into four serotypes:DENV-1, DENV-2, DENV-3 and DENV-4 that are genetically related
but antigenically distinguishable.5 The phenomenon of co-circulation of multiple dengue
serotypes is referred to as hyperendemicity on account of dengue haemorrhagic fever (DHF)
recovery from infection by one provides lifelong immunity against that particular serotype,
but cross-immunity to the other serotypes after recovery is only partial and temporary.6-8
Subsequent infections by other serotypes increase the risk of developing severe dengue.
The previous reports of predominant dengue serotype in Bangkok showed DENV-1 from
1990-1992, DENV-2 from 1973-1986 and 1988-1989; DENV-3 in 1987 and 1995-1999;
and DENV-4 from 1993-1994.9-10 Anantapreecha et al.3 detected the most common DENV1 in 2001 and DENV-2 in 2002 from six provinces across Thailand. In north of Thailand,
four provinces such as Chiangmai, Lamphun, Lampang and Mae Hong Son have a large
area (49 828 163 sq.km) and population (3 061 482 mid-year population in 2012), and
have subsequently reported dengue incidence rate from 2003 to 2012 with 95.12, 55.56,
97.34, 46.67, 48.66, 199.34, 99.39, 303.37, 35.26 and 81.33, respectively.4 Whereas
dengue vaccine development is currently being investigated in clinical trial, the efficient
dengue surveillance, prevention and control programme plays a key role in the strategy of
Thailand. Hence, the data of continuous dengue serotype circulation is an important factor
in effectively developing dengue surveillance and prevention and control programmes. The
objective of this study was to determine the pattern of dengue serotypes in four provinces
of northern Thailand from 2003-2012.
Specimen
Serum samples were collected from dengue patients in four provinces of northern Thailand
including Chiangmai, Lamphun, Lampang and Mae Hong Son (Figure 1) during 2003-2012
and were confirmed for dengue infection by IgM/IgG ELISA.11 A total of 1756 seropositive
acute samples were subsequently subjected to dengue serotype examination at Regional
Medical Sciences Center 1 Chiangmai, Thailand (RMSC1_CM).
Viral RNA extraction
Dengue viral RNA was extracted by using QIAamp viral RNA Mini Kit, Cat. No. 52 904
(QIAGEN, Hilden, Germany) according to manufacturer’s instruction. 12 The eluted RNA
was kept in -70°C until use.
12
RT-PCR
Figure 1: Map of four provinces of northern
Thailand
Dengue serotype was performed by using
two steps conventional RT-PCR according
to protocol previously described by
Yenchitsomanus et al.13 Dengue serotypes
were identified by the size of the resulting
bands with 504 bp of DENV-1, 346 bp of
DENV-2, 196 bp of DENV-3 and 145 bp
of DENV-4.
Results
The number of seropositive acute samples
and percentage of dengue serotypes in
the four provinces from 2003 to 2012 are
shown in Table 1. The data of all ten years,
a total of 1756 seropositive acute samples
were analyzed, of which 895 samples
(51.0%) were positive specific dengue
serotype by RT-PCR. All four dengue
serotypes were found during this study, of which DENV-1 was the most predominant serotype
40.3%, followed by DENV-2, DENV-4 and DENV-3 as 37.7%, 13.4% and 8.6%, respectively.
Table 1: Summary of dengue serotypes in 4 provinces of northern Thailand, 2003–2012
Dengue serotype (%)
Year
Seropositve
acute sample
Positive
dengue RNA
DENV-1
DENV-2
DENV-3
DENV-4
2003
205
62
20 (32.3)
37 (59.7)
2 (3.2)
3 (4.8)
2004
257
148
37 (25.0)
104 (70.3)
2 (1.4)
5 (3.4)
2005
241
136
26 (19.1)
60 (44.1)
13 (9.6)
37 (27.2)
2006
161
72
39 (54.2)
3 (4.2)
4 (5.6)
26 (36.1)
2007
238
126
77 (61.1)
12 (9.5)
3 (2.4)
34 (27.0)
2008
250
97
72 (74.2)
7 (7.2)
11 (11.3)
7 (7.2)
2009
97
55
34 (61.8)
3 (5.5)
18 (32.7)
0 (0.0)
2010
68
54
16 (29.6)
32 (59.3)
6 (11.1)
0 (0.0)
2011
92
66
5 (7.6)
54 (81.8)
6 (9.1)
1 (1.5)
2012
147
79
35 (44.3)
25 (31.6)
12 (15.2)
7 (8.9)
Total
1756
895
361 (40.3)
337 (37.7)
77 (8.6)
120 (13.4)
13
The pattern of dengue serotypes by year from 2003 to 2012 was shown in Figure 2. During
2003-2005, a total of 62, 148 and 136 samples showed the proportion of predominant
serotype DENV-2 as 59.7%, 70.3% and 44.1%, respectively, followed by serotype DENV-1
as 32.3% in 2003 and 25.0% in 2004, while DENV-4 was 27.2%.in 2005. During 20062009, a total of 72, 126, 97 and 55 samples showed the proportion of predominant serotype
DENV-1 as 54.2%, 61.1%, 74.2% and 61.8%, respectively, followed by serotype DENV-4 as
36.1% in 2006 and 27.0% in 2007, whereas DENV-3 as 11.3% in 2008 and 32.7% in 2009.
During 2010-2011, the result of 54 and 66 samples showed the proportion of predominant
serotype DENV-2 as 59.3% and 81.8%, with followed by serotype DENV-1 as 29.6% and
DENV-3 as 9.1%, respectively. In 2012, a total of 79 samples showed DENV-1 as 44.3% and
followed by DENV-2 as 31.6%.
Figure 2: The pattern of dengue serotypes in northern Thailand by year
from 2003 to 2012
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
2003
n=62
DENV-4
DENV-3
DENV-2
DENV-1
2004
n=148
2005
n=136
2006
n=72
2007
n=126
2008
n=97
2009
n=55
2010
n=54
2011
n=66
2012
n=79
The pattern of dengue serotypes by province from 2003 to 2012 is shown in Figure 3 (A-D).
The number of positive dengue RNA in each province, which has more than 5 samples per
year was analyzed. The data study of Chiangmai province has shown throughout 10 years,
the predominant dengue serotype was DENV-2 during 2003-2005 and 2010-2011 as 54.8%,
71.4%, 52.0%, 67.7% and 50.0%, respectively. DENV-1 was predominant as 56.9%, 85.1%,
79.2% and 40.0% in 2006, 2008, 2009 and 2012, respectively. DENV-4 was predominant in
2007 as 53.9% (Figure 3A). In Lamphun province, the data of predominant dengue serotypes
in seven years were showed DENV-2 as 50.0% in 2004, DENV-4 as 61.8% and 77.8% in
2005 and 2006, respectively. During 2007-2009 and in 2012, DENV-1 was 85.7%, 76.2%,
79.2%and 87.5%, respectively (Figure 3B). In Lampang province, the predominant dengue
serotypes in six years were showed mainly DENV-2 from 2003 to 2005, 2007 and 2011 as
62.5%, 79.3%, 40.0%, 33.3% and 80.0%, respectively. DENV-1 was predominant as 71.4% in
2006 (Figure 3C). In Mae Hong Son province, the predominant dengue serotypes throughout
eight years were DENV-2 as 75.1% and 40.0% in 2005 and 2012, respectively. DENV-1 was
14
predominant during 2006-2009 and 2011-2012 as 80.0%, 97.3%, 50.0%, 48.1%, 97.5%
and 40.0%, respectively. While in 2010, we found only serotype DENV-3. Moreover, we
detected predominant serotypes with equally percentage in 2009 (DENV-1 and DENV-3)
and in 2012 (DENV-1 and DENV-2) (Figure 3D).
Figure 3: The pattern of dengue serotypes by province, (A) Chiangmai province,
(B) Lamphun province (C) Lampang province and (D) Mae Hong Son province
(A) Chiangmai province
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
2003
n=42
2004
n=98
2005
n=75
2006
n=51
DENV-1
2007
n=39
DENV-2
2008
n=47
2009
n=24
DENV-3
2010
n=48
2011
n=20
2012
n=50
DENV-4
(B) Lamphun province
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
2004
n=20
2005
n=34
DENV-1
2006
n=9
DENV-2
2007
n=21
2008
n=21
DENV-3
2009
n=24
2012
n=8
DENV-4
15
(C) Lampang province
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
2003
n=16
2004
n=29
2005
n=15
DENV-1
DENV-2
2006
n=7
2007
n=33
DENV-3
2011
n=5
DENV-4
(D) Mae Hong Son province
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
2005
n=12
2006
n=5
DENV-1
2007
n=33
2008
n=26
DENV-2
2009
n=27
DENV-3
2010
n=6
2011
n=40
2012
n=20
DENV-4
Discussion
Our study has shown the pattern of dengue serotypes over the 10-year period that was
determined from the seropositive acute samples from Chiangmai province, (the second
16
biggest city of Thailand) and its 3 neighboring provinces (Lamphun, Lampang and Mae Hong
Son) in northern highland areas.
Throughout the 10 years, the overall results of dengue serotypes circulation were
presented and all four serotypes were prevalent in this region in different proportion. The
pattern of predominant dengue serotype fluctuated circulating with a proportion of 44-81%
and was mainly switching between two serotypes of DENV-1 and DENV-2.
During the first period, from 2003 to 2005, our result of predominant serotype was
DENV-2 that differed from the previous study of Queen Sirikit National Institute of Child
Health (QSNICH), Bangkok, capital of Thailand during 2003-2005 and the study from
KhonKan province, Northeast region, Thailand in 2004 which indicated the predominance
of DENV-1.14-15 The annual epidemiological surveillance report of Thailand during 2004-2005
and the study from Kamphaeng Phet province, central region of Thailand in 2004 indicated
a predominance of DENV-4.4, 16
During the second period, from 2006 to 2009, the predominant serotype in the study
areas switched to DENV-1 that was also observed by the study of QSNICH from Bangkok13
and the study in children from Ratchaburi province, 100 km west of Bangkok.17 During 20102011, the predominant serotype changed back to DENV-2 like the studies in other regions
of Thailand.4, 14-15 Whereas, the report from South-East Asia countries in 2010; Brunei18 and
Cambodia, Republic of Lao, Malaysia, Philippines and Vietnam in 2011 showed predominant
DENV-1 except Singapore report (2011) was DENV-2.19 In 2012, DENV-1 was predominant
in this region as the report from Indonesia20 but the report from central region of Thailand
had still DENV-2 predominant.4 Our data was indicated the predominant serotype from
major outbreak in 2008 was DENV-1 and changed to DENV-2 when the next outbreak
occurred in 2010. Our data indicated the predominant serotype from major outbreak in
2008 was DENV-1 with a high dengue incidence rate4 as 199.34 and the rate was down to
99.39 in 2009. While it was changed to DENV-2 in the next outbreak 2010, the rate was the
highest as 303.37 and down to 35.26 in 2011. Moreover, the rate in 2012 was increasing to
81.33 and predominant serotype was changed back to DENV-1. We therefore considered
the proportion of other serotypes, DENV-4 was mostly at low levels but trend to increase
proportion when DENV-2 was displaced to DENV-1 during 2005-2007. Moreover, the
proportion of DENV-3 in the last 5 years of study were higher rate than in the first 5 years
that also likely the QSNICH report.13
We compared the pattern of dengue serotype in each province. The predominant
serotype in Chiangmai province during 10 years were mostly shown as the overall result of four
provinces. This is also seen in the data of four years in Lamphun province (2004, 2007–2008
and 2012), the data of three years in Lampang province (2003, 2006 and 2011) and the
data of seven years in Mae Hong Son province (2005–2009, and 2011–2012). Whereas, the
predominant serotypes in some provinces and years were found differently from neighbouring
area with temporal serotype such as DENV-4 in Lamphun province (2005–2006), DENV-2
in Lampang province (2007) and DENV-3 in Mae Hong Son province (2010).
17
Our study has surveyed long-term dengue serotype circulated in northern Thailand where
the incidence rate may differ from year to year. Our data presented here will not suggest that
dengue serotype DENV-1 and DENV-2, the most frequently detected serotypes, represented
the indigenous serotype in the northern region of Thailand, but also provided an update of
epidemiological hyperendemicity with multiple serotypes and its pattern. We agreed with the
previous study that the pattern of dengue serotypes in geographical locations in Thailand and
several South-East Asian countries is dynamic and there may have many factors associated
with these dynamic changes such as human and vector population in terms of the number
and their movement, environment, social factor and public health infrastructure.15, 21 This
study will provide data to the activity of the dengue surveillance, prevention and control
programmes including the possible vaccine trial in the future.
Acknowledgements
The authors express their sincere thanks to Mr Bumroong Kongdee, former director and
Mr Terasak Suphachaiyakit, Director of Regional Medical Sciences Center 1 Chiangmai, for
their support.
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19
Estimation of the adjustment factor for hospitalized
clinical cases diagnosed and tested for dengue in
Madurai, Tamil Nadu (India)
Brij KishoreTyagi,a# Shanmugavel Karthiga,a Chellaswamy Vidya,a
Narendra K Arora,b Deoki Nandan,†c Yara A Halasa,d Jhansi Charles,e,f N Mohan,e
Poovazhagi Varadarajan,g T Mariappan,a P Philip Samuel,a R Paramasivan,a
S Vivek Adhish,c Mukul Gaba,b R T Porkaipandianh and Donald S Shepardd
Centre for Research in Medical Entomology, Indian Council of Medical Research (ICMR), No.4,
Sarojini Street, Chinna Chokkikulam, Madurai, Tamil Nadu, India.
a
International Clinical Epidemiology Network (INCLEN) Trust International, F-1/5 2nd floor, Okhla
Industrial Area Phase I, New Delhi-110020, India.
b
National Institute of Health and Family Welfare, Munirka, New Delhi-110067, India.
c
d
Brandeis University, Schneider Institutes for Health Policy, The Heller School, P.O. Box 549110,
Waltham, MA 02454-9110, USA.
Madurai Medical College, Madurai, Tamil Nadu, India.
e
The Tamil Nadu Dr. M.G.R. Medical University, Chennai, Tamil Nadu, India.
f
g
Institute of Child Health, Madras Medical College, Chennai, Tamil Nadu, India.
Department of Public Health and Preventive Medicine, Chennai, Tamil Nadu, India
h
Abstract
Dengue is a notifiable disease in India since 1996, with an annual average of 20 018 laboratory
confirmed cases reported between 2006 and 2012. However, the true magnitude of dengue
burden is poorly understood. A study was conducted to estimate the true number of clinically
diagnosed dengue cases in Madurai District, Tamil Nadu. A descriptive inventory was developed
on healthcare facilities treating and/or testing and laboratories testing dengue. The hospitals were
stratified by bed capacity and the laboratories by type of dengue tests performed. Numbers of
dengue cases clinically diagnosed, tested and confirmed for the years 2009–2011 were obtained
from the selected facilities and extrapolated to obtain a realistic estimate. Projected cases were
compared with the officially reported numbers to highlight possible missing cases of dengue. The
average projected number of clinically diagnosed dengue cases referred to laboratory for testing
was 6334 whereas that of hospitalized confirmed dengue cases accounted for 2188. Ironically, for
the same period, the average number of reported dengue cases for the district was 134 and for
the 126 state. This gives an adjustment factor of 16.29 at the district level and 17.41 at the state
#
E-mail: : bk_tyagi@sify.com, crmeicmr@icmr.org.in
20
Estimation of the adjustment factor for hospitalized clinical cases diagnosed and tested for dengue
in Madurai, Tamil Nadu (India)
level for confirmed dengue cases, and 47.15 at the district level and 50.40 at the state level for
clinically diagnosed dengue cases laboratory tested cases.Under-representation of dengue cases in
India is a serious handicap in determining the realistic disease burden and thereby also hindering
in proper planning and executing the health delivery system effectively.
Keywords: Dengue; Disease surveillance; Adjustment factor.
Introduction
Dengue infection (DI), transmitted by Aedes mosquitoes, is a rapidly emerging arboviral
infection and a major public health concern globally with a 30-fold increase during past five
decades.1,2 Worldwide, an estimated 3.6 billion people (50% of the world population), living
in more than 125 dengue-endemic countries, are at risk of infection whereas countries in
Asia-Pacific regions alone bear nearly 75% of global burden.1-4 India reported its first dengue
case in 19465, followed soon by a disease epidemic in Calcutta and other east-coastal towns
of India in 1963-1964.6-8 Ever since the dengue incidence has been showing an upward
trend as between 2006 and 2012, India reported a total of 143 321 dengue cases and 923
deaths.9 Presently dengue fever is endemic in 34 States/Union territories (UTs); the only
exception being Lakshadweep. About 68% of the dengue burden is contributed by States
in the north and south regions.
WHO has categorised countries based on the dengue transmission potential; until 2009,
India was in Category B (micro level). However, in 2010, WHO revisited its categorization and
grouped India in Category A (macro level) countries where dengue is a major public health
problem with a leading cause of hospitalization and death among children. Interestingly, once
considered an urban infection, dengue with all the four serotypes has lately been reported
appreciably from rural environments.10
In India, dengue surveillance was a component of national disease specific health
programmes till 1997. In order to strengthen the disease surveillance activities, National
Surveillance Programme for Communicable Diseases (NSPCD), operative in 101 districts in
all States/UTs 11, 12 was established in 1997 by the Government of India to predict outbreaks.
In 2000, the percentage of under-reporting for vector-borne disease mortality was estimated
by comparing the reported national data with WHO estimated mortality. The comparison
found that nearly 99.8% of dengue mortality was missed from reporting in the surveillance
system.13-15 A study on the dengue epidemic in Chennai in 2001 indicated that the present
surveillance system in India is unlikely to generate proper information on epidemiology of
dengue, hampering the design of the prevention and control measures against dengue.16
Therefore, the Government of India launched an Integrated Disease Surveillance Project
(IDSP) in 200417,18 to integrate and strengthen the disease surveillance in the country to
detect early warning signals and use them for effective public health action in disease
21
control and management.18 To reach this objective the IDSP identified and established 347
Sentinel Surveillance Hospitals (SSH) with full-fledged laboratories and 14 Apex Referral
Laboratories for augmentation of diagnostic facilities for dengue.17 The IDSP was established
in Tamil Nadu in 2005 with 21 SSHs and 9 Zonal Entomological Teams (ZETs)17 that report
to the district surveillance unit from where first to the state surveillance unit and finally to
the central surveillance unit. Diagnostic test kits for screening dengue were provided to all
SSHs and ZETs by the GoI through National Institute of Virology, Pune.17
While the sentinel disease surveillance programme in India covers all the villages, districts/
zones in States/UTs19 through network of SSHs linked to referral laboratories, actual coverage
is low partly because healthcare practitioners and hospitals are not legally required to report
dengue cases.20 Moreover, variation in dengue testing, poor diagnostic facilities, misdiagnosis,
and the absence of feedback to medical practitioners also contribute to under-reporting of
dengue.21-25 In the Americas and South-East Asia, researchers have estimated the true dengue
burden by extrapolating from cohort studies with active surveillance.26,27 However, we are not
aware of comparable cohort studies and projections in India. Therefore, to address this gap
in knowledge a study was conducted in Madurai district, Tamil Nadu (India) as a component
of a multi-institutional research project aiming to estimate the economic burden of dengue
in India (2012 population 1260 Millions)28 based on hospitalized clinically-diagnosed and
laboratory confirmed dengue cases. The current pilot study is the first to our knowledge that
seeks to derive an adjustment factor to adjust for the under-reporting of dengue in India.
The pilot study was located at Madurai district in Tamil Nadu state for three reasons: (1) its
established dengue surveillance system compared to other states in India, (2) between 2006
and 2012, Tamil Nadu reported 14% of the total dengue cases in India (20 164/143 321), and
(3) due to the endemicity of dengue, we believe, the health work force is better informed
and familiar with dengue compared to other states. The annual average number of dengue
cases reported (126) at Madurai was found comparable with the average of other health
districts (125) at state level.
Methods
A descriptive inventory was prepared of all healthcare facilities or laboratories treating or
testing dengue patients in the district based on data inculcated from Madurai Corporation,
Indian Medical Association (IMA), and Madurai Laboratory Association. Healthcare units
were classified by sector, into private and public based on their statutory ownership. All
healthcare units were also classified by setting into ambulatory facilities and hospitals. The
public sector was further classified based on administrative set up (Taluk/Non-Taluk) and its
healthcare system (rural and urban). Private hospitals were stratified according to their bed
capacity into three groups: (i) small (1 to 50 beds), (ii) moderate (51 to 100 beds), (iii) and
large (more than 100 beds). Private laboratories were classified by type of dengue test they
performed.
22
Sample for each stratum
Madurai Medical College (MMC) acts as the public apex reference laboratory and nodal
unit for all governmental healthcare units in Madurai. For the public hospital, the laboratory
of MMC was selected as the main source to obtain the number of dengue tests performed
at a public sector, including the number of hospitalized clinically-diagnosed dengue cases
tested for dengue for the years 2009–11.
A sample size of 10% (22/224) of small private hospitals with bed strength between
1 and 50 was adopted following the systematic random procedure, whereas for mediumsized private hospitals with bed strength of 51–100, a sample of 40% (4/10) was selected.
As to the larger hospitals with bed strength over 100 beds, a systematic sample of 71% (5/7)
was selected. As this design sampled most of the larger hospitals, it managed to capture 5 out
of the 6 (83%) sentinel sites, the official government sentinel surveillance hospital (Madurai
Medical College) and four out of the five sentinel private hospitals/practitioners reporting to
the district surveillance unit.
A total of 126 private laboratories in Madurai have the capability to test for dengue in
Madurai, of which 85 use rapid card test (RCT) and 21 use enzyme-linked immunosorbent
assay (ELISA). To understand the dengue dynamics at the private laboratories, a sample of
four of these laboratories were selected, in which three used the ELISA test and one used
the RCT. We obtained the number of cases tested for dengue and confirmed dengue cases,
by the type of test performed, the sources of patients’ referral (ambulatory, hospitals, other
labs), and number of providers in each referral category. Data obtained from the private
laboratories were used to adjust for the number of clinically diagnosed, hospitalized-dengue
cases tested for dengue in the public and private sectors.
Data collection tool
A self-structured standardized questionnaire was developed to collect the number of clinically
diagnosed cases tested for dengue and confirmed dengue cases by month and year, and
number of deaths due to dengue from January 2009 through December 2011, and hospital
statistics such as number of beds and volume of services provided for the study years 2009
through 2011.
Data collection procedure
The questionnaire was shared with the selected hospitals. They reviewed the questionnaire
and agreed to collaborate with the study by providing data from the microbiology department
for the number of dengue cases tested, and from the medical record department through the
death registry to capture death due to dengue. For the public hospital and 6 out of the 15
private hospitals, data were retrospectively collected on the number of clinically diagnosed
23
hospitalized dengue cases laboratory tested for dengue and confirmed dengue cases from the
microbiology department laboratory. Additionally the number of beds, number of inpatients
and outpatients visits were collected from human resource department, along with the number
of deaths due to dengue from the death registry in the medical record department. One
private hospital, with computerized record provided the information directly by retrieving
the information from the admissions made in the medical records of the microbiology
department. For the remaining eight private hospitals, laboratory technicians collected the
number of hospitalized dengue cases tested for dengue and laboratory confirmed cases from
the microbiology department, while personnel from the public relations or human resources
collected other hospital statistics. Simultaneously, a sample of patients was collected from
the list provided by the microbiology department and confirmed the demographic details of
patients from the medical records department. For public health facilities, the required data
was collected from the microbiology department of MMC, Govt. Emergency and Obstetric
Care (EOC) inpatient unit (1 out of 2) and Govt. Railway Hospital, Madurai.
Analyses
The numbers of dengue cases from our sampled hospitals were extrapolated by stratum
based on the ratio of cases to total beds in the sampled facilities to beds for all hospitals by
stratum. We added the number of dengue cases according to sector and compared it with
the officially reported numbers from the district surveillance unit (DSU), and the officially
reported numbers from the state surveillance unit (SSU).
To get an adjustment factor for clinically diagnosed hospitalized tested dengue cases at
the district and state level we divided the average number of clinically diagnosed hospitalized
tested dengue cases for the years 2009-2011 by the average number of reported dengue
cases for the year 2009-2011based on the formula given below:
Adjustment factor=
Best estimate of the number of cases of
dengue illness in a specified population in one year
Number of reported cases considered for
denuge in that population in one year
We conducted sub-analyses to compute the adjustment factor by using certain parameters
namely (i) by setting, i.e., hospital and diagnostic facilities, (ii) by sector, i.e., public and
private, and (iii) by year, i.e., hospitalised dengue cases recorded between 2009 and 2011.
This study is based on empirical ratio evolved from reviewing hospitals and laboratory data
after subjecting them to necessary statistical treatment, and accordingly was derived by
dividing the number of reported dengue cases by the best estimated number of laboratory
confirmed hospitalised dengue cases collected for the purpose of this study. This extrapolation
model aims to provide primarily an adjustment factor for commensurate estimation of disease
burden in other settings as well.
24
Results
The overall response rate for private hospitals was 48.39% (15/31). Of the 22 randomly
selected small hospitals (1-50 beds) only 7 (32%) provided the needed information, while
6 (40%) did not have the appropriate records to extract the needed data, 3 (20%) declined
to participate in the study, 2 (13%) reported dengue as a febrile illness only, 2 (13%) referred
the clinically suspicious dengue cases to multi-specialty hospital, and 2 (13%) could not be
traced as they had shifted to other places in the city or closed. The response rate among
medium private hospitals (51-100 beds) was 100% (4 out of 4) whereas the response rate
was 80% (4 out of 5) for the large private hospitals (>100 beds). The fifth hospital failed to
offer appropriate records to extract the needed data.
The average projected number of hospitalizedclinically diagnosed dengue cases referred
to a microbiology department for test was 6334 of which 17.32% (1097/6334) came from
the public sector and 82.68% (5237/6334) from the private sector. Table 1 presents the
results for the years 2009-2011.
The average projected number of hospitalized confirmed dengue cases was 2188 of
which 11.75% (257/2 188) came from the public sector and 88.25% (1931/2188) from the
private sector. Table 2 presents the results for the years 2009-2011.
For the same period, the average number of reported dengue cases at the district level
was 134 cases, and at the state level were 126 cases as presented in Table 3. This gives
an adjustment factor of 47.15 at the district level, and 50.40 at the state level for clinically
diagnosed dengue cases laboratory tested for dengue and 16.29 at the district level and 17.41
at the state level, for confirmed dengue cases. The reporting rate was 6.14% (134/2188) for
confirmed cases at the district level and 5.76% (126/2188) at the state level. The reporting
Table 1: Adjusted number of hospitalized clinically diagnosed dengue cases tested for
dengue in Madurai, 2009–2011
Clinically diagnosed hospitalized
dengue cases tested for dengue
2009
2010
2011
Average
2009–2011
Public Hospitals
780
1716
796
1097
Private Hospitals
3921
7418
4371
5237
1-50 beds
1730
4758
3172
3220
537
755
59
450
1654
1905
1140
1566
4701
9134
5166
6334
51-100 beds
More than 100 beds
Total
25
Table 2: Adjusted number of laboratory confirmed hospitalized dengue cases in Madurai,
2009–2011
Laboratory confirmed hospitalized
dengue cases
Average
2009–2011
2009
2010
2011
Public Hospitals
234
476
62
257
Private Hospitals
1688
2768
1337
1931
1211
2153
1020
1461
51-100 beds
129
120
16
88
More than 100 beds
348
495
302
382
1922
3243
1400
2188
1-50 beds
Total
rate was 2.12% (134/6334) for clinically diagnosed dengue cases laboratory tested for dengue
at the district level and 1.98% (126/6334) at the state level. The number of reported dengue
cases compared to adjusted clinically diagnosed hospitalized laboratory tested dengue cases,
and adjusted number of laboratory confirmed cases compared to the reported dengue cases
at district and state levels is illustrated in Figure 1.
The adjustment factor for hospitalised confirmed cases for the private sector was 40.23
(1931/48) and for the public sector was 2.99 (257/86), indicating a 33.46% (86/257)reporting
rate for the public sector, and 2.49 % (48/1 931) for the private sector. Year-wise, the
adjustment factors for Madurai district were 12.99 (2009), 15.15(2010) and 34.15 (2011).
Table 3: Reported dengue cases at IDSP-Madurai district and state surveillance unit
[DPH (TN)] for Madurai district
Reported dengue cases
2009
2010
2011
Average
2009–2011
IDSP Reported dengue cases:
Madurai
148
214
41
134
Public Hospital
73
146
40
86
Private Hospital
75
68
1
48
1–50 beds
1
5
0
2
51–100 beds
0
0
0
0
74
63
1
46
120
214
43
126
More than 100 beds
DPH (TN) Reported dengue
cases for Madurai
26
Adjustment
Factor
16.29
17.41
Figure 1: A comparison of DPH (TN) reported dengue cases with the estimated clinically
diagnosed hospitalized dengue cases tested for dengue and the estimated confirmed
dengue cases for Madurai, 2009–2011
7000
6334
Number of Cases
6000
5000
4000
3000
2188
2000
1000
126
134
0
DPH TN Reported
dengue cases for
Madurai
IDSP Reported dengue Adjusted hospitalized
cases at district level confirmed dengue cases
Adjusted clinically
diagnosed hospitalized
dengue cases tested for
dengue
Between 2009 and 2011, the IDSP surveillance system at Madurai district reported on
average 134 dengue cases, of which 64% were reported from the government sector and
remaining 36% from the private sector. No dengue deaths were reported by the surveillance
system of the study district from either public or private sector in 2009-2011 (unpublished
data collected from Madurai district’s IDSP cell, Deputy Directorate of Health Services, 2012).
The coverage of healthcare strata by the Madurai district surveillance system is presented in
Figure 2. It clearly indicates the exclusion of private health care facilities from the reporting
system. Also, none of the small and medium healthcare units, which mainly depend on the
private laboratories for screening dengue, were covered under district surveillance reporting
system.
Discussion
Since independence, by implementing various national policies and programmes, India has
prioritized strengthening the public healthcare services through improving public facilities
and appointing a large number of healthcare professionals. In 2005, the National Rural
Health Mission (2005–2012) was launched by Government of India in 18 States, mainly to
improve the effectiveness of quality care to rural population. Though the chain of healthcare
delivery system in India seems well designed, only 20% of the population utilizes public
27
Figure 2: Coverage of healthcare stratum by the IDSP surveillance system in Madurai,
2009–2011
Number of Laboratory Confirmed dengue cases
220
200
2009
180
2010
160
2011
140
120
100
80
60
40
20
0
1-50 beds
Total
Public Hospital
51-100 beds
More than
100 beds
Private Hospital
Hospital Stratum
services. Approximately 80% of healthcare needs are still being met by the private sector due
to dissatisfaction with quality of services at public hospitals, which means that about 80% of
healthcare information is available in the private sector is neither included nor regulated.29-31
According to National Family Health Survey30, private sector plays a prime role in the last
25 years in catering the health needs in both rural (63%) and urban areas (70%) in India, in
which about 46% of urban and 36% of rural households are approaching private doctors/
clinics while private hospitals are second most common sources in private sector. Though
the Indian healthcare delivery system is highly dominated by the private sector with around
70% of total market share, but their inclusion in the dengue surveillance system in India was
limited.30 In this study it was found that the dengue epidemiological data relies mostly on
the public sentinel units and a few major private hospitals and as consequences, the cases
that dealt and treated by the private sector/ laboratories are not included for reporting which
would lead to under-representation of overall dengue cases and deaths of study district.
Under IDSP framework, it was emphasized that at least 15 urban laboratories and 15
private practitioners/hospitals would be included per district under surveillance.32 In this
28
study with regard to private sector, it was found that only 2.08% of private hospitals were
included in the surveillance and observed a high level of under-reporting especially complete
exclusion of dengue cases treated at private clinics, in both small and moderate healthcare
units. Medical practitioners in private clinics and small healthcare units do not have diagnostic
facilities for screening dengue but they utilize the services of private laboratories. All the
laboratories and private hospitals who are utilizing the services of private laboratories are not
covered under surveillance system, leading to enormous under-reporting of dengue cases
and perhaps of dengue deaths. In order to organize and execute an effective dengue case
management quick and timely reporting should be encouraged at all levels of healthcare
facilities in both public and private sectors.33
This study has helped to document the fact that dengue reporting varies not only between
public and private facilities, but also among public facilities. For example, a variation was
observed in government sentinel units between the proportions of dengue cases confirmed by
laboratory at public hospitals and number of cases reported in district surveillance system. As
an apex laboratory, MMC was receiving suspected serum samples from its adjoining districts
and often cases were also treated at city government hospitals. Therefore, a strong network
should be developed between the district surveillance units in recording, monitoring and
follow ups of those cases. Though the Madurai Railway Hospital is a government institution,
it instituted the screening test for dengue only in 2009.
Laboratory confirmation improves the specificity of surveillance.34 As per the Government
of India‘s guidelines on dengue treatment, Mac-Elisa is prescribed for the confirmatory
test for dengue infection. However, many private laboratories and hospitals are detecting
dengue through RCT. Dengue confirmation based on rapid diagnostic assays have not been
considered as confirmed dengue cases as per the government surveillance system (IDSP),
which contributes to understating the real number of dengue cases and deaths and having
timely information for reducing disease transmission.
Our study has several limitations, especially the limited number of facilities studied which
treat ambulatory dengue cases. Another likely limitation is the absence of testing of some
hospitalized dengue patients. Our study focuses only on clinically diagnosed dengue cases
hospitalized and tested for dengue.
In summary, this study is the first to our knowledge that used facility-based data to better
understand the true burden of dengue in India. To obtain the overall number of hospitalized
dengue cases, we need to include those who were hospitalized but not tested. To obtain the
total number of symptomatic dengue cases, the number treated in the ambulatory setting
must also be estimated. A companion paper presents these extensions, estimating 11 975
hospitalized cases, 24 312 ambulatory cases and 36 287 total clinical cases. These imply an
adjustment factor of 281 relating total symptomatic dengue cases to reported dengue cases.35
As dengue varies by region and by year, it would be helpful to replicate this approach across
other districts of India.
29
Acknowledgements
The authors are thankful to Dr V.M. Katoch, Secretary, Government of India and Director
General, Indian Council of Medical Research, New Delhi for permission and encouragement.
Authors are also thankful to the various medical and healthcare institutions in Madurai and
to the District and State health authorities for their support and interactive discussions on
this study. They are also thankful to all the staff at CRME for their contributions in completion
of this study.
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Med & Hygiene. 2014;91(6):1235-42. doi:10.4269/ajtmh.14-0002. http://www.ajtmh.org/content/
early/2014/10/02/ ajtmh.14-0002.full.pdf - accessed 18 December 2014.
32
Dengue vectors survey at Punjab University, Lahore,
Pakistan, January 2012 – April 2014
Muhammad Saeed Akhtara,#, Ayesha Aithetashama, Mehwish Iqtedarb,
Nasim Beguma and Muhammad Akhtara
a
Department of Zoology, University of the Punjab, P.O. Box No.54590, Lahore, Pakistan
Department of Biotechnology and Microbiology Lahore College University for Women,
Lahore, Pakistan
b
Abstract
During the period (January 2012-April 2014), 13 positive samples of dengue larvae (per 200 ml
of water) were recovered from different sites of Punjab University. Aedes albopictus larvae were
more common (59.1%0) than Ae. aegypti (40.9%). More larvae were recovered in September (51)
as compared to October (7) and November (10) during 2012. In 2013, however, more larvae of
dengue collected in July (35) as compared to August (18) and September (6), and started appearing
in the samples earlier than 2012. The adults of dengue (recovered by CDC aspirator appeared
much earlier in 2014 (i.e., March and April) than 2013 (June and July) and 2012 (August and
September). In Pakistan dengue vector species are spreading their tentacles to cooler span of the
year and colder parts of Pakistan. For example, record of Dengue cases in 2013 from Swat, a
cooler locality in Pakistan.
Keywords: Dengue vectors; survey; Lahore; Pakistan.
Introduction
Dengue fever surfaced in Pakistan and particularly in Punjab, Lahore very strongly infecting
21 292 humans and killing 354 during 2011. Since then the Government of Punjab and
different Universities/Departments have organized themselves to combat the disease and to
exterminate the vectors. But the dengue vectors have stayed for a long time wherever they
entered, posing a constant threat to the public. For example, for nearly 60 years, dengue
was eradicated from the United States with the onset of mosquito combat spraying and
prevention campaigns. But since 2001, outbreaks in Hawaii, Texas and Florida’s Key West
have signaled its return1.
#
E-mail: msakhtarch@yahoo.com
33
Dengue vectors survey at Punjab University, Lahore, Pakistan, January 2012 – April 2014
In 2013, dengue fevers out breaks were reported from various areas of Pakistan. A severe
Dengue outbreak confronted District Swat Khyber Pakhtunkhwa province, and from 7th
August to 19th September, a total of 5194 Dengue fever cases and 14 deaths were reported.
Fifteen samples tested at NIH revealed that three types of virus (DNV-1, DNV-2, DNV-3)
were detected in different patients from Swat2.
Ae. aegypti is highly anthropophilic species and often resides in and near human
dwellings, preferentially feeding on humans3,4. After dengue outbreak in Lahore in 2011,
regular monitoring of both larvae and adults is being carried out. In spite of preventive control
measures in Punjab University area, Dengue vectors in addition to other Culex species stayed
in the area and were recovered in samples. In the present report only Dengue vectors larvae
and adults are discussed and not the other Culex species which are far more abundant,
but are not transmitting diseases at the moment except invading houses for blood feeding
exclusively at night on humans.
Larvae
The studies involved collection of mosquito larvae from reservoirs and containers with
water because of rain or negligence of humans. If reservoir or container was positive for
the presence of larvae, a sample of 200 ml jar was taken and species identified using WHO
guidelines. Water reservoirs were water tanks dug up in the ground (4 feet wide and 5 feet
deep), basically developed for experiments on snails. Later on, they were abandoned, and
became the abode of mosquitoes. The second types of water reservoirs were drains to irrigate
surrounding lawns with tube well water. When the drains were not used for irrigation, the
stagnant water was the breeding site for mosquitoes. The containers were dishes of flowers
pots, coal tar drums, desert coolers, tree holes, and tyres. The day one type of container
was positive for larvae, the total number of containers of that nature examined for that day
were considered for container Index (CI), which was worked out as the percentage of water
holding containers with larvae.
Adults
Adult mosquitoes were collected from student hostels, teachers’ residences and their surroundings from July to December 2012 using CDC aspirator. The collection effort for
each sample was fixed (10 minutes).
The data were statistically analyzed for Correlation using “Graph Pad Prism version 5.00
for Windows, Graph Pad Software, San Diego California USA, www.graphpad.com”.
34
Results
Table 1 gives details of dengue vector larvae recovered in 13 positive samples of 200 ml each
from sewer free water sources from different departments, hostels, tyres, flower pots etc.,
of Punjab University area. In 2012, larvae were recorded from September onwards up to
13 November 2012. In 2013, larvae were recovered slightly earlier, i.e., from 17 July 2013
and up to 30 September 2013 (Figure 1).
Table 1: Dengue vector larvae (under different temperature and humidity conditions)
recovered from Punjab University (Quaid-e-Azam) campus in 200 ml sample,
during 2012 to 2014
Aedes
albopictus
Temperature
(°C)
Humidity
(%)
11.9.2012 (Zoology Depart. Tank 2)
2
34.5
78
13.9.2012 (School of Biological Sciences)
31
35.0
79
36.0
79
10
29.6
88
1
33.5
71
27.0
71
Date and Locality
14.9.2012 (P.U.Town II)
Aedes
aegypti
8
19.9.2012 (English Depart.)
9.10.2012 (Hostel No 4)
2
9.10.2012 (Hostel No. 9)
4
12.11.2012 (Girls Hostel No.1)
4
27.0
84
13.11.2012 (Girls Hostel No.6)
6
25.8
89
17.7.13 University Executive club, From
Tree hole in Alstonia
15
31.5
69
24.7.13 Outside Controller of
Examination, From Tyre
20
22.8.18 Department of Botany, from
Flower pot
18
35.4
96
35
53
30.9.2013 Jogging Track
3
33.6
62
30.9.2013 (Hostel No 4)
3
33.6
62
Total
52
75
*No larvae of Dengue vectors were collected from University area up to May 8, 2014
Correlation coefficient between:
No. of Larvae of Ae. aegypti vs. Temperature
(r=0.389; P >.05; d.f.3; N.S.) vs. Humidity (r= 0.165; P>.05; d.f.3; N.S.)
No. of Larvae of Ae. albopictus vs. Temperature
(r=0.205; P >.05; d.f.7;.N.S.) vs. Humidity (r=0.188; P >.05; d.f.7;N.S.)
35
Figure 1: Dengue vector larvae recovered from Punjab University (Quaid-e-Azam)
campus in 200ml sample, during 2012 to 2014
60
2012
Number of Larvae
51
40
2013
35
18
20
6 7
0
Jan Feb Mar Apr May Jun Jul
10
Aug Sep Oct Nov
Months
Table 2 shows the type of water reservoirs/containers examined for the presence of larvae.
As only the number of containers examined for the day when containers of that type were
positive were considered, CI is very high in some cases. For example, for tyres, the CI is 50.
The overall CI, however, was 11.11.
Table 2: Number with container index (CI) the percentage of water-holding
containers larvae
Containers/ water sources/
reservoirs
No. examined
No. infested
Container index
(CI)
Water tanks in soil
8
1
12.5
Dishes of flower plants
14
1
7.14
Coal Tar drums
6
1
16.66
Desert Coolers
41
4
9.75
No. of tree holes
20
1
5.0
Drains with standing water
6
1
16.16
Tyres
4
2
50.0
Total
99
11
11.11
36
In 2012, only one dengue fever patient was reported from boy’s hostel and the patient
recovered after treatment. In 2013, twenty one suspected cases of dengue fever were
registered in Punjab University Health Centre. Out of these, 7 cases were referred to Shaukat
Khanum Memorial Hospital for confirmation. All these patients received treatment from the
Health centre and recovered. As far as abundance of dengue larvae is concerned (Table 3)
larvae of Ae. albopictus were more abundant (59.1%) than Ae. aegypti (40.9%).
Table 3: Abundance of dengue larvae* from clean water sources/ containers from Punjab
University Lahore. (Data based on 13 positive samples of 200 ml each)
Species
No. of specimens
Percentage of total
Ae. aegypti
52
40.9
Ae.albopictus
75
59.1
*larvae of culex species recovered along with dengue larvae are not described in the present report, but they were
highly abundant.
The adults were collected with help of CDC aspirator with a collection effort of 10 minutes
for each sample. The details are submitted in Table 4. During 2012, adults of dengue vectors
were recovered from August to December and were more abundant (Figure 2) in October
(recovered 29 adults). In 2013, dengue adults started appearing in the samples from 19.6.13
and samples were positive up to 11.11.13. Dengue adults (mostly Ae. albopictus) expanded.
Figure 2: Number of dengue adults collected from August 2012 to May 2014 from
Punjab University with the help of CDC aspirator
Number of adults
40
2012
2014
20
20
10
4
0
2013
29
30
0
1
2
3
2
4
2 1
5
6
7
7
4
2
1
8
9
2
4
1
10 11 12
Months
37
Table 4: Number of dengue adults collected from August 2012 to May 2014
from Punjab University using CDC aspirator
Months
A. aegypti A. albopictus
23.8. 2012 Jogging Track
1
Temperature Humidity at
(°C)
5.00 P.M.
28.4
62
35
64
13.9.2012 School of Biological Sciences
3
25.9.2012 Department of Zoology
2
1
34.8
42
01.10.2012 Sport Ground
4
6
35.3
41
3
35.4
44
1
33.5
41
6
29
50
02.10.2012 Sport Ground
09.10.2012 Hostel No. 4
2
11
05.11.2012 Hostel No. 9
1
12.11.2012 Girls Hostel No. 1
3
29.5
51
29.7
73
27
43
1
22.6
42
1
39.2
53
1
39.2
52
1
35.5
96
1
37.2
51
01.08.2013 Computer Lab
1
37.2
51
1
35.2
67
1
34.8
66
21.8.2013 Department of Physics
8
32.3
62
22.8.2013 Department of botany
7
35
57
1
34.4
62
14.9.2013 Department of zoology
1
34.5
78
30.9.2013 Jogging track
3
37.7
44
30.9.2013 Botanical garden
3
37.7
45
1
29.6
54
26.2
44*
1
11.11.2013 School of Biological sciences
2
18.3.2014 Department of Botany
02
01
10.4.2014 I.E.R School
01
15.4.2014 Girls Hostel No. 7
01
Total
10
68
*Correlation coefficient was worked out for data of only 2012 to 2013:
No. of adults of Ae. aegypti vs. Temperature (r=0..603; P>.05; d.f. 5; N.S.) v.s. Humidity (r=-0.209; P>.05; d.f. 5; N.S,).
No. of adults of Ae. albopictus vs. Temperature (r=-0.185; P> .05; d.f. 21; N.S.) vs. Humidity (r=-0.157; P>.05 ; d.f.
21; N.S.).
38
Their survival span to cooler months of the year and consequently dengue vectors
during 2014 were recovered in the samples much earlier, i.e., March-April 2014. Adults of
Ae albopictus (Table 5) were more abundant (87.18%) than Ae.aegypti (12.82%).
Table 5: Abundance of dengue adults in Punjab University area in 24 positive samples.
Species
No. of specimens
Percentage of total
Ae. aegypti
10
12.82
Ae.albopictus
68
87.18
*Adults of culex species recovered along with dengue adults are not described in the present report, but they were
highly abundant.
As regards relationship with temperature and humidity conditions, dengue adults and
for that matter dengue cases were more common from September to November, every year.
However, relationship of Ae. aegypti larvae with temperature and humidity was not significant
(r=0.389) and (r= 0.165), respectively. Similarly the relationship between the recoveries
of larvae of Ae. albopictus with temperature and humidity was insignificant (r=0.201),and
(r=0.188), respectively.
Availability of Dengue adults in the samples with respect to the temperature and humidity
was also considered. In general Dengue mosquitoes were rare during hot period of the year
(May and Mid-June, 2013) and also during cold winter. May 2014 was exceptionally cool
and comfortable but during 10–12 June 2014 temperature reached up to 48 °c in Lahore.
The samples revealed that dengue mosquitoes have evolved adaptability to slightly colder
part of the year and were available up till November 2013. The recovery of Ae. aegypti adults
at different temperature conditions of the dengue season showed weak and non significant
relationship with temperature (r=0.603) but negative and weak with humidity (r= -0.209).
The relationship of Ae. albopictus adults with temperature and humidity conditions was very
weak, negative and non significant ( r=-.185 ) and (r=–0.157 ), respectively.
Discussion
Dengue is the most common mosquito-borne viral disease in tropical and subtropical regions
of the world, and hence, dengue virus (DEN) is an emerging human pathogen of major
importance5. Dengue has also expanded its area of distribution and according to a new
estimate, 3.6 billion (55% of the world’s population) are at risk of dengue in 124 endemic
countries with an estimated 21 000 deaths every year6.
There is no community-based mosquito surveillance data available for Lahore and
particularly about Punjab University area. Data about a few localities of Lahore were published
in 2011 about House Index (HI) and were 4.16, 2.76, 2.32 for October, November and
December, respectively7. Dengue fever outbreaks have been reported from Pakistan in 1994,
39
1995, and19978,9 which indicates that dengue persisted at different times and in different
parts of the country. The histogram given below shows dengue status in different Provinces
of Pakistan. Up till 26 April 2014, there were 179 positive dengue cases in Sindh, four in
Punjab and Zero in KP2 (Figure 3).
Figure 3: Number of positive dengue fever cases by province (1 Jan to 26 Apr 2014)
Number of cases
200
179
150
100
50
0
0
Sindh
4
0
0
Punjab
KP
Balochistan
It is predicted that like 2013, dengue epidemic will spread in Khyber Pakhtunkhwa
and Punjab after migration of viremic people (mostly labourers) from Sindh to celebrate
Eid-ul-Fitr in their native towns in Khyber Pakhtunkhwa and Punjab, during July 2014.
Ae. aegepti infests urban habitats and breeds mostly in artificial container and is a primary
vector of dengue. Ae. albopictus, a secondary dengue vector in Asia, is highly adaptive and can
survive in cooler temperature regions of Europe. The Asian tiger mosquito can outcompete
and eradicate other species with similar breeding habits from the start of its dispersal to
other regions and biotopes, It is also known that Ae. albopictus can transmit pathogens and
viruses, such as West Nile Virus, Yellow fever virus, St. Louis encephalitis, dengue fever and
Chikungunya fever10. The Asian tiger mosquito was responsible for ckikungunya epidemic
on the French Island La Reunion in 2005–200611. By September 2006, there were estimated
266 000 people infected with the virus, and 248 fatalities on the Island 11. In Pakistan,
however, the Asian tiger mosquito has not been reported to transmit any other virus, so far.
Ae. albopictus has proven to be very difficult to suppress or to control due to their
remarkable ability to adapt to various environments, their close contact with humans, and
their reproductive biology. Recently (2013) in Pakistan, this mosquito expended its area of
distribution and a sort of epidemic in Swat demands serious consideration. The spread of Ae.
40
alobpictus is also due to its tolerance to temperature below freezing, hibernation, and ability
to shelter in microhabitats. As pointed in the results, dengue cases in Punjab are common
during September and October because of favourable temperature and humidity conditions.
Frequent rains during dengue season also promote breeding of the dengue mosquitoes.
Table 6: Summary of dengue cases
Number of cases
reported
Number of deaths
By November 2013*
1362 in Punjab
5 in Punjab
By November 2012**
261
Nil
21292
354
Year
By November 2011
*The Dawn, 9-11-2013; ** The News, 16-11-2012
The role of dengue vectors in spreading disease in various areas of Pakistan is shown in
Figure 3. As indicated in Table 6, after dengue epidemic in 2011 when 21 292 cases were
reported with 354 deaths, Government of Punjab and other research organizations started
monitoring population of dengue vectors. As a result there was a decline in dengue cases
in Punjab in 2012 to 2013. The exception was Swat area where 5194 cases were reported
and there were 14 deaths2. Dengue problem in Swat started with migration of labourers/
workers from Sindh to celebrate Eid-ul-Fitr in their native towns in Swat and suburbs. It is
also important to note that dengue vectors (especially Ae .albopictus) are expanding their
span of activity to cooler part of the year and cooler parts of Pakistan and they successfully
continued breeding in Swat which has a relatively temperate climate.
In Punjab University Health Centre, 21 suspected dengue fever cases were reported. Out
of these, seven patients were referred to the Shaukat Khanum Memorial Cancer Hospital
for confirmation. All these patients received the treatment and recovered. Thus, Punjab
witnessed considerable decrease in the number of dengue fever cases from 2011 to 2013,
as a result of organized control measures.
Conclusion
Very hot summer and very cold winter in Punjab restricts the breeding of dengue vectors.
There is, however, no definite relationship of availability of larvae and adults with temperature
and humidity. Frequent rains during dengue seasons (August to November) promote breeding
of dengue vectors. Preventive and chemical control measures organized by the Government
of the Punjab and other research organizations have to a considerable extent controlled the
surge of dengue vectors population from 2011–2013. But still there is a need to monitor
the population to completely eradicate dengue vectors from Punjab.
41
Acknowledgement
The authors are grateful to the Vice-Chancellor (Prof Dr. Mujahid Kamran) for providing
necessary facilities to accomplish the work.
References
[1] Sagastume P. Dengue fever presence in Florida at a pretty serious level. Aljazera America. 2013 Sep 12.
http://america.aljazeera.com/articles/2013/9/12/dengue-fever-presenceinfloridaataprettys eriouslevel.
html - accessed 18 December 2014.
[2] World Health Organization. Weekly Epidemiological Bulletin. 2014;5(17).
[3] Gubler DJ, Kuno G. Dengue and denue hemorrhagic fever. New York: CAB International,1997.
[4] Thavara U, Tawatsin A, Chansang C, Kong-ngamsuk W, Paosriwong S, Boon-Long J, Rongsriyam Y,
Komalamisra N. Larval occurrence, oviposition behavior and biting of potential mosquito vectors of
dengueon Samui Island, Thailand. J. Vector Ecol. 2001Dec;26(2):172-80.
[5] Gubler DJ. Epidemic dengue/dengue hemorrhagic fever as a public health, social and economic problem
in the 21st century. Trends Microbiol. 2002 Feb;10(2):100-3.
[6] Pediatric dengue vaccine initiative. Global Burdon of dengue. Kwanal http://www.pdvi.org/about_
dengue/GBO.asp - accessed 18 December 2014.
[7] Akhtar MS, Aihetasham A, Saeed M, Abbas G. Aedes survey following a dengue outbreak in Lahore,
Pakistan. Dengue Bulletin. 2012;36:87-93.
[8] Chan YC, Salahuddin NI, Khan J, Tan HC, Seah CL, Li J, et al. Dengue haemorrhagicfever outbreak in
Karachi, Pakistan. Trans R Soc Trop Med Hyg. 1995;89:619-20.
[9] Qureshi JA , Notta NJ, Salahuddin N, Zamman V, Khan JA. An epidemic of dengue fever in Karachiassociated clinical manifestations. J Pak Med Assoc. 1997 Jul;47(7):178-81. [10]Hochedez, P Jaureguiberry S, Debruyne M, Bossi P, Hausfater P, Brucker G, et al. Chikungunya infection
in travelers. Emerg Infect Dis. 2006 Oct;12(10): 1565-67. http://www.ncbi.nlm.nih.gov/pmc/ articles/
PMC3290953/ - accessed 18 December 2014.
[11]Flauhaut A. Chikunguna—Indian Ocean update (32). ProMED. 2006 Oct 14. archive no.
20061014.20062953. http://www.promedmail.org - accessed 18 December 2014.
42
Trends in dengue during the periods 2002–2004
and 2010–2012 in a tertiary care setting in
Trivandrum, Kerala, India
Henna ASa, Ijas Ahmed Ka, Harilal SLa, Saritha Na,
Ramani BaiJ Ta, Zinia T Nujuma#,
a
Medical College, Thiruvananthapuram, Kerala, India
Abstract
Dengue has become one of the major public health concerns in recent years. Kerala is now
hyperendemic for dengue. Over the past 10–15 years, next to diarrhoeal disease and acute
respiratory infections, dengue has become a leading cause of hospitalisation and deaths. This study
was done to compare the trends in the proportionate positivity of dengue among samples tested
for dengue IgM during the periods 2002–2004 and 2010–2012 in the Microbiology Department,
Government Medical College, Thiruvananthapuram, to look for seasonality and to find age-sex
characteristics of the disease during these periods. A descriptive study was done from the records
of the Microbiology department, Government Medical College, Thiruvananthapuram. All those
patients with clinically suspected dengue whose blood samples were sent to the microbiology
department during the period 2002–2004 and 2010–2012 were studied. 10 064 samples were
tested over a period of 6 years (2002–2004 & 2010–2012). Out of these, 3334 samples were
positive for dengue (33.1%). When compared to 2002–2004 period, there’s a significant increase
in dengue positivity for the period 2010–2012 (23.7% v/s 35.8%; p value<0.001).Mean age of
study population was 27.05 years (standard deviation-19). Mean age of positive dengue was
significantly higher during the period 2010–2012 (27.58) when compared to 2002–2004 (24.42)
with p value <0.001. The proportionate dengue positivity among females (34.1%) was higher than
males (32.3%). However, among the total 3334 positive cases, 1808 cases (54.2%) were males.
A higher increase in the proportionate positivity of dengue was seen among females from 24.2% in
2002–2004 to 36.7% in 2010–2012 (12.5%) when compared to the increase from 23.2% to 35.1%
in males (11.9%). Dengue positivity was higher during the months June, July and August (22.6%,
16.2%, and 10.9% respectively). No difference in seasonality was seen across years. There is a rise
in dengue positivity over the years and the age of occurrence has also increased. Pre-monsoon
activities should be strengthened to reduce the incidence of dengue.
Keywords: Dengue; Proportionate positivity of dengue; Seasonality; Thiruvananthapuram; Kerala.
#
E-mail: drzinia@gmail.com
43
Trends in dengue during the periods 2002–2004 and 2010–2012 in a tertiary care setting in Trivandrum, Kerala, India
Introduction
Dengue is one of the most serious and rapidly emerging tropical mosquito-borne diseases.
In 2012, dengue ranks as the most important mosquito-borne viral disease in the world1.
The global disease burden is 465 000 Disability adjusted life years (DALYs), which is only
paralleled by that of malaria among mosquito-borne diseases 2. Worldwide, approximately
2.5–3 billion people (40% of the global population) live in constant risk of contracting
this infection. It was estimated that 50 million cases and 24 000 deaths occur annually
in 100 endemic countries worldwide. Nearly 500 000 cases are hospitalized annually, of
which 90% are children. The south-east Asia region contributes 52% of the cases annually
3
. Using cartographic approaches, the annual estimate has been shown to be 390 million
(95% credible interval 284–528) dengue infections per year, of which 96 million (67–136)
manifest apparently 4.India is one of the seven identified countries in this region that regularly
reports dengue fever/dengue hemorrhagic fever (DF/DHF) outbreaks. India appears to be
transforming into a major hyperendemic niche for dengue infection. Increasingly, previously
unaffected areas are being struck by the dengue epidemic. The first confirmed report of
dengue infection in India dates back to the 1940s. Thereafter, several states began to report
the disease, which mostly struck in epidemic proportion, often inflicting heavy morbidity
and mortality, both in urban and rural environments 5,6.
In Kerala, cases of dengue, including some deaths, were reported for the first time in
1997; nevertheless, DEN-1, DEN-2 and DEN-4 viruses had been previously detected in
human sera. Dengue antibodies had been detected in human sera from Kozhikode, Kannur,
Palakkad, Thrissur, Kottayam and Thiruvananthapuram districts as early as 19797. The first
outbreak in large numbers in Kerala occurred in 2003, soon after the southwest monsoon8.
The risk of dengue has shown an increase in recent years due to rapid urbanization,
lifestyle changes and deficient water management including improper water storage practices
in urban, peri-urban and rural areas, leading to proliferation of mosquito breeding sites9.
This study was done to compare the trends in the clinically suspected dengue,
proportionate positivity of dengue among samples tested for dengue and case load during
the periods 2002–2004 and 2010–2012 in the Microbiology Department, Government
Medical College, Thiruvananthapuram. The years 2002–2004 marks the beginning of the
epidemic of Dengue and the latter years represent the latest available information at the point
of the study. We also tried to look for the variations and trends in the age-sex distribution
and seasonality across the years.
Methods
A record-based descriptive study was done using the records of Microbiology department,
Government Medical College, Thiruvananthapuram. Medical College Hospital, located in
Thiruvananthapuram, Kerala, India, is a premier institution for the provision of comprehensive
44
tertiary health care irrespective of economic or social status and disabilities. It is the largest
multi-specialty hospital in South Kerala and serves the major portion of Thiruvananthapuram
and Kollam districts and the adjacent districts of Tamil Nadu. All those patients with clinically
suspected dengue presenting to this tertiary setting are tested for dengue at the Microbiology
department. The samples for serology were tested for dengue virus IgM antibodies by IgM
capture ELISA. This is a qualitative detection of IgM antibodies against dengue virus antigen
(1–4) in human serum10. The samples pertained to the periods 2002–2004 and 2010–2012.
Data collection period consisted of 3 months from August–October, 2013. Important variables
included in the data collection Pro forma were year, month, age, sex and results-positive/
negative. Proportionate positivity of dengue in this study was defined as the percentage
of blood samples tested positive for dengue. Ethical clearance from the Institution Ethical
Committee and the permission from the corresponding heads of the departments were
obtained. The significance of the difference in proportionate positivity, gender differences
across the years and period was tested using chi-square test. The mean age of the positive
cases in the two periods were compared to look for any age shift, by the t-test
Results
Out of 10 064 samples tested over a period of 6 years, 3334 (33.1%) were positive for dengue.
Among the total tested samples, 7836 (77.9%) samples were collected during 2010–2012
as compared to 2228 (22.1%) collected during 2002–2004. Of the total positive cases,
2807 (84.2%) cases were from 2010–2012 and 527 (15.8%) cases were from 2002–2004.
A significantly higher proportion (p value <0.001) of samples tested during 2010–2012
were positive for dengue as compared to 2002–2004 (35.8 % and 23.7 %). The year-wise
proportionate dengue positivity is shown in Figure 1. It was the highest in 2012, when nearly
half (42%) of the tested samples were positive. 2012 also contributed to 37% of total dengue
positive cases. However maximum number of samples was tested during 2010. Out of the
total positive cases,1.1%, 6.1%, 8.5%, 32.3%, 15.2% and 36.6% belonged to years 2002,
2003, 2004, 2010, 2011 and 2012 respectively (Table 1, Figure 2).
Out of the total samples that were tested, 5590 (55.5%) samples were of males and
4474 (44.4%) samples were of females. The proportionate dengue positivity among females
(34.1%) was higher than males (32.3%). However, among the total 3334 positive cases, 1808
cases (54.2%) were males. These differences were however not statistically significant. The
proportionate positivity of dengue among males increased from 23.2% in 2002–2004 to
35.1% in 2010–2012. A higher increase in the proportionate positivity of dengue was seen
among females from 24.2% to 36.7% (12.5 %), when compared to the increase from 23.2%
to 35.1% in males (11.9%). This increase is also consistently seen across the years (Table 2).
In males,the proportionate positivity increased from 21.1% in 2002 to 41.6% in 2012. In
females,it has increased from 18.9% in 2002 to 42.3 in 2012.
45
Figure 1: Proportionate positivity of dengue across the years studied
100
90
% of positive cases
80
70
60
50
40
30
20
41.9
35.6
26.1
26.8
22.6
20.2
10
0
2002
2003
2004
2010
2011
2012
Year
Table 1: Proportionate positivity of dengue during years studied
2002
2003
2004
2010
2011
2012
2002–
2004
2010–
2012
Total
Dengue
positive
38
(20.2%)
205
(26.1%)
284
(22.6%)
1078
(35.6%)
508
(26.8%)
1221
(41.9%)
527
(23.7%)
2807
(35.8%)
3334
(33.1%)
Dengue
Negative
150
(79.8%)
581
(73.9%)
970
(77.4%)
1950
(64.4%)
1386
(73.2%)
1693
(58.1%)
1701
(76.3%)
5029
(64.2%)
6730
(66.9%)
Total
188
(1.9%)
786
(7.8%)
1254
(12.5%)
3028
(30.1%)
1894
(18.8%)
2914
(29.0%)
2228
(100%)
7836
(100%)
10064
(100.0%)
There has been a significant shift in mean age of the clinically suspected and positive
dengue cases towards higher ages from 2002 to 2012 and across the two comparison periods
(Table 3 and Table 4). The mean age of clinically suspected cases increased from 15.91 (SD16.39) in 2002 to 27.05 in 2012. The maximum number of clinically suspected (30% and
32%) and positive dengue cases (34% and 36%) was found in the age groups of 20–40 years
during the two comparison periods. (Table 5, Figure 3)
Dengue was higher during the months June, July and August (22.6%, 16.2% and 10.9%
respectively). The seasonality pattern has been maintained from the beginning of the epidemic
throughout the years (Table 6 and figure 4)
46
Figure 2: Contribution of each year to total positive cases
% contribution of each year
100
90
80
70
60
50
40
36.6
32.3
30
20
10
0
1.1
2002
6.1
8.5
2003
2004
15.2
2010
2011
2012
Year
Table 2: Proportionate positivity of dengue during years studied compared across sex
Year →
Total samples Male
(N=5590)
Dengue positive
males
Total samples Female
(N=4474)
Dengue positive
females
2002
2003
2004
2010
2011
2012
2002–
2004
2010–
2012
114
465
721
1627
1092
1571
1300
4290
24
(21.1%)
118
(25.4%)
160
(22.2%)
572
(35.2%)
281
(25.7%)
653
(41.6%)
302
(23.2%)
1506
(35.1%)
74
321
533
1401
802
1343
928
3546
14
(18.9%)
87
(27.1%)
124
(23.3%)
506
(36.1%)
227
(28.3%)
568
(42.3%)
225
(24.2%)
1301
(36.7%)
Table 3: Mean age of clinically suspect and dengue positive cases across the two periods
Clinically
suspect Dengue
Dengue positive
Period
Mean age
SD
t value
p-value
2010–2012
N=7823
27.40
20.08
3.27
0.001
2002–2004
N=2224
25.82
20.14
2010–2012
N=2802
27.58
18.95
3.71
<0.001
2002–2004
N=527
24.40
17.7
47
Table 4: Mean age of dengue positive case during the years studied
Year
N
Mean
Std.
deviation
95% Confidence Interval for
Mean
Lower bound
Upper bound
Minimum
Maximum
2002
38
22.36
20.507
15.61
29.10
1
75
2003
205
24.40
17.075
22.04
26.75
0
73
2004
284
24.71
17.861
22.62
26.80
1
93
2010
1074
28.46
18.524
27.35
29.56
0
85
2011
507
28.72
18.991
27.07
30.38
0
88
2012
1221
26.33
19.245
25.25
27.41
1
95
Total
3329
27.08
18.797
26.44
27.72
0
95
Table 5: Clinically suspected and positive dengue cases in different age groups during the
two comparison periods
2010–2012
2002–2004
48
Age group
Dengue positive
Dengue negative
Clinically suspect cases
0–10
610(21.8%)
1370(27.3%)
1980(25.3%)
11–19
527(18.8%)
832(16.6%)
1359(17.4%)
20–40
942(33.6%)
1370(27.3%)
2312(29.6%)
41–60
589(21.0%)
1119(22.3%)
1708 (21.8%)
>61
134(4.8%)
330(6.6%)
464(5.9%)
0–10
144(27.3%)
455(26.8%)
599(26.9%)
11–19
99(18.8%)
309(18.2%)
408(18.3%)
20–40
192(36.4%)
520(30.6%)
712(32.0%)
41–60
71(13.5%)
316(18.6%)
387(17.4%)
>61
21(4.0%)
97(5.7%)
118 (5.3%)
Figure 3: Distribution of total no. of positive cases in different age groups
4.7
26.3
19.8
0-10
11-19
20-40
41-60
≥61
15.1
34.1
Month
Jan
Feb
Mar
Apr
May
Jun
July
Aug
Sep
Oct
Nov
Dec
yr category
Table 6: Variation of dengue cases across months
2002–
2004
N=527
No.
67
36
42
17
27
101
146
20
10
10
31
20
%
12.7
6.8
8.0
3.2
5.1
19.2
27.7
3.8
1.9
1.9
5.9
3.8
2010–
2012
N=2807
No.
166
142
148
114
249
654
395
342
177
161
126
133
%
5.9
5.1
5.3
4.1
8.9
23.3
14.1
12.2
6.3
5.7
4.5
4.7
Total
No.
233
178
190
131
276
755
541
362
187
171
157
153
%
7.0
5.3
5.7
3.9
8.3
22.6
16.2
10.9
5.6
5.1
4.7
4.6
49
Figure 4: Variation of positive cases with months during (2002–2004) & (2010–2012)
100
90
% positive cases
80
2002-2004
70
2010-2012
60
50
23.3
40
30
27.7
5.9
20
5.1
12.7
10
0
Jan
14.1
5.3
6.8
8
4.1
3.2
Feb
Mar
Apr
8.9
19.2
12.2
3.8
5.1
May
Jun
Jul
Aug
6.3
1.9
5.7
1.9
4.5
5.9
4.7
3.8
Sep
Oct
Nov
Dec
Discussion
Dengue has become a major health concern in recent years. This study was aimed to find
the trends, seasonal variation and age-sex variation of dengue across the years. In this
study, it was found that the incidence of dengue is increasing across the years. From 20%
proportionate positivity, the figure has risen to 42%. A similar study conducted in Malaysia
during 2000–201011 and in Lucknow during 2008–201012 also found that there is an increase
in the number of dengue cases across the years. Every 10 years, the average annual number
of cases of DF/DHF cases reported to WHO continues to grow exponentially. From 2000 to
2008, the average annual number of cases was 1 656 870 or nearly three-and-a-half times
the figure for 1990–1999, which was 479 848 cases. In SEAR also, the number of dengue
cases has increased over the last three to five years, with recurring epidemics. Moreover, there
has been an increase in the proportion of dengue cases with their severity, particularly in
Thailand, Indonesia and Myanmar13. In 2008, 2009 and 2010, the average number of cases
reported to WHO were 1 279 668, 1 451 083 and 2 204 516. During the past five decades,
the incidence of dengue has increased 30-fold1. The reported cases in India have increased
from 12 561 in 2008 to 75 454 in 201314. The case reports from Kerala also have increased
from 2503 in 2006 to 7 911 in 2013. Reported cases in the district of Thiruvananthapuram
have increased from 1150 in 2006 to 4188 in 201315,16.
In the study, when the age characteristics of the positive dengue cases were studied,
it shows that the number of cases was more in the 20–40 age group followed by age
50
group 0–10. Also, the mean age of the positive dengue cases was found to increase across
the years. A study conducted at the Central laboratory, Mediciti Institute of Medical Sciences,
Ghanpur in 201217 showed that among the seropositives, majority (42.3%) were of the age
group 20–30 years and now there is an increasing incidence in the young adults and older
age groups. This suggests an age shift of dengue infections indicating an epidemiological
change. In another study conducted at Thailand using cases from 1985–200518 found that
there is a substantial increase in the average age of dengue cases. The study conducted at
Lucknow during 2008–2010 also revealed that there is an age shift from pediatric age group
in 2008 & 2009 to a higher age group in 201012.
On analysis of sex-wise distribution of dengue positivity, this study shows that the
proportionate positivity of dengue is more among females although the absolute number
of clinically suspected and positive cases are more in males. The reason for more positivity
among males is because there were more samples or clinically suspected cases of males.
This could be because males report to hospital more or male being a risk factor or otherwise,
there are more clinical suspects among males. A study conducted at CMC, Vellore during
1999–200319 showed that the overall increase in the dengue IgM positivity seen over the five
year period in both the sexes was statistically significant. The increase in percentage positivity
seen in females as compared to males was also statistically significant. A recent serological
study of adults by Yew et al20 found no significant differences between males and females
in recent dengue infection, despite the excess of male cases reported during the same year
the serological study was conducted.
The present study shows that the disease has got a seasonal occurrence. The incidence
of dengue was at the peak during June–July period which is the peak monsoon period in
Kerala. A study conducted in Dhaka during 2000–200821 found that the dengue cases started
increasing, as the rainfall increased and with declining rainfall dengue cases also showed
gradual decline. Another study conducted at Rajasthan during 2008–201122, on a monthwise analysis of dengue infections revealed that dengue cases increased in number gradually
from July onwards and that they peaked in the month of October each year. Most of the
cases occurred in the post-monsoon season, with a peak in the month of October, each year.
Limitations
(1) The study was a record-based study. Therefore the validity of the results obtained
depends on the efficiency of recording of the system
(2) Since the study was conducted at regional level, it cannot be generalized to state
51
Conclusion
The number of cases being clinically suspected as dengue, the proportionate positivity among
them and the absolute case load are increasing. The proportionate positivity of dengue has
risen to 42%. The proportionate dengue positivity among females was higher than males.
A higher increase in proportionate positivity is also seen among females. However, the
number of clinical suspects and absolute dengue cases are more in males. These differences
have not significantly changed across the years. 20–40 years age group contributed to the
maximum number of cases. There has been a significant shift in mean age of the clinically
suspect and positive dengue cases towards higher ages from 2002 to 2012 and across the
two comparison periods. The monsoon period depicted the peak of the case load and this
seasonality has not changed across the years.
References
[1] World Health Organization. Global strategy for dengue prevention and control 2012–2020. Geneva:
WHO, 2012. http://www.who.int/immunization/sage/meetings/2013/ april/5_Dengue_ SAGE_ _Global_
Strategy.pdf - accessed 21 December 2014.
[2] Gubler DJ. Dengue and dengue haemorrhagic fever: its history and resurgence as a global public
health problem. In: Gubler DJ, Kuno G. Eds.. Dengue and dengue haemorrhagic fever. New York:
CAB International,1997. pp. 1-23.
[3] World Health Organization. Dengue: guidelines for diagnosis, treatment, prevention and control: new
edition. Geneva: WHO, 2009. Document No. WHO/HTM/NTD/DEN/2009.1. http://www.who.int/
rpc/guidelines/9789241547871/en/ - accessed 21 December4 2014.
[4] Bhatt S, Peter W. Gething, Oliver J. Brady, Jane P. Messina, Andrew W. Farlow, Catherine L. Moyes,
et al. The global distribution and burden of dengue. Nature. 2013 Apr 25;496(7446):504-7. doi:
10.1038/nature12060.
[5] Lall R, Dhanda V. Dengue haemorrahagic fever and the dengue shock syndrome in India. Natl Med
J India 1996;9:20.
[6] Kadar A, Kandasamy MS, Appavoo P, Anuradha CN. Outbreak and control of dengue in a village of
Dharmapuri, Tamil Nadu. J Commun Dis. 1997;29:69.
[7] Banerjee K, Desai PK. Survey of arbovirus antibodies in South India. Indian J Med Res. 1973;61:344.
[8] Dengue in Kerala: a critical review. ICMR Bulletn. 2006 Apr-May, 36(4-5): 1-31.
[9] National Vector Borne Diseases Control Programme. Guidelines for clinical management of dengue
fever, dengue hemorrhagic fever and dengue shock syndrome. Delhi: Publication of Government of
India, 2008.
[10]Zinia T Nujum, Vijayakumar K, Pradeep Kumar AS, Anoop M, Sreekumar E, Ramani Bai JT, 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.
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[11]Mia MS, Begum RA, Er AC, Abidin RD, Pereira JJ. Trends of dengue infections in Malaysia, 2000-2010.
Asian Pac J Trop Med. 2013 Jun;6(6):462-6. Doi: 10.1016/s1995-7645(13)60075-9.
[12]Pandey N, Nagar R, Gupta S, Omprakash, Khan D, Singh DD, et al. Trend of dengue virus infection at
Lucknow, North India (2008- 2010): a hospital based study. Indian J Med Res. 2012 Nov;136: 862-867.
[13]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.
[14]Government of India, Ministry of Health and Family Welfare. Dengue: dengue cases and deaths in
the country since 2008. New Delhi: National Vector Borne Disease Control Programme, 2014. http://
nvbdcp.gov.in/den-cd.html - accessed 21 December 2014.
[15]Government of Kerala, Directorate of Health Service. Public health. Thiruvananthapuram: DHS. http://
dhs.kerala.gov.in/index.php/publichealth ,- accessed 21 December 2014.
[16]Government of Kerala, Directorate of Health Services. State bulletin,Thiruvananthapuram. Integrated
Disease Surveillance Project, State Surveillance Unit, 2010.
[17]Ahmed Jalily Q, Pavani G, Nandeshwar AJ. Screening for dengue infection in clinically suspected cases
in a rural teaching hospital. J. Microbiol. Biotech. Res. 2013;3(2):26-9.
[18]Cummings DAT, Iamsirithaworn S, Lessler JT, McDermott A, Prasanthong R, Ananda N, et al. The
impact of the demographic transition on dengue in Thailand: insights from a statistical analysis and
mathematical modeling. PLoS Med . 2009;6(9): e1000139. doi:10.1371/journal.pmed.1000139.
[19]Vijayakumar TS, Chandy S, Narayanan S, Abraham M, Abraham P, Sridharan G. Is dengue emerging
as a major public health problem? Indian J Med Res. 2005 Feb;121:100-107.
[20]Yik Weng Yew, Tun Ye, Li Wei Ang, Lee Ching Ng, Grace Yap, Lyn James, Suok Kai Chew, Kee
Tai Goh. Seroepidemiology of dengue virus infection among adults in Singapore. Annals of the
Academy of Medicine, Singapore. 2009; 38:667–75. pmid:19736569. http://www.annals.edu.sg/
pdf/38VolNo8Aug2009/ V38N8p667.pdf - accessed 21 December 2014.
[21]Md. Nazmul Karim, Saif Ullah Munshi, Nazneen Anwar, Md. Shah Alam. Climatic factors influencing
dengue cases in Dhaka city: a model for dengue prediction. Indian J Med Res. 2012 July;136(1): 32–9.
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3461715/ - accessed 21 December 2014.
[22]Sood S. A hospital based serosurveillance study of dengue infection in Jaipur (Rajasthan), India. Journal
of Clinical and Diagnostic Research. 2013 Sept;7(9):1917-20.
53
Evaluation of the efficacy of thermal fogging applied
in closed premises on dengue vector Aedes aegypti in
Malaysia
Nurulhusna AH1, Khadijah K2, Khadri MS1, Roziah A1,Muhamad-Azim MK1,
Mahirah MN1, Khairul-Asuad M1, Ummi Kalthom, S and Lee HL1
Medical Entomology Unit & WHO Collaborating Centre for Vectors, Institute for Medical Research,
Jalan Pahang, 50588 Kuala Lumpur
1
Vector Control Unit, Department of Health, Kuala Lumpur Federal Territory and Putrajaya,
Jalan Cenderasari, 50290 Kuala Lumpur
2
Abstract
Space spraying or fogging of insecticide to control dengue in residential areas is always hampered
by inaccessible or unoccupied houses. Therefore, a field study on the efficacy of insecticide
thermal fogging through the door-floor gap of closed and unoccupied residences was conducted
to determine the most effective angle of fog tube and the fogging duration. Thermal fogging using
a fogger (Agrofog®) and a water-based pyrethroid formulation, AquaResigen™, was tested in two
types of houses with volume of 186.3m3 (Type 1) and 368.1 m3 (Type 2). The fogging efficacy
was tested using 13 unoccupied houses with three houses as controls. The test was conducted
in triplicates. A total 25 Aedes aegypti each (sugar-fed laboratory bred, aged 3 – 6 days) were
aspirated into ten cages. The cages were hung in the sitting hall and bedrooms of test houses
1.5 m from floor level. Prior to the experiments, the suitable angle of lance at the door-floor gap
and the optimum fogging duration through the gap were determined. The insecticide was then
discharged into the house at the pre-determined angle and duration. After 60 minutes of exposure,
mosquitoes were transferred into clean paper cups and their mortality recorded after 24 hours. Fog
tube pointed 30° downward and 15-second fogging duration through the gap induced complete
or high mortality of Aedes mosquito in house sized 186.3m3, whereas house sized 368.1 m3 had
lower mortality compared to the smaller house. Insecticide droplet analysis indicated generally
uniform distribution of the droplets. The current practice of controlling Aedes mosquitoes using
thermal fogging in closed houses can be improved if the fog tube is positioned at 300 and with 15
second of fogging through the door-floor gap.
Keywords: Space spraying; Fogging; Aedes aegypti; Insecticide droplet.
#
E-mail: drzinia@gmail.com
54
Evaluation of the efficacy of thermal fogging applied in closed premises on dengue vector Aedes aegypti in Malaysia
Introduction
Dengue is endemic in Malaysia and used to be a seasonal problem, but in recent years,
dengue outbreaks often occur regardless of the season. There was an increase of 277% of
dengue cases in 2013 compared to 2014 within the same week period1. Dengue virus (DENV)
transmission occurs in both rural and urban areas; however, dengue infections are most often
reported from urban settings. Aedes aegypti (Linnaeus) and Aedes albopictus Skuse have been
implicated in the transmission of classical dengue fever (DF), dengue haemorrhagic fever
(DHF) and chikungunya in many urban areas of South-East Asia 2-5. Currently, in most tropical
countries including Malaysia, dengue is a serious public health problem causing morbidity
and mortality. To date, there is still no effective vaccine available to protect the people from
periodic recurrent outbreaks of DF and DHF6. Thus, to reduce the incidence of the disease
and control periodic outbreaks, the local authorities and public are still dependent very
much on the conventional measures of dengue vector control, such as insecticide fogging,
public health education and public involvement.
The biological and chemical control of both adult and immature Aedes mosquitoes are
still the mainstay of dengue vector control during outbreaks. Space spraying of insecticides or
fogging is one of the methods used in controlling the dengue vectors. However, the primary
vector of dengue, Aedes aegypti is an indoor breeder and prefers to rest mostly inside the
house. Thus space spraying with insecticides to kill adult mosquitoes is not usually effective
unless they are used indoors7. Fogging activities to control Aedes mosquito in closed premises
seems to be a very difficult task for vector control health personnel since quite a number
of houses are closed in an outbreak area. Recent surveys in two dengue outbreak areas in
Kuala Lumpur showed that only 23% - 45% of the houses could be fogged indoor8. There
are several reasons for this low level of indoor fogging: empty houses, houses were locked
(owners left for work) and the owners were reluctant to allow fogging indoors. To improvise
a solution, spacespraying through the gap between the door and floor is introduced to try
killing Aedes residing inside the closed premise. This study was conducted firstly to observe the
effectiveness of fogging through the gap between the door and floor, secondly to evaluate the
optimum angle of fog tube nozzle that can be used and finally to optimize fogging duration.
Study site and premises
The study was conducted from August – November 2011. Based on house size, two types
of houses were used in this study. The first type comprised houses sized 186.3 m3 (PPR
Beringin) and the second type was houses sized 368.1 m3 (Pangsapuri ATM). Prior to indoor
treatment, permission from the housing management in each study area was obtained.
55
PPR Beringin is an urban residential area with a very high population density and covers an
estimated area of 0.25 km2. It consists of six blocks of buildings, each composed of 17 floors,
with a total of 1896 units and an estimated population of 10 000 people. Each unit consists
of three bedrooms, a kitchen, a bathroom and a toilet. This residential area is classified as
a denguehigh risk locality since 2009. Pangsapuri ATM consists of five blocks, each with 15
storeys and the total number of residential units is 617. The population was estimated to
be 3500 people. Each unit comprises three bedrooms, two bathrooms and a kitchen. This
housing estate was declared a dengue outbreak area on May 2011 and a total of 13 cases
were reported within the same month. All the test and control (untreated) houses selected
were unoccupied and were partially furnished. A total of 13 houses were used in this study,
10 houses used for treatment while three houses were used as controls. The control houses
were set up in the untreated block.
Modification of thermal fogger nozzle
The nozzle fitted on the lance of the portable thermal fogger (Agrofog AF35®, Germany) was
modified. Originally the fog tube nozzle was round shape 4.7 cm in diameter. The round
nozzle was modified into oval shape measuring 2.5 cm x 6.0 cm. The flow rate machine
was recorded as 250ml/min.
Optimizing angle of lance
Three angles of lance to the floor gap were chosen: 30°, 45° and 60° (Figure 1). Each angle
was tested using the modified lance. The floor-door gaps of the three selected units were
measured. Wood wedges each came with 30°, 45° and 60 degrees were used to position the
lance. Magnesium oxide-coated rods on a rotator were placed into each test unit to measure
the droplet profiles of the fogged insecticide inside the premise. Prior to the fogging, the No. 1
nozzle size (0.8 mm) was used and calibrated to discharge the insecticide solution at 15L/h.
Insecticide
AquaResigen™ EW is a water-based pyrethroid formulation from Bayer CropScience
(Germany). It consists of 0.14% S-bioallethrin and 10.27% permethrin and 9.84% piperonyl
butoxide. The insectides was prepared as recommended by the manufacturer which is
10ml of the formulation per liter of the diluent for thermal fogging. The application dosage
recommended is 10L of diluted solution per hectare.
56
Field experiment
Laboratory-bred sucrose-fed Aedes aegypti females aged 3–5 days from insectary of Institute
for Medical Research (IMR) Kuala Lumpur, Malaysia were used in this study. Cylindrical test
cages (∅ 9cm, 15cm length) recommended by WHO9 were prepared. A total of 25 female
mosquitoes were collected and transferred into each cylindrical cage and a total of 10
cylindrical cages were used per house (Figure 1).
The cylinder cages were numbered and hung from the house ceiling 1.5 m above the
floor and 25 cm from each corner of the house. Before the test, all the windows and doors
were closed except the doors to all the rooms inside the house. Based on WHO9 standard
method for space spraying trial, magnesium oxide-coated rods were place vertically on
rotators located at the centre of a room to collect the droplets. Ten houses from each type
of house were used in this study. Ten houses were used in this study for both types of houses
and three houses in different blocks as a control. The door gap is variable between the test
houses. The thermal fogger nozzle was place directly at the gap and supported by a wood
wedge to obtain the optimal angle (Figure 2).
Figure 1: Setup of the cages in house sized 186. 3m3 (left) and
house sized 368.1m3 (right)
Fogging machine
Cylindrical cage
door
57
Figure 2: The position of the lance and the door gap
The rotator was switched on just before fogging started. Fogging was conducted through
the closed door-floor gap at an angle of 30o for about 15 seconds. The 15-second duration
was based on Khadijah et al10 who showed that this was the optimum duration to discharge
the insecticide effectively at door-floor gap compared to 10-second and 20-second duration.
Sixty minutes post–exposure, the number of mosquitoes knocked down was recorded and all
the mosquitoes were transferred into clean paper cups with 10% sugar pads. The mosquito
knockdown rate was observed at one hour and six hours, while mortality rate was observed
at 24 hours post-treatment.
Droplet profiles
Insecticidal droplets were examined under a normal light compound microscope fitted with
a photo-imaging system at a magnification of 400X. The diameters of the impinged droplets
were recorded and a minimum of 200 droplets were measured for each rod to determine
the droplet density and droplet size. The droplet analysis was carried out using the software
of Sofield and Kent11.
58
Results
Optimizing the fog tube angle
Thermal fog tube placed at an angle of 30o, 45o or 60o during fogging activities produced
condensation of insecticides on the floor (Figure 3). However, at the angle of 30o, lesser
insecticide condensation was observed compared to the other two angles. In addition, at
45o the fog tube could not fit into the gap between the door and door-grill, whilst at 60o,
the fog tube was too tilted and resulted in more condensation of insecticide on the floor.
This angle also burdened the operator of the thermal fogging machine. Therefore, fog tube
at an angle of 30o was chosen for the purpose of subsequent experiment.
Effectiveness of fogging
The knockdown was observed after one hour and six hours post-fogging interval and followed
by post-fogging 24-hour mortality. In the houses sized Type 1 (186.32m3) the knockdown
and mortality of the mosquitoes were 100% at every observation interval.
Figure 4 shows the observation of knockdown and mortality rate of Ae. aegypti postfogging activity in the houses sized Type 2 (368.12m3). The knockdown was higher in the 2nd
bedroom (73.60%) and was followed by the 1st bedroom (72.00%), while the cage located
in the toilet, 3rd bedroom and kitchen showed 31.60%, 41.20% and 24.00% knockdown
respectively.
In the living hall the cages located at position 1, 2, 3 and 5 showed lower knockdowns
compared to the living hall at position 4 with percentage <20%. Six hours post-fogging, the
location at living room 1, 2, 3, 5 and kitchen showed increased knockdown rate, while in
Figure 3: Schematic representation of insecticide condensation
from the fog tube at different angles
Grill
Fog tube
condensed
insecticide
Door
30°
45°
60°
59
Figure 4: The knockdown and mortality rates of Aedes aegypti in house size Type 2
(368.12m3) at various placements
26.40
31.60
Living
room 4
11.20
17.60
12.40
21.20
Living
room 3
24.00
25.60
33.60
6.80
13.60
21.60
Living
room 2
1.60
5.60
12.00
8.00
9.20
14.80
4.40
20.00
14.80
20.80
40.00
24.00
36.40
%
37.60
48.40
60.00
41.20
24 Hours
48.40
58.40
6 hours
72.00
1 Hour
80.00
73.60
100.00
0.00
Living
room 1
Living
1st
2nd
3rd
Kitchen
room 5 Bedroom Bedroom Bedroom
Locations
Toilet
the living room 4, knockdown was decreased from 17.60% to 12.40%. The same decreasing
pattern was also observed in locations such as 1st bedroom (36.40%), 2nd bedroom (48.40%),
3rd bedroom (24.00%) and toilet (11.20%).
No complete mortality was recorded in house type 2. Cages located in the 1st bedroom
(48.40%), 2nd bedroom (58.40%), 3rd bedroom (37.60%), toilet (26.40%) and kitchen
(33.60%) has the highest mortality compared to cages located at in the living room (12.00%
- 21.60%). In the living rooms the mortality was 14.80% - 21.60%.
Droplets size determination and analysis
The droplets of water-based insecticide (Aqua Resigen™) were detected on MgO rods on
a rotating impactor9 that were placed in the centre of the house hall. The NMD and VMD
values were computed using droplet analysis software and are shown in Table 1. The droplet
ratio in PPR Beringin and Pangsapuri ATM was 1.40 and 1.36 respectively, indicating the
uniform distribution of big and small droplets in both type of houses during the fogging trials.
60
Table 1: Analysis of thermal fog droplets collected on MgO coated rods placed at the
centre of the main entrance hallway
House area (m3)
VMD (µm)
NMD (µm)
VMD/NMD ratio
Type 1 (186.32)
23.32
16.67
1.40
Type 2 (368.12)
21.36
15.71
1.36
Discussion
During the field study several adjustments were made to optimize the angle of the fog tube
at the selected house door. This is needed as every house in both study sites was fitted with
door-grill, and the door-floor and door-grill gaps are variable. The design and thickness of
the door-grill also may influence the amount of insecticide penetrating the house. The fog
tube angle of 45o and 60o were not suitable to be used in these study sites. The observation
showed that when the fog tube was pointed at 45o the fog tube cannot be fitted into the gap
between the door and house grill and thus influences the rate of insecticide entering the house,
while at 60o, the fog tube position was too tilted, thus the fume was easily converted into
liquid. Besides that, thermal fogging cannot be operated at this position. The observation also
showed that the insecticide quickly condensed; changing its form from fume to liquid which
spilled out from the thermal fogging tube onto the floor. This condensation of insecticide on
the floor is slippery and may be risky to the residents when entering the house. Fogging at the
other two angles produced lesser amount of condensation on the floor. Fogging at door-floor
gap at 30o produced the least volume of condensed insecticide; hence the position of the
fog tube at 30o was chosen for the purpose of this experiment. Based on our observation, fog
tube at 30° was the best angle that allows maximum amount of insecticide to penetrate the
room with minimal condensed insecticide on the floor. The results showed that the spraying
effectively killed the caged mosquitoes inside the house. The door-gap of 3 mm to 28 mm
obviously allowed droplets to travel into all the rooms and spaces available.
The modification of the nozzle shape did not affect the discharge rate of the machine.
The modification was made to facilitate entry of the fog into the house. An earlier study
conducted by Khadijah (2011) showed that the discharge rate of the fogger was similar for
both modified and unmodified nozzle.
Each Type 1 house (186.3 m3) consists of three bedrooms, a hall, a kitchen, a toilet and
a bathroom. Comparatively, this is a small house in this country. This may account for the
high mortality of mosquitoes tested in this house type. In Type 2 (Pangsapuri ATM) houses
the volume of the house is 368.1 m3 which is 49% bigger than Type 1 (PPR Beringin) house.
In Type 2 houses, one hour post-spray cage located at 2nd bedroom and cage located at
1st bedroom had the highest knockdown. Six hours post-spray observation of the cage
located at the same location (2nd bedroom and 1st bedroom) also showed the highest
61
knockdown rates eventhough the percentage of knockdown decreased from the first one
hour post-fogging.
The mortality for all locations in the Type 2 houses was less than 60%. Knockdown
rates of mosquitoes in the cage located in the 3rd bedroom, toilet and kitchen had a lower
knockdown compared to the 1st & 2nd bedrooms because during one hour post-spraying
lesser insecticide droplets entered these places since their locations were far from the doorgap. The insecticide droplets would need to travel further through each room to kill the
mosquitoes. This will cause less knockdown rate and mortality observed in this area. The
mortality and knockdown rate of the mosquitoes were the lowest in cages placed in the
living hall in Type 2 house and this was probably due to wider area of the living hall, which
was twice as big than the living hall in Type 1 house. This essentially had a dilution effect
on the insecticide fog. The ratio of VMD and NMD at both study sites showed the big and
small droplets were homogenous, consistent and uniformly distributed.
Further improvement can be made especially in fogging duration according to house
volume. The volume of houses to be fogged through door-floor gap must be estimated
correctly to optimize fogging activities and ensure complete mosquito mortality. Further
study should be conducted to test field mosquitoes in order to gain more information and
since it has been shown that field-collected mosquitoes are more tolerant to insecticides13. In
addition, fog obstacles and mosquito hiding and resting places such as curtains and furniture
should be considered in future studies.
Conclusion
The study indicated that the mortality of laboratory-bred Aedes aegypti in empty houses in
PPR Beringin was high (100%) compared to Pangsapuri ATM (12% - 58%), showing that the
insecticide fog generated during the 15-second fogging could travel through the small doorgap as narrow as 3 mm. This study also proved that the water-based insecticide formulation
was able to penetrate the door-floor gap and travel throughout the room volume of ≈ 1300
square feet (120.7 m2). Indoor thermal fogging through the door-floor gap appears to be
suitable for the control of Aedes aegypti inside closed houses.
References
[1] Malaysia, Ministry of Health. Press statement of the Director General Ministry of Health Malaysia,
current situation dengue and chikungunya in Malaysia for week 17/2014 (1st May 2014).
[2] Smith CEG. The history of dengue in tropical Asia and its probable relationship to the mosquito Aedes
aegypti. Journal of Tropical Medicine and Hygiene. 1956; 59(10):243-51.
[3] Hammon WM. History of mosquito-borne hemorrhagic fever. Bulletin World Health Organization.
1966;44:643-49.
62
[4] Runnick A. Aedes aegypti and hemorrhagic fever. Bulletin World Health Organization. 1967;36:528.
Renganathan E, Parks W, Lloyd L.Towards sustaining behavioural impact in dengue prevention and
control. Dengue Bulletin. 2003;27:6–12.
[5] Nero C. Chikungunya the travelling virus.Clinical Microbiology Newsletter. 2008;30 (13):97-100.
[6] Kumar K, Singh PK, Tomar J, Baijal, S. Dengue: epidemiology, prevention and pressing need for vaccine
development. Asian Pacific Journal of Tropical Medicine. 2010;3(12):997-1000. doi: 10.1016/s19957645(11)60017-5.
[7] Gubler DJ. Aedes aegypti and Aedes aegypti-borne disease control in the 1990s: top down or bottom
up. Am. J. Trop. Med. Hyg. 1989;40:571-578.
[8] VBDCKL (2011). Summarize fogging data of Program Perumahan Rakyat (PPR) Beringin and
PangsapuriAngkatanTentera Malaysia (ATM). Bilikgerakandenggi.
[9] World Health Organization. Guidelines for efficacy testing of insecticides for indoor and outdoor
ground-applied space spray application. Geneva:WHO, 2009. Document No. WHO/HTM/NTD/
WHOPES/2009.2.
[10]Khadijah K. Effectiveness and optimizing of thermal fogging for dengue control in closed premise.
Thesis submitted for fulfilment of Diploma in Applied Parasitology and Entomology. Kuala Lumpur:
Institute for Medical Research, 2011.
[11]Sofield RK, Kent R. A basic program for the analysis of ULV insecticide droplets. Mosq News.
1984;44:73-5.
[12]Himel CM.The optimum size for insecticide spray droplets. J. Econ. Entomol. . 1969;62(4):919-25.
[13]Nazni WA, Kamaludin MY, Lee HL, Rogayah TAR, Sa’diyah I. Oxidase activity in relation to insecticide
resistance in vectors of public health importance. J Trop Biomed. 2000;17:69-79.
63
Civil-military cooperation (CIMIC) for
an emergency operation against a dengue outbreak
in the western province, Sri Lanka
HA Tissera1,2, PC Samaraweera2, BDW Jayamanne2, WCD Botheju1,
NWAN Wijesekara3, MPPU Chulasiri2, MDS Janaki2,
KLNSK De Alwis2, P Palihawadana1
1
Epidemiology Unit, Ministry of Health, Sri Lanka
National Dengue Control Unit, Ministry of Health, Sri Lanka
3
Disaster Preparedness and Response Division, Ministry of Health, Sri Lanka
2
Abstract
Dengue is a major public health problem in Sri Lanka. Despite many preventive strategies in
place, the dengue situation in the country worsened mainly due to the densely populated western
province. Therefore, a large-scale premises inspection programme was initiated in a phased
approach based on the disease and vector surveillance data. Health authorities in partnership with
the military identified as Civil-Military Cooperation (CIMIC) initiated a door-to-door programme
with the primary objective of source reduction within a short period. Results of this programme
seem to be noteworthy while its sustainability is probably a challenge.
Keywords: Dengue; Epidemic; Disease burden; Civil-military partnership; Sri Lanka.
Introduction
Dengue is a major public health concern throughout tropical and subtropical regions of the
world with an estimated 390 million infections, 50 000 severe dengue/dengue haemorrhagic
fever (DHF) cases and 22 000 deaths annually.1 It is the most rapidly spreading mosquitoborne viral disease, with a 30-fold increase in global incidence over the past 50 years. The
World Health Organization (WHO) estimates that 50–100 million dengue infections occur
each year and that almost half the world’s population lives in countries where dengue is
endemic. While dengue is a global concern, with a steady increase in the number of countries
reporting the disease, currently close to 75% of the global population exposed to dengue is in
the Asia–Pacific region. Sri Lanka has been witnessing its increasing incidence over the years.2
#
E-mail: dr_korelege@yahoo.co.uk
64
Civil-military cooperation (CIMIC) for an emergency operation against
a dengue outbreak in the western province, Sri Lanka
Dengue was serologically confirmed in Sri Lanka in 1962, with the first outbreak being
reported in 1965. Although the country has had a history of 40 years of dengue, since
the early 2000s, progressively large epidemics have occurred at regular intervals. Dengue
transmission in Sri Lanka is endemic, with large epidemics being reported in 2004 and
2009 with the peak transmission occurring in June-August soon after the monsoon season.
According to official statistics from the Epidemiology Unit, Ministry of Health, this trend has
continued to date with an annual average of 33 000 cases reported from 2009 to 2013. In
2012, 44 461 dengue cases were reported nationally, being the highest ever, corresponding
to an incidence rate of 220 per 100 000 population and 181 deaths (case fatality rate 0.4%).
Figure 1: Map of Sri Lanka showing the districts mostly affected by
dengue outbreak in 2014
Sri Lanka is a tropical country with high humidity and warm temperatures throughout
the year. Sri Lanka gets rainfall mainly from two rainy seasons: southwest monsoon (May to
August) bringing abundant rainfall to the country’s western and southern regions and the
northeast monsoon (November to February) bringing less rain to the dry north and eastern
regions. Nearly one quarter of the island is in the “wet zone” which includes the densely
populated western province. The average temperature for the country ranges between 26 °C
to 28 °C and the day and night temperatures may vary by 4 °C to 7 °C.
Studies show that most of the vector-borne diseases exhibit a distinctive pattern closely
linked to climatic parameters such as rainfall, temperature and other weather variables.3
65
Distribution of dengue cases is closely associated with the post-rainfall period in Sri Lanka.
Dengue incidence has been relatively low during the heavy rainfall and increases when
the rainfall starts to decrease, showing a three-to-four-week lag time between the rainfall
and dengue outbreaks.4. Two disease peaks occur annually in association with the monsoon
rains, when the densities of two mosquito vectors (Ae. aegypti and Ae. albopictus) are high
in Sri Lanka. Generally, the first peak occurs in June/July, coinciding with the south-western
monsoon that commences in late April. The second peak, comparatively a smaller one,
usually occurs at the end of the year and is associated with the north-eastern monsoon rains
that prevail from October to December.
Over the past 10 years we have witnessed a dramatic increase in the reported dengue
incidence and its severe manifestations (dengue haemorrhagic fever and dengue shock
syndrome) making this infectious disease a major public health problem. In Sri Lanka,
control and prevention strategies include integrated surveillance (disease, vector, serological),
standardized case management of dengue haemorrhagic fever, integrated vector management
(IVM), social mobilization and outbreak response.5
Ae. aegypti, the primary vector of dengue, is a ‘hydrophilic species’ i.e. humidity loving
and it has adapted to breeding in water-storage containers in domestic habitation. During
the rainy season, when temperatures fluctuate and humidity increases, the species invades
peridomestic areas and breeds profusely in any man-made or natural container holding
rainwater, building up a very high density.6
Globally, vector control (mainly for malaria) has been executed using chemicals, biocontrol agents and personal protection measures including insecticide-treated nets (ITNs)
but without much success for dengue. A successful vector control programme requires
intersectoral coordination, and active individual and community participation.7
Recently, a WHO-sponsored research project entitled “Eco Bio-social Research on
Dengue in Asia” concluded that variable influence on vector breeding is complex and public
health response should go beyond larviciding /spraying of insecticides. The study emphasized
the need to develop close interaction between political leaders, religious leaders, all sectors
of the economy and municipal authorities, which is critical for the success of dengue vector
control.8
In Sri Lanka, the Ministry of Health has advocated that disease control activities require a
sustained high-level government commitment, strengthening of public health infrastructure,
inter-sectoral collaboration and community participation. Timely control of dengue epidemics
requires preparedness and capacity to undertake suitable and effective control activities
during the inter-epidemic period. As dengue disease transmission occurs mostly in places
of residence, the ultimate success of the control programme would depend on community
participation and cooperation.
66
Due to progressive worsening of the dengue situation in the country mainly contributed by
the western province (60% of the cases of Sri Lanka)9, a decision was taken by the ‘Presidential
Task Force on Dengue Prevention’ on 9 June 2014 to carry out mass scale premises inspection
programme including houses, schools, government and non-governmental organizations,
public places, religious places and vacant.
The main objectives of the emergency dengue control programme involving Civil-Military
Cooperation (CIMIC) were:
zz
To mobilize a large number of civil-military personnel to rapidly reduce dengue vector
breeding sites in the western province.
zz
To inculcate sustainable behavioural change towards removing dengue breeding sites at
household level with the support of the armed forces and police.
This paper discusses the importance of social mobilization and intersectoral coordination
in an outbreak situation for control and prevention of dengue in the western province of
Sri Lanka.
Methods
Presidential task force on dengue prevention (PTFD)
As the burden of dengue fever is evolving rapidly, with increased frequency of outbreaks
and expansion to new geographical areas that were previously unaffected, the Ministry of
Health recognized the importance of sustained high-level government commitment through
intersectoral collaboration in order to maximize the provision of integrated services. The
Presidential Task Force On Dengue Prevention (PTFD) was established on 25 May 2010 in
order to strengthen multisectoral collaboration and smooth implementation of strategies at
the national, provincial, district and divisional level. Major stakeholders of PTFD include
the ministries of education, environment, defence, law and order, public administration,
disaster management, mass media, and local government under the technical guidance of
the Ministry of Health.
Three-phase mass-scale premises inspection
As a directive of the PTED, an Emergency Dengue Control Programme was conducted in
the western province comprising three districts namely Colombo, Gampaha and Kalutara.
Colombo district is divided into two administrative divisions called Colombo Municipal
Council (CMC) and Colombo Regional Directorate of Health Services (RDHS) while Kalutara
District as Kalutara RDHS and National Institute of Health Sciences (NIHS). Gampaha District
is administratively under the purview of Gampaha RDHS.
67
This programme was conducted in the western province coordinated by the health
authorities with the participation of tri forces and police, special task force and civil defence
force, together with other stakeholders and the community. In the armed forces this type
of collaborative activity is known as Civil-military cooperation (CIMIC). This programme is
reported as the first-ever major CIMIC activity in Sri Lanka and probably the sub-continent
to battle against dengue outbreak.
A number of planning meetings were held with the participation of all stakeholders
prior to the execution of the programme. Furthermore, a training of trainers programme
was conducted for over 1500 service personnel on identification of breeding places using
a standard checklist. A joint operation centre was activated at the Epidemiological Unit of
the Ministry of Health, with the participation of officers from the health ministry, tri forces
and police.
The emergency dengue control programme was conducted in the priority high-risk
Medical officer of health (MOH) areas based on the epidemiological trends reported.
A phased approach was used to manage the logistics. The first phase was conducted from
20 to 22 June 2014 while the second phase was conducted in two levels from 3 to 5 July and
8 to 10 July 2014. The third phase was also conducted in two levels. While 18 June 2014
(1st level) was aimed at institutions and second level conducted again, inspecting residential
premises. Altogether a three-phased campaign for 13 days of mass-scale inspection was
conducted targeting most vulnerable areas. Inspection teams comprised of one person from
the health authorities, two persons from tri-forces and police and a volunteer from the area/
village. A standard checklist and the route map were given to each team while assigning a
minimum of 50 premises to be targeted. Coordinating officers were assigned at each district
while monitoring teams were appointed from the national level to monitor the programme
implementation and to ensure smooth operations.
The programme was mainly aimed at detection and elimination of mosquito breeding
places onsite, augmented by cleaning up campaigns and the use of available vector reduction
methods (introduction of fish, larvicide spraying, fogging). Community awareness was
created during the programme and legal action against those premises contributing towards
substantial mosquito breeding was also initiated. In order to promote positive behaviours
towards eliminating dengue breeding sites, a green sticker was awarded to premises in which
not even a single dengue breeding site (positive or potential) could be detected. A yellow
sticker was given to identify the premises which were not accessible to the teams on the
days of field visits. Mosquito larval breeding sites were targeted according to the available
entomological surveillance data, while follow-up surveys were carried out to estimate the
reduction.
68
Results
Table 1: Total number of premises inspected during all three phases
and % of premises with larvae
Area
No. of
premises
visited
No. of
premises
with
larvae
Percentage
No. of persons mobilized
Health
Military
Volunteers
Phase I
CMC*
53 533
908
1.7
551
3 738
-
RDHS Colombo
20 628
363
1.8
405
1 343
191
RDHS Gampaha
15 047
766
5.1
322
1 131
-
RDHS Kalutara
16 705
713
4.3
320
1 165
69
105 913
2 750
2.6
1 598
7 377
260
Total
Phase II
CMC
80 726
767
1
1 777
4 582
427
RDHS Colombo
96 005
1 412
1.5
1 324
3 721
903
RDHS Gampaha
50 272
937
1.9
724
2 033
19
RDHS Kalutara
20 940
704
3.4
NIHS Kalutara
4 889
405
8.3 658
2 321
344
252 832
4 225
1.5
4 483
12 657
1 693
Total
Phase III
CMC
6 809
67
2.1
456
168
-
RDHS Colombo
47 938
482
1.0
467
2 120
815
RDHS Gampaha
45 639
441
1.0
742
2 220
1 083
RDHS Kalutara
15 742
397
2.5
447
1 045
249
NIHS Kalutara
6 031
59
1.0
169
432
33
122 159
530
1.2
2 281
5 985
2 180
480 904
8 495
1.8
8 362
26 019
4 133
Total
Grand Total
*CMC – Colombo Municipal Council
69
Table 2: Analysis of reduction of premises with larvae
Phases
Premises
Statistics
Without larvae
With larvae(%)
Test statistic
P value
Phase I
103 163
2 750(2.59)
–
–
Phase II
248 607
4 225(1.67)
18.7147
<0.01
Phase III
122 629
1 520(1.24)
24.7835
<0.01
There was a significant reduction in Premise Index in phases II and III when compared
to phase 1 larval percentage during the programme.
Figure 2: Map showing Colombo RDHS area covered in all three phases
70
Figure 3: Map showing Gampaha RDHS area covered in all three phases
Figure 4: Map showing Kalutara RDHS area covered in all three phases
71
Figure 5: Reported dengue cases by week within the western province
from January to August 2014
1200
Phase I
Phase IIB
1000
Phase IIA
Cases
800
600
Phase III
400
200
0
1
2
3
4
5
6
7
8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30
Week of year 2014
Table 3 : Statistical comparision of Premise Indices during
follow-up entomological surveys
Premise Index
Phases
Statistics
CIMIC
Follow-up
Test Statistic
P value
Phase I
2.59 (2 750/103 163)
3.29 (70/2 125)
-1.776
0.07508
Phase II
1.67 (4 225/248 607)
2.18 (50/2 192)
-1.775
0.07508
Phase III
1.24 (1 520/122 629)
1.64 (45/2 738)
-1.883
0.06010
The effectiveness of the programme is shown by statistical comparison of premise indices
during and the follow-up entomological surveys. 72
Table 4: Percentages of Aedes positive (for larvae/pupae), potential wet and dry containers
observed in follow-up entomological surveys (Phase I to III)
Item
Positive
for
Aedes (%)
Potential wet
containers
(%)
Potential dry
containers
(%)
1
Discarded receptacles
40.32
42.27
65.69
2
Water storage tanks and containers
16.71
15.48
6.08
3
Tree holes, bromilia plants and other
natural containers
4.77
7.18
4.62
4
Tyres
4.24
2.38
4.88
5
Roof gutters
3.71
1.81
4.09
6
Air conditioners and refrigerator trays
3.71
6.69
4.11
7
Concrete slabs
2.65
2.03
1.33
8
Abandoned cisterns
2.65
1.20
0.18
9
Ponds and birth baths
2.39
4.80
0.46
10
Hardened soil of plotted plants and
flower pot plates
1.59
1.59
0.64
11
Flower vases
1.59
0.86
0.40
12
Clear water drains and gully traps
0.80
1.84
0.42
13
All others*
14.85
11.88
7.11
100.00
100.00
100.00
* All others- other miscellaneous places (e.g. covering material (i.e. polythene sheets), tube wells, earth pipes, water
leaking areas, discarded building waste/materials (i.e. roof tiles), etc).
According to the follow-up entomological surveys, it was still evident that discarded
receptacles remained the most productive type of container.
Discussion
Recurrence of dengue outbreaks in the western province, Sri Lanka has become a growing
public health problem despite ongoing control measures. Population growth, rapid
urbanization, inadequate basic housing, improper waste disposal systems are a few of the
known factors for increased incidence of dengue in general. Reducing larval habitats of
the principal vector mosquito Aedes aegypti is a major component of the dengue control
programme in Sri Lanka. However, sustainability of source reduction programmes through
continued community participation has been a challenge due to lack of interest among
the people in removing potential breeding places in their own premises. Therefore, every
73
available opportunity to promote social mobilization should be considered in this “war”
against the scourge of dengue.
Sri Lanka is committed to controlling vector-borne diseases with a very high-level of
political commitment seen by the establishment of the Presidential Task Force on Dengue
Prevention in 2010. Vector management is taken very seriously, with the active engagement
of various stakeholders and the community. Strengthening intersectoral coordination and
social mobilization was the main aim of this civil–military partnership. The high level of
inspection of premises is a testament to the close relationship between the armed forces,
local field health teams and the community. The armed forces and the police in particular
have won the acceptance of the community in Sri Lanka in recent times. Extending and
sustaining this model will bring great benefits in dengue prevention and control and ultimately
for improvement of public health. In addition, this is a model public health intervention to
demonstrate how a well planned and executed community-based intervention could bring
about immediate relief to its people in a middle-income country.
Dengue vector mosquitoes use a wide range of confined larval habitats, mainly
man-made. It is known that some man-made container habitats produce large numbers
of adult mosquitoes, whereas others are less productive. Targeting control efforts at the
most productive and epidemiologically more important larval habitats is a key strategy
in reducing transmission effectively, especially when working with limited resources. The
training provided to all members of inspection teams based on local entomological indices
significantly influenced their ability to identify potential and positive breeding habitats more
effectively. In the context of dengue vector control, management of non-biodegradable
items in solid waste is challenging. Proper storage, collection and disposal of waste through
community engagement and empowerment were initiated at every possible instance during
the programme. To this end, the support given by the local government bodies is noteworthy.
As a measure of the effectiveness of each programme, follow-up entomological surveys
were carried out in the same areas. In the RDHS area of Kalutara district, the follow-up survey
Premise Indices (PI) were comparable with phase I, II and III of the programme in contrast
with the other three areas. A higher PI was seen in CMC, RDHS Colombo and Gampaha
throughout the programme (Table 3). Many factors may be associated with this disparity.
In addition, the discrepancy between Table 2 and Table 3 could be the factors for selecting
houses for mass scale programme and entomological surveys. Entomological surveys were
carried out selecting high-risk localities with a limited number of houses leading to higher
possibility of larval detection. Awareness of the programme and dispersion of the message
to the public may be very effective that public has complied timely and correctly so that
during the programme, breeding sites were minimum. Entomological surveys are carried out
by well-trained technical personnel after 2–3 weeks of a particular phase and by that time
the public awareness may have returned to neutral level resulting in the above findings. The
quality of inspection may be higher than the trained military personnel and health volunteers
but in some areas during some phases these factors have played a minimum role. Other
74
than the above factors the environmental factors like rainfall, humidity and environmental
temperature might also have contributed to the above disparity.
When analysing the data for the last five years there was an exponential increase in
reported number of patients per week (900 patients per week on average in the western
province during the 22nd to 25th weeks) in 2014 just before starting phase I. According to
Figure 5, one can notice the epidemiological impact by the dramatic reduction of case load
per week by disrupting the upward trend (estimated forecast of cases for 26th week is 1 162
according to the trend model () generated from the 17th week onwards) rapidly which we
cannot achieve without this kind of door-to-door inspection during a month’s time with this
sort of civil-military partnership.
The total direct cost on all three phases of the programme by the Ministry of Health was
Sri Lankan Rupees 30 million for 481 000 premises (~Sri Lankan Rupees 63 per premise).
In 2012, the health system cost of dengue prevention activities in Colombo district reached
a total of Sri Lankan Rupees 127 million (per capita cost was around Sri Lankan Rupees
55.10). The total cost of dengue response in Colombo district by health system budgets in
2012 amounted to Sri Lankan Rupees 452.9 million (US$ 3.5 million) giving a per capita
cost of Sri Lankan Rupees 196.09 (US$ 1.5). The morbidity cost included control cost per
reported case (~Sri Lankan Rupees 13 000) and hospital management cost (DF - Sri Lankan
Rupees 26 000–64 000/DHF Sri Lankan Rupees 34 000–114 000) per patient10. Therefore, a
substantial cost on case management would have been averted due to this timely intervention
through CIMIC.
Integrated Vector Management (IVM) is a rational decision-making process for the optimal
use of resources for vector control and the sustainability of the programme. The approach
seeks to improve the efficacy, cost-effectiveness, ecological soundness and sustainability of
disease-vector control11. The ultimate goal is to prevent the transmission of vector-borne
diseases. Successful implementation of IVM should lead by evidence-based decision making
guided by operational research and entomological and epidemiological surveillance and
evaluation which is a key feature. Adequate human resources, training and career structures
need to be developed at national and local level to promote capacity building to sustain
these types of programmes. Strengthening the attitude of households and getting their active
involvement is the most effective proven strategy of IVM. The Ministry of Health expects to
achieve low morbidly and mortality due to dengue illness through this type of CIMIC activities.
Acknowledgements
The authors would like to thank the Presidential Task Force on Dengue (PTFD), His Excellency
the President of Sri Lanka and all Ministers and Ministry Officials of the PTFD, and the
Secretary, Ministry of Defense for taking the leadership in the activities.
75
The Secretary of Health (Sudharma Karunarathna), Director General of Health Services
(Dr PG.Mahipala), Deputy Director General-Public Health Services (Dr Sarath Amunugama),
Provincial Director – Western Province (Dr Deepthi Perera), Consultant Community Physician
(CCP) – Western Province (Dr Priyadarshani Samarasinghe), Regional Directors of Health
Services Colombo (Dr Chula Gunasekara), Gampaha (Dr Sugath Darmarathne), Kalutara
(Dr UI Rathnayake) Director National Institute of Health Sciences(Dr Lakshman Gamlath),
Chief Medical Officer of Health - Colombo Municipal Council (Dr Ruwan Wijemuni),
Regional Epidemiologists (Dr Nayani Sooriyarachchi-Colombo, Dr Rohan Ranasinghe/
Dr Manjula Arachchi /Dr Chandrani Liyanage (Gampaha), Dr Prasad Liyanage (Kalutara)
and Dr Lasitha Tantriwatta (N.I.H.S) Medical Officers of Health (MOOH) and all the field
staff Ministry of Health, Provincial Departments of Health –Western Province and Colombo
Municipal Council.
Special acknowledgement goes to Major General BA Perera (Director General –
Operations and Systems), Brigadier SHFP Perera (Director – Operations and Systems) at
Office of the Chief of Defence Staff (OCDS-SL Army), Commander SD Kodikara (Command
Land Operations Officer-SL Navy)Wing Commander BR Booso (Staff Officer, Health ServicesSLAF),Lieutenant Colonel HMS Priyantha (Civil Affairs Officer-Civil Defence Force), Director
Environment Police Division (Quintus Raymond-Senior Superintendent of Police) and all the
respective chiefs and team members for their contributions.
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] Bhatt S, Gething PW, Brady OJ, Messina JP, Farlow AW, Moyes CL, Drake JM, Brownstein JS, Hoen
AG, Sankoh O, Myers MF, George DB, Jaenisch T, Wint GR, Simmons CP, Scott TW, Farrar JJ, Hay SI.
The global distribution and burden of dengue. Nature. 2013 Apr 25;496(7446):504-7. doi: 10.1038/
nature12060. Epub 2013 Apr 7. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3651993/ - accessed
24 December 2014.
[2] World Health Organization. Global strategy for dengue prevention and control, 2012-2020. Geneva:
WHO, 2012. Document No. WHO/HTM/NTD/VEM/2012.5. – accessed 24 December 2014.
[3] Gubler DJ, Reiter P, Ebi KL, Yap W, Nasci R, Patz JA. Climate variability and change in the United
States: potential impacts on vector-and rodent-borne diseases. Environmental Health Perspectives.
2001 May;109(Suppl 2):223-33. http://www.ncbi.nlm.nih.gov/pmc/ articles/PMC1240669/pdf/
ehp109s-000223.pdf – accessed 24 December 2014.
76
[4] Pathirana S, Kawabata M, Goonatilake R. Study of potential risk of dengue disease outbreak in Sri Lanka
using GIS and statistical modelling. Journal of Rural and Tropical Public Health. 2009;8:8-17. http://
epubs.scu.edu.au/cgi/viewcontent.cgi?article=1866& context=esm_pubs – accessed 24 December
2014.
[5] Sri Lanka, Ministry of Health. National plan of action for prevention and control of dengue fever 2005
– 2009. Colombo: Epidemiology Unit. http://www.epid.gov.lk/web/ images/pdf/Circulars/latest_draft_
poa_for_dfdhf.pdf - accessed 24 December 2014.
[6] Dash A, Bhatia R, Kalra N. Dengue in South-East Asia: an appraisal of case management and vector
control. Dengue. 2012 Dec;36:1-13. http://www.wpro.who.int/mvp/epidemiology /dengue/Dengue_
Bulletin_Vol36.pdf – accessed 24 December 2014.
[7] Erlanger T, Keiser J, Utzinger J. Effect of dengue vector control interventions on entomological parameters
in developing countries: a systematic review and meta-analysis. Medical and veterinary entomology.
2008;22(3):203-21.
[8] Arunachalam N, Tana S, Espino F, Kittayapong P, Abeyewickrem W, Wai KT, et al. Eco-bio-social
determinants of dengue vector breeding: a multicountry study in urban and periurban Asia. Bulletin
of the World Health Organization. 2010;88(3):173-84. http://www.scielosp.org/pdf/bwho/v88n3/10.
pdf - accessed 25 December 2014.
[9] Sri Lanka, Ministry of Health. Epidemiology Unit. Colombo: MoH, 2011. www.epid.gov.lk – accessed
25 December 2014.
[10]Thalagala N. Health system cost for dengue control and management in Colombo District,Sri Lanka.
in 2012. Colombo: Dengue Tool Surveillance Project, Epidemiology unit, Ministry of Health, 2014.
http://www.epid.gov.lk/web/images/pdf/Publication/Health_System_Cost_for_Dengue.pdf - accessed
25 December 2014.
[11]World Health Organization . Integrated vector management (IVM). Geneva: WHO. http://www.who.
int/neglected_diseases/vector_ecology/ivm_concept/en/ - accessed 25 December 2014.
77
Dengue in South Asian sub-continent: how well have
the surveillance systems done?
Ananda Amarasinghe1,2, Anil K Bhola3, Scott B Halstead2
Epidemiology Unit, Ministry of Health, Sri Lanka
Dengue Vaccine Initiative, International Vaccine Institute, Seoul, Korea
3
Independent Public Health Consultant, New Delhi, India
1
2
Abstract
The South Asian sub-continent with high population density accounts for two-third of the global
burden of symptomatic dengue cases but the severe under-reporting based on passive surveillance
systems hardly measures the true extent and spread of dengue infection. It warrants re-orienting
and re-vitalizing surveillance systems for effective and efficient control and prevention of dengue,
particularly in larger countries in the subcontinent.
Keywords: Dengue; Dengue burden; South Asia; Surveillance.
Background
Dengue virus (DENV) infection is the most prevalent arbo-virus infection in tropical and
subtropical regions of Asia and Americas.1 The recent global estimates reveal that 390
million (95% CI 284–528) DENV infections occur annually and 2.5 billion people live in
dengue-endemic countries.2 It is estimated that only 30% of dengue infections manifest as
overt illnesses ranging from mild acute febrile illness to dengue haemorrhagic fever (DHF).
Out of 96 million global symptomatic cases nearly two-third are from Asia.2 This
commentary is focused only on the following South Asian sub-continent countries;
Bangladesh, Bhutan, India, Maldives, Nepal, Pakistan and Sri Lanka. All four serotypes of
DENV have been reported in these countries.3
The number of cases and the patients clinical care are the concerns of the public and
the media. Most countries in the sub-continent have developed national guidelines for the
clinical management of dengue by customizing the WHO South-East Asia Region guidelines
according to the prevailing local situations.2,3 Availability and better access to good medical
#
E-mail: ana_amarasinghe@yahoo.co
78
Dengue in South Asian sub-continent: how well have the surveillance systems done?
care has no doubt significantly reduced mortality. However, the true burden of the disease
and its economic impact in these countries is still not adequately studied.4-5 Dengue is a
notifiable disease in all these countries and functioning surveillance of communicable diseases;
including dengue, is in place. But the issue of concern is whether the dengue surveillance
system in the South Asian sub-continent is effective and efficient enough to serve its purpose
of controlling and preventing dengue transmission and its spread.
Dengue burden in the South Asian sub-continent
India is the largest country, both geographically and by population, in this region.6 The
first ever report of dengue in India was 200 years ago but it has been reported as endemic
only over the last two decades.7–9 Only after a severe dengue outbreak in 1996, a sentinel
surveillance system was established under the National Vector-Borne Disease Control
Programme in India.10 Since then, the number of reported cases has gradually increased. In
2013, the highest-ever number of 75 454 cases with 167 deaths were reproted.10 However,
according to the global estimates, annually there are about 32 million symptomatic DENV
infections in India.2 Another recent estimate found that there would be 700 000 or more
cases of overt dengue illnesses/year in India.9 It is important to note that comparison of these
numbers need to be cautious, because there are some distinct features of the numbers:
infections (in apparent illness), overt dengue illness and laboratory cases are not the same.
The infections represent the highest proportion of the disease, while laboratory cases are
the lowest. It is important to note that the reporting system in India is passive, sentinel sitebased and only laboratory confirmed cases are reported. This system cannot possibly detect
the full magnitude of dengue disease in the country.
Bangladesh, with a population of 156.5 million has hardly reported any major outbreak
of dengue, except in 2000,6,11 despite the prevailing factors favouring the disease transmission
such as vector, tropical climate, unplanned urbanization, etc. The estimates indicate about
4 million cases of dengue, but national reports by passive surveillance show only around
1000 cases/year.2 It is important to note that Bangladesh reports the lowest rate in the subcontinent (Table 1). Other competing communicable diseases and public health issues and
also frequent natural disasters (eg. floods) in the country may have resulted in less attention
to dengue.
Global burden study estimates that there are 3.4 million dengue cases in Pakistan with
a population of about 182 million.2,6 The first dengue outbreak was reported in 1994.12
Reporting practice varies by the states and mixed passive and ad hoc sentinel site surveillance
systems are in place. It is observed that the country surveillance system largely functions only
during epidemics. According to the country reports from 2006, less than 5000 cases/year
were reported except in 2010–2011 when the country reported the largest-ever outbreak
with 252 000 clinically suspected cases, of which 17 000 were laboratory confirmed.13,14
79
Sri Lanka with a population of 20.4 million6, has indicated a hyper-endemic trend of the
disease.15 It has a combined sentinel and enhanced passive surveillance system. Dengue was
first reported in the 1960s and since 2009, it has been reported on an average of 30 000 to
40 000 clinically suspected cases/year.16 However, according to the global estimates, 670 000
symptomatic cases would be expected annually in the country.2 Sri Lanka has a potentially
high opportunity to improve the surveillance system, because of the high public health alert
and the disease priority recognized by the health authority.
Dengue is new to Nepal, where 27.7 million population6 first experienced a massive
outbreak in 2010, since its first-ever dengue case was reported in 2004.17-18 Country statistics
shows around 100 cases/year, while estimates indicate 570 000 cases annually.2
Bhutan, a hilly small country with 0.75 million population,6 also reported around
100 cases/year.19 Dengue started to appear in 2004 and over 2500 cases were reported
in the dengue outbreak of 2005.20 The estimated annual burden is 4700 cases/year.2 Both
Nepal and Bhutan share a common challenge with its geographical terrain to sustain an
efficient surveillance system. In any country, surveillance is a part of the health care delivery
system and it depends on the health care infrastructure too. When the infrastructure is
underdeveloped, a poor surveillance system is unavoidable.
Maldives with 199 inhabited small islands with 0.35 million population has reported
around 1000 cases/year although the global estimates indicate around 6000 cases per year.2
The health care network covering each inhabited island is able to pick suspected dengue
cases from a given small population, and is an advantage in its surveillance system.
Central points
The proportion of cases reported by the surveillance system, even during outbreak periods
fall short of the global estimates. This is more apparent in larger countries. We used available
published estimates to demonstrate a comparison between reported caseload against
expected caseload (Table 1). It helps to understand the magnitude of under-reporting and
what proportion of cases from the population is missing from the surveillance radar. During
the last few decades, an increasing number of research projects including special surveillance
have been reported in these countries.4,8-9, 15 This a positive sign that these countries are
generating novel country specific data.
According to the new global burden study, India had the highest disease burden of any
dengue-endemic country in the world.2 In the last few years, the increasing number of dengue
cases reported by India is largely due to improvements in the surveillance system rather than a
true increase in disease burden. However, as we have pointed out previously, the surveillance
system in India is limited to sentinel sites and also to the laboratory confirmed cases.
80
Table 1: Country surveillance system and its ever reported highest number of cases
and dengue burden estimates
Country
Type of dengue surveillance system
Bangladesh
Routine passive surveillance
Bhutan
Routine passive surveillance and
enhanced sentinel sites surveillance
India
Passive sentinel site- laboratory
confirmed surveillance
Maldives
Routine enhanced passive surveillance
Nepal
Routine passive surveillance
Pakistan
Routine passive surveillance and adhoc sentinel sites surveillance
Sri Lanka
Routine passive surveillance and
Enhanced sentinel site surveillance
Highest number of cases ever reported
versus dengue estimates*
Ratio
%
5000: 4 000 000
0.13%
2500: 4700
53.19%
75 000: 32 000 000
0.23%
75 000: 700 000
10.71%
1000: 6000
16.66%
7000: 570 000
1.23%
252 000: 3 400,000
7.42%
44 000: 670 000
6.57%
¶
*Global estimates by Bhatt et al (2012)
¶
Estimates for India by Amarasinghe et al (2014)
Laboratory diagnosis is important in dengue, particularly in non-epidemic periods, nonendemic geographical areas and in early detection of the outbreaks. It is also an essential
component in research confirming the cases. Although it is a bonus to have a laboratorysupported routine surveillance system it is not practical, one reason being the cost involved.
All available dengue diagnostics have their advantages and disadvantages; each of the lab
test result is linked with day of illness. The clinical case definition with a good sensitivity and
specificity is the key in routine passive surveillance.
Existing passive surveillance systems need to be supported with a sentinel site component.
Routine passive surveillance can rely on clinical diagnosis, whereas the sentinel sites need
support with laboratory diagnosis. This combination will lead to a high yield in surveillance.
Besides, entomological surveillance should also supplement and guide the vector control
interventions. It is unrealistic to expect any good output from a surveillance system, without
adequate number of trained manpower, logistics support and monitoring and evaluation.
These are the core issues common in most of these countries in the sub-continent. It is true
that this is an immense challenge, particularly for larger countries with a very high and diverse
population, complex administrative structures and health care delivery systems.
The consequences of a weak and flaccid surveillance system are an under-estimated
burden of dengue, leading to unrealistic planning that is unlikely to be evidence-based with
insufficiently designed prevention and control measures.
81
The countries share some common challenges in dengue surveillance and also have some
differences. Therefore, the concern of the public health authority should be to review the
country surveillance system in order to address the gaps for measuring the dengue burden
and planning, resource allocation, designing disease prevention and control interventions.
Conclusion
Dengue burden as measured by existing surveillance systems in the South Asian sub-continent,
particularly in Bangladesh, India and Pakistan are still below expectation and largely underreported. Surveillance systems in the countries must be re-oriented and re-vitalized for
capturing the realistic extent of the burden of dengue. Without realistic data on disease
burden it is difficult to have effective interventions for prevention and control of dengue in
the sub-continent.
References
[1] World Health Organization. Dengue guidelines for diagnosis, treatment, prevention and control: new
edition. Geneva: WHO, 2009. http://www.who.int/rpc/ guidelines/ 9789241547871/en/ - accessed
25 December 2014.
[2] Bhatt S, Gething PW, Brandy OJ, Messina JP, Farlow AW, Moyes CL, Drake JM, Brownstein JS, Hoen
AG, Sankoh O, Myers MF, George DB, Jaenisch T, Wint GRW, Simmons CP, Scott TW, Farrar JJ, Hay SI,
2013. The global distribution and burden of dengue, 2013. Nature. 2013 Apr 25;496(7446):504-7.
doi:1038/nature 12060.
[3] World Health Organization, Regional Office for South-East Asia. Comprehensive guidelines for
prevention and control of dengue and dengue haemorrhagic fever. New Delhi: WHO-SEARO, 2011.
[4] Yara Halasa, Halasa YA, Dogra V, Arora N, Tyagi BK, Nanada D, Shepard DS. Overcoming data limitations:
design of a multi component study for estimating the economic burden of dengue in India. Dengue
Bulletin. 2011;35:1-14.
[5] Gubler DJ. The economic burden of dengue. Am J Trop Med Hyg. 2012;86(5):743–4. doi: 10.4269/
ajtmh.2012.12-0157. http://www.ajtmh.org/content/86/5/743.full.pdf +html - acessed 25 December
2014.
[6] World Bank. Data: population, total. Washington, DC: WB. - accessed on August 08, 2014
[7] Jatanasen S, Thongcharoen P. Dengue haemorrhagic fever in South East-Asian countries. In: Monograph
on dengue/dengue haemorrhagic fever. New Delhi: WHO-SEARO, 1993. pp. 23-30.
[8] Chakravarti A, Arora R, Luxemburger C. Fifty years of dengue in India. Trans R Soc Trop Med Hyg.
2012 May;106(5):273-82. doi: 10.1016/j.trstmh.2011.12.007. Epub 2012 Feb 21.
[9] Amarasinghe A. Bhola AK. Halstead SB. Uncovering dengue in India: morbidity estimates. Global
Journal of Medicine and Public Health. 2014;3(3). - accessed 25 December 2014.
82
[10]Government of India, Ministry of Health and Family Welfarea. Long term action plan for prevention
and control of dengue and chickengunya. New Delhi: Directorate of National Vector Borne Disease
Control Programme, MOH&FW, 2007. http://nvbdcp.gov.in/Doc/Final_long_term_Action_Plan%20.
[11]Rahman M, Rahman K, Siddque AK, Shoma S, Kamal AHM, Ali KS, Nisaluk, Breiman RF. First
outbreak of dengue hemorrhagic fever. Bangladesh. Emerg Infect Dis. 2002;8(7):738-40. doi:10.3201/
eid0807.010398.
[12]Paul RE, Patel AY, Mirza S, Fisher-Hoch SP, Luby SP. Expansion of epidemic dengue viral infections to
Pakistan. Int J Infect Dis. 1988;2(4):197-201.
[13]Ahmed S, Mohammad WW, Hamid F, Akhter A, Aftal RK, Mahmood A. The 2011 dengue haemorrhagic
fever outbreak in Lahore – an account of clinical parameters and pattern of haemorrhagic complications.
J Coll Physicians Surg Pak. 2013 Jul;23(7):463-7. Doi:07.2013/JCPSP.463467. http://www.ncbi.nlm.
nih.gov/ pubmed/ 23823947 - accessed 25 December 2014.
[14]World Health Organization, Regional Office for the Eastern Mediterranean. Dengue in Pakistan. Cairo:
WHO-EMRO. http://www.emro.who.int/surveillance-forecasting-response/outbreaks/dengue-fever-inpakistan.html - accessed 25 December 2014.
[15]Tissera H, Amarasinghe A, de Silva AM, Kariyawasam P, Corbett KS, Katzelnick L, Tam CC, Letson GW,
Margolis HS, De Silva AD. Burden of dengue infection and disease in a pediatric cohort in urban Sri
Lanka. Am J Trop Med Hyg. 2014 Jul;91(1):132-37. doi:10.4269/ajtmh.2013.0540.
[16]Sri Lanka, Ministry of Health. Epidemiology unit. Colombo: MOH. http://www.epid.gov.lk - accessed
25 December 2014.
[17]Pandey BD, Morita K, Khanal SR, Takasaki T, Miyazaki I, Ogawa T, et al. Dengue virus. Nepal. Emerg
Infect Dis. 2008;14(3):514–5. Doi: 10.3201/eid1403. http://www.ncbi.nlm.nih.gov/pmc/articles/
[18]Gupta BP, Manandhar KD, Malla R, Tamarakar CS, SK Mishra, Rauniyar R. Emergence of dengue virus
infection in Nepal. Int J Appl Sci Biotechnol. 2013;1(3):79-84. Doi:10.3126/ijasbt.v1i3.8384. http://
ijasbt.org/vol_1/ BP_Gupta_et.al._1(3).pdf – accessed 25 December 2014.
[19]Royal Government of Bhutan, Ministry of Health. Public health laboratory services. Thimphu:
Department of Public Health, MOH. http://www.phls.gov.bt - accessed 25 December 2014.
[20]Tandin Dorji, In-Kyu Yoon, Edward C. Holmes, Sonam Wangchuk, Tashi Tobgay, Ananda Nisalak, Piyawan
Chinnawirotpisan, Kanittha Sangkachantaranon, Robert V. Gibbons, Richard G. Jarman. Diversity and
origin of dengue virus serotypes 1, 2, and 3. Bhutan. Emerg Infect Dis. 2009;15(10):1630–1632.
doi: 10.3201/eid1510.090123. http://wwwnc.cdc.gov/eid/article/15/10/09-0123_article accessed 25
December 2014.
83
Evaluation of sensitivity and specificity of commercially
available dengue rapid test kit in two hospitals in
Colombo, Sri Lanka
Hasitha A Tisseraa, Dinindu P Kaluarachchia, Thilini D Jayasenaa,
AnandaAmarasinghea, Aravinda M de Silvab, BuddikaWeerakoona,
SunethraGunasenac, Jayantha S D K Weeramana, Duane Gublerd,
Annelies Wilder-Smithe, Paba Palihawadanaa
Epidemiology Unit – Ministry of Health, Sri Lanka
Department of Microbiology and Immunology, University of North Carolina School of medicine,
Chapel Hill, north Carolina, United States of America (USA)
c
Medical Research Institute, Colombo, Sri Lanka
d
DUKE-NUS, Graduate Medical School, Singapore
e
Umea University, Sweden
a
b
Abstract
Easy to perform and accurate point of care rapid diagnostic test could be a useful tool for timely
decision making for management of dengue patients. This study was done on paediatric and
adult patients presenting with ≤ 7 days of fever in both outpatient and inpatient settings. Dengue
rapid test kit (NS1 and IgM) performance at the point of care was compared with standard inhouse RT PCR, NS1 Ag ELISA and IgM Capture ELISA tests. A total of 1225 blood samples, 71.8%
collected on 3–5 days of fever, were tested. In outpatient and inpatient departments rapid NS1
test sensitivity ranged from 62.39% to 74.64% upto day 4 of fever and then declined from day 5
onwards. The sensitivity of rapid IgM test was 18.99% for outpatients and 48.85% for inpatients.
Overall sensitivity of the rapid test was 77.51% with little variation due to day of fever and type
of treatment setting. For acute fever patients in the inpatient setting the rapid test kit would be a
useful bedside test to guide the clinicians.
Keywords: Dengue diagnosis; Dengue laboratory tests; Dengue rapid tests.
Introduction
Dengue has become the most common mosquito-borne arboviral infection in the world1.
An early diagnosis is important for effective management and prevention of complications2.
#
E-mail: dr_korelege@yahoo.co.uk
84
Evaluation of sensitivity and specificity of commercially available dengue rapid test kit
in two hospitals in Colombo, Sri Lanka
Detection of viral antigen, RNA and specific antibodies are the common laboratory methods
used to confirm the presence of dengue virus (DENV) infection2. Dengue rapid test kits to
detect specific antibodies and NS1 antigen are more frequently being used in patient care
services as well as for disease surveillance3,4,5.
DENV isolation and a four-fold or greater increase in specific antibodies are considered
the “Gold Standard” of diagnosing dengue infection. Because of its higher sensitivity and
the rapidity of obtaining results6,7,8 detection of dengue virus RNA by reverse transcriptase
polymerase chain reaction (RT-PCR) is replacing standard virology and serologic diagnostic
methods. Real-time PCR sensitivity ranges from 62–92.8% and specificity 92.4–100% for
all four dengue virus serotypes9,10,11.
NS1 antigen detection can also be used for early detection of dengue infection. Dengue
NS1 antigen can be detected from 0–9 days of the illness12,4 and is most sensitive during the
first three days of illness and during primary infection13. The sensitivity of NS1 detection by
commercial kits vary with the kit (range 21–99%), but in all the specificity remains 100%14,15,16.
When the NS1 is combined with IgM antibody in a DUO Kit, the sensitivity improves without
compromising specificity17,18.
DENV specific antibodies can be detected by enzyme-linked immunosorbent assay
(ELISA), Haemaggulutination inhibition (HI), complement fixation (CF) or neutralization test
(NT)4. IgM antibody is detected after 3–5 days of the illness in both primary and secondary
infections, but the response is weaker and more transient in the latter4, leading to a small
percentage of false negatives19. False positive IgM results have been observed in malaria
and secondary dengue patients by rapid IgM assays4,20. IgM sensitivity and specificity by
commercially available kits ranges from 21–99% and 77–98%, respectively20,4. Denguespecific IgG antibodies are detectable only after the first week of illness (day 10–15 of
illness) in primary dengue infection, but are detectable in the acute phase sera in high titres
in secondary dengue infection4.
Dengue has currently become a major health care issue in Sri Lanka. During the rainy
season a large number of febrile patients who are suspected of having dengue illness
present to health care institutions. Although there is no rapid test that can be accurately
used in a point-of-care setting, in busy medical care settings, early diagnosis can be helpful
to physicians in making timely decisions to admit, follow-up and rule out the diagnosis of
possible dengue infection. It also benefits the patient/family to care for the illness. In current
Sri Lankan health care setting, there is a growing demand for laboratory testing. In such
situations dengue rapid test assays can be useful. The rapid test is easy to use and does not
require a lab or special expertise. The steps are simple, easy to follow and clinic personnel
can be easily trained to perform them. However, it should be emphasized that a suspicion or
early diagnosis of dengue in a general practitioner or outpatient setting should be primarily
based on the clinical presentation, and not on the rapid test kit results.
85
The objective of this study was to evaluate the sensitivity and specificity of the DUO
NS1/IgM dengue rapid test kit and compare it with single plex NS1 and IgM tests in two
hospitals in Colombo, Sri Lanka. A secondary objective was to determine the best day and
setting (outpatient or inpatient care settings) to perform these tests.
Study design: The study was a cross-sectional analytical study that was conducted from
March 2012 to April 2014.
Study setting: The study was carried out in two main hospitals in the Colombo district; Lady
Ridgeway Hospital (LRH) for children, which is the national centre of excellence for paediatric
care, and the Infectious Disease Hospital (IDH), the national centre for infectious disease
care. Both the inpatient and outpatient settings were used for data collection.
Study population: A total of 1225 patients were enrolled through simple random sampling.
Case definition: A case of fever was defined as a patient having a history of temperature
of ≥38 °C lasting ≤7 days at the time of enrolment and was considered a case even in the
absence of high temperature at the time of interview since a majority of patients were taking
antipyretics before reaching hospital.
Inclusion criteria: A patient having fever lasting ≤7 days who had given consent for blood
drawing was included in the study.
Exclusion criteria: Patients having fever for more than seven days, those who have not or were
unable to give written consent were not included in the study. Also, patients with a history
that could have harmful effects due to blood drawing were also excluded from the study.
Consent: Informed written consent from the patient was taken by a trained pre-intern doctor.
In paediatric patients, informed written consent was taken from the parent or guardian with
paediatric assent.
Collection of blood samples: A volume of 2.5ml and 5 ml of venous blood was drained
from paediatric patients and adult patients respectively into Ethelene diamine tetra acetic
acid(EDTA) anti-coagulated vacutainer tubes (BD vacutainer tubes, BD diagnostics, New
Jersey, USA). The sample was labelled with a study ID and a small amount of blood taken
for on-the-spot rapid test. The cold chain of sample were maintained until transport to the
laboratory where laboratory testing was performed and sample allocates were stored for
further testing.
Rapid test: The rapid test was performed using the SD Bioline Dengue Duo kit by trained
pre-intern doctors. The test was carried out according to the manufacturer’s instruction21.
86
Laboratory testing: The tests performed were the RT-PCR, Dengue IgM antibody and Dengue
NS1 Antigen. RT-PCR was performed using an in-house method22 while Standard Diagnostics
(DS) Dengue NS1 A°g ELISA kit and SD Dengue IgM Capture ELISA kit were used according
to the manufacturer’s instructions23,24.
Data entering and analysis: All the available data were entered in duplicate by two data entry
operators into Microsoft Access database. The consent forms and lab reports were stored in
secured cupboards accessible only to authorized personnel of the study. All computers and
databases were password-protected. Analysis was carried out using SPSS 20.
Ethical clearance for this study was granted by the Research Ethics Committee at the
Medical Research Institute, Ministry of Health, Sri Lanka.
Results and discussion
The total sample of 1225 patients consisted of 51.8% (n=635) males, 49.85% (n=611)
paediatric (<12 years of age), and 49.3% (n=604) were > 12 years, including 0.7% (n=10)
patients aged >65 years. The majority of the samples were collected on day 3–5 of the
illness (71.8%), with small numbers on day 1 (n=23) and day 7 (n=37).
The sensitivity and specificity of the Dengue Duo kit NS1 alone were 61.07% and 96.32%
respectively (Table 2). These values remained the same for both outpatient and inpatient
departments (Figures 4,5). Rapid Test NS1 sensitivity remained high on day 2, 3 and 4 of
illness, ranging from 62.39% to 74.64% (Figure 1) but declined from day 5 onwards. This
is probably because the NS1 antigen is high in the first few days of the illness and gradually
declines thereafter. The Duo kit NS1 specificity remained high in both departments regardless
of the day of illness (Figures 4,5).
The sensitivity of Dengue Duo kit IgM alone was 46.04% and the value was comparatively
high for inpatients (Table 2). This is probably because the IgM estimation by the rapid test
kit is more accurate later in the infection and since most of the samples after the fourth day
of illness were collected from the inpatient department. However, the specificity of the test
remains more or less the same (95.79%) for both departments.
The SD bioline Dengue Duo kit as a whole had a sensitivity of 77.51% and a specificity
of 93.68%. The sensitivity was higher in the inpatient department (78.72%) and the specificity
was higher in the outpatient department (98.88%). Overall the sensitivity and specificity
showed relatively little variability with the day of illness (Figure 3).
The results show that using the Dengue Duo kit with both NS1 and IgM together will
result in a higher sensitivity rather than using each test alone.
87
Also, in the inpatient setting the rapid kit would be a useful bedside screening test rather
than a confirmatory test. The decision whether the rapid test kit should be used will depend
on the availability of the rapid and conventional tests, costs and time constraints. Interpretation
of the test by the health professional should be carried out in collaboration with the respective
patient’s clinical scenario and the kit used as a guide rather than a definitive diagnostic tool.
Table 1: Comparison of standard tests vs rapid tests
Rapid
tests
Result
NS-1
Only PCR
%
Only
NS1
%
Only
IgM
Positive
530
310
58.5
486
91.7
350
Negative
695
220
31.7
38
5.5
Total
1225
530
43.3
524
Result
IgM
Only PCR
%
Positive
405
102
Negative
820
Total
1225
Result
Standard tests
Any of 3
%
66.0 154 29.1
516
97.4
178
25.6 357 51.4
14
2.0
42.8
528
43.1 511 41.7
530
43.3
Only
NS1
%
Only
IgM
%
All 3
%
Any of 3
%
25.2
181
44.7
239
59.0
56
13.8
285
70.4
303
37.0
223
27.2
165
20.1 120 14.6
119
14.5
405
62.1
404
33.0
404
33.0 176 14.4
404
33.0
%
Only
NS1
%
Only
IgM
%
All 3
%
Any of 3
%
Both (+) Only PCR
%
All 3
%
Positive
256
109
42.6
238
93.0
237
92.6
34
13.3
170
66.4
Negative
526
147
27.9
15
2.9
18
3.4
86
16.3
160
30.4
Total
782
256
32.7
253
32.4
255
32.6 120 15.3
330
42.2
Table 2: Summary of standard laboratory tests and rapid test kit results
Lab confirmation by RTPCR/ SD IgM/ SD NS1
Test
Rapid NS1
Rapid IgM
Rapid duo
88
Positive
Negative
Total
(n=845)
(n=380)
1225
Positive
516
14
530
Negative
329
366
695
Positive
389
16
405
Negative
456
364
820
Positive
655
24
679
Negative
190
356
546
Result
Table 3: Sensitivity and specificity of rapid test kit NS1 antigen and
IgM antibody detection
OPD
(n=257)
IPD
(n=968)
Total
(n=1225)
RapidNS1 Sensitivity
58.23%
61.36%
61.07%
RapidNS1 Specificity
98.88%
94.06%
96.32%
RapidIgM Sensitivity
18.99%
48.83%
46.04%
RapidIgM Specificity
100.00%
92.08%
95.79%
Duo Sensitivity
65.82%
78.72%
77.51%
Duo Specificity
98.88%
89.11%
93.68%
Figure 1: Rapid test NS1 sensitivity and specificity variation with duration of illness
100%
90%
100
97.06
97.96
97.06
94.81
93.75
100
80%
70%
74.64
60%
62.39
62.05
58.01
50%
40%
53.42
46.88
45.45
30%
20%
10%
0%
Day 1
Day 2
Day 3
RNS1 Sensitivity
Day 4
Day 5
Day 6
Day 7
RNS1 Specificity
89
Figure 2: Rapid test IgM sensitivity and specificity variation with duration of illness
100%
90%
100
100
100
98.04
100
93.51
85.42
80%
70%
60%
62.77
66.44
50%
53.13
40%
36.32
30%
20%
10%
0%
20.29
18.18
9.38
Day 1
Day 2
Day 3
Day 4
RIgM Sensitivity
Day 5
Day 6
Day 7
RIgM Specificity
Figure 3: Rapid Duo kit : NS1 and IgM combination sensitivity and specificity variation
with duration of illness
100%
90%
100
97.06
97.96
89.61
80%
81.16
80.09
74.36
70%
60%
100
96.08
63.64
85.42
78.08
68.75
68.75
50%
40%
30%
20%
10%
0%
Day 1
Day 2
Day 3
Duo Sensitivity
90
Day 4
Day 5
Day 6
Day 7
Duo Specificity
Figure 4: Outpatient department NS1 with day of illness
100%
90%
100
94.12
100
98.25
100
100
87.05
80%
70%
65.52
60%
57.14
50%
40%
50.00
45.83
42.86
30%
20%
10%
0%
Day 1
Day 2
Day 3
Day 4
NS1 Sensitivity
Day 5
Day 6
NS1 Specificity
Figure 5: Inpatient department NS1 with day of illness
100%
90%
100
100
93.94
100
95.56
92.16
93.02
80%
77.06
70%
60%
50%
40%
64.29
50
58.04
54.17
53.47
46.88
30%
20%
10%
0%
Day 1
Day 2
Day 3
NS1 Sensitivity
Day 4
Day 5
Day 6
Day 7
NS1 Specificity
91
Figure 6: Outpatient department IgM with day of illness
100%
90%
100
100
100
100
100
100
100
0.00
Day 6
Day 7
80%
70%
60%
57.14
50%
40%
30%
33.33
20%
10%
0%
14.29
Day 1
0.00
Day 2
6.90
Day 3
Day 4
IgM Sensitivity
Day 5
Igm Specificity
Figure 7: Inpatient department IgM with day of illness
100%
90%
100
100
100
100
95.56
90.20
80%
83.72
70%
60%
62.95
67.36
50%
53.13
40%
36.67
30%
20%
25.00
10%
0%
23.85
12.50
Day 1
Day 2
Day 3
IgM Sensitivity
92
Day 4
Day 5
Day 6
Day 7
Igm Specificity
Figure 8: Outpatient department Duo test with day of illness
100%
90%
100
94.12
100
98.25
100
100
87.50
80%
70%
71.43
68.97
60%
50%
100
58.33
57.14
50.00
40%
30%
20%
10%
0%
Day 1
Day 2
Day 3
Day 4
Duo Test Sensitivity
Day 5
Day 6
Day 7
Duo Test Specificity
Figure 9: Inpatient department Duo test with day of illness
100%
90%
100
100
93.94
80%
70%
100
93.33
84.31
84.40
80.36
76.19
75.00
83.72
78.47
68.75
60%
62.50
50%
40%
30%
20%
10%
0%
Day 1
Day 2
Day 3
Duo Sensitivity
Day 4
Day 5
Day 6
Day 7
Duo Specificity
93
Acknowledgements
The study was partly funded under the Health Theme of the Seventh Framework Programme
of the European Community (Grant No. 282589). We offer special thanks to Standard
Diagnostics, Inc, Republic of Korea and George Steuart Health, Sri Lanka for providing
substantial support for the study. The authors thank all the research assistants and project staff
for their dedication. Also special thanks go to the laboratory staff of the Medical Research
Institute and Genetech Research Institute, Colombo.
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95
Prevalence of dengue vector in relation to
dengue virus infection in central region of Nepal
Bijaya Gairea,b, Komal Raj Rijala, Biswas Neupaneb, Pravin Paudyalb,c, Ishan
Gautamd, Megha Raj Banjaraa, Kouichi Moritae and Basu Dev Pandeyb#
a
Central Department of Microbiology, Tribhuvan University, Kirtipur, Nepal
Everest International Clinic and Research Center, Kathmandu, Nepal
b
c
Department of Microbiology, National College, Kathmandu, Nepal
Natural History Museum, Tribhuvan University, Swayambhu, Kathmandu, Nepal
d
Institute of Tropical Medicine, Nagasaki University, Japan
e
Abstract
This paper describes results of an entomological and serological survey that was conducted from
July to October 2012 in Chitwan district, central Nepal. A total of 159 breeding habitats were
investigated for the presence of Aedes larvae, among which 54 discarded tyres were found to be
positive, with a breeding preference ratio (BPR) of 1.15. In the serological study, 46 dengue cases
were determined by enzyme linked immuno-sorbent assay (ELISA) in the same area. The container
index (CI) as well as the number of dengue cases was higher in the post-monsoon season than
the monsoon season. It is concluded that discarded tyres lying outdoors were the preferable wet
container for the dengue vector.
Keywords: Dengue; Dengue vectors; Aedes; Container index.
Introduction
Dengue, the most common arboviral disease, ranks as the most important mosquito-borne
viral disease in the world. Annually, about 50-100 million new infections are estimated to
occur in more than 100 endemic countries.1 About 2.5 billion people living in tropical and
sub-tropical regions are at risk of dengue infection.2 The threat of dengue virus infection
(DVI) is increasing in Nepal as the disease causes significant morbidity and mortality every
year in the neighbouring country. Being bordered by India in the eastern, western and
#
E-mail: drbasupandey@gmail.com
96
Prevalence of dengue vector in relation to dengue virus infection in central region of Nepal
southern belts, Nepal is more vulnerable to worse consequences of DVI. The first outbreak
occurred in Nepal following the Indian epidemic of DF/DHF in September–October 2006
followed by a second dengue epidemic in Chitwan in 2010.3 In 2010, there was a major
outbreak of dengue in three districts of the Central Terai with 917 cases reported.4 Chitwan
district was the worst hit with more than 700 dengue IgM positive cases (data obtained from
District Public Health Office, Chitwan). Further, the epidemic of 2010 in Chitwan alarmed
the possibility of future outbreaks in Central Terai region of Nepal.
Dengue virus (DENV) has five serotypes and is transmitted by the day-time biting mosquito
Aedes aegypti and Ae. albobticus. Ae. aegypti is the major vector for the dengue virus in
many parts of the world; Ae. aegypti has wider geographical distribution at present than at
any time in the past and is established in virtually all tropical and subtropical countries.6 Ae.
albopictus is considered a secondary vector5 and known to be present in the Terai lowlands,
Siwalik hills and Middle Mountain region of Nepal since 19567,8 but the introduction of Ae.
aegypti is as recent as 2006 in the Terai region of Nepal9 and is involved in dengue outbreaks
in Nepal.9,10,11,12 Presence of Ae. aegypti and Ae. albopictus immatures in different areas of
Middle Mountain including Kathmandu valley (average elevation 1350 m above sea level)
have been reported12,13,14 including the first record of Ae. aegypti from Kathmandu.15 The
geographical distribution of dengue vectors in central Nepal was clearly defined. Dengue
distribution has gradually spread since 2004 in Nepal and Ae. aegypti and Ae. albopictus
were commonly found upto 1350 m in Kathmandu valley and present but rarely found from
1750 m to 2100 m in Dhunche, Rasuwa district, Nepal.
The primary dengue vector A. aegypti has already expanded to at least above 2000m
altitude which clearly defines its geographical distribution in Nepal. 14 Its altitudinal
ranges, density and distribution could be linked to global and local changes resulting from
temperature, rainfall, humidity and seasons, varying latitude and altitude16,17,18 along with
vehicular movements, growth in human populations, and their activities13,14,15 attributable
to outbreaks at new foci.19,20
In Nepal, despite the geographical expansion and significant morbidity of dengue, very
limited entomological studies12,13,15,21 along with knowledge, attitude and practice of the local
communities about dengue fever among the healthy population of highland and lowland
communities in central and southern Nepal22,23 have been carried out so far and hence,
the density of the vector mosquitoes has not been clearly noted in the study area. Chitwan,
being the worst hit place by dengue in Nepal, we aimed at relating the serology of dengue
with the entomological studies here. The major objective of the study was to identify the
relationship between Container Index (CI) of vector larvae with the occurrence of dengue.
97
Methodology
Study area
Chitwan lies in the central part of the southern lowlands of Nepal between 27°21’45’’ to
27°52’30’’ N and 83°54’45’’ to 84°48’15’’ E. The altitude of the district ranges from 141
to 1947 meters above sea level. The sampling for the serological study was performed in a
tertiary-care hospital, Bharatpur Hospital during July to October 2012. The hospital has a
capacity of >300 beds and serves a mixed population and often gets referrals from adjacent
districts such as Nawalparasi, Gorkha, Lamjung, Tanahun, Makawanpur and Rupandehi.
Study population
Patients presenting with history of fever for >5 days or temperature of >37.8 oC were
recruited into the study if they had two or more of the signs and symptoms relating to dengue.
A case was excluded, if routine laboratory analysis (whole blood cell count, urine analysis)
suggested bacterial or any viral infection other than dengue infection or any other disease.
Subjects with previous Japanese encephalitis immunization were excluded from the study.
After the patient was assessed and provided treatment, a standard case report form was
completed. About 5 ml of blood from adults and 3 ml blood from children of five years and
younger was collected and serum was separated for further serological testing.
Serological study
The serum samples were transferred to the Everest International Clinic and Research Centre
(EICRC), Kathmandu, maintaining the reverse cold chain for further serological tests by IgM
antibody capture enzyme linked immunosorbent assay (MAC-ELISA) for DENV (Standard
Diagnostics Inc., Korea).
Entomological study
The entomological study was also conducted in Chitwan (Figure 1) during the monsoon
and post-monsoon period. All potential Aedes breeding habitats such as discarded tyres,
plastic buckets, metal drums and earthen pots were examined. Immatures of Aedes were
collected using 400 ml capacity dipper, pipette (10 ml), spoon and torchlight depending on
the nature of the breeding habitat. The immature of Aedes that were found in the sites were
transferred into a plastic container and were brought back to the lab for identification. All
live immature mosquitoes were collected and reared24 until adult emergence at the Natural
History Museum, Kathmandu. The adult mosquitoes emerged from reared larvae and pupae
were identified on the basis of different morphological characters by using taxonomic keys
published earlier.8,25 A total of 159 wet containers (71 in monsoon and 88 in post-monsoon
98
period) were examined which were categorized into four different container types; discarded
tyres, plastic buckets, metal drums and earthen pots. Based on data collected, Container
Index (CI) and Breeding Preference Ratio (BPR) of dengue vectors for different container
were calculated.
Statistical analysis
Data was analyzed using SPSS Version 17.0. Chi-square was done and the value of significance
for all statistical tests was p value < 0.05.
Figure 1: Map of Chitwan district
Settlement Map
Bharatpur Municipality
Chitwan
99
Result
The MAC-ELISA test performed in 227 serum samples from suspected dengue cases detected
the dengue virus specific IgM antibodies from 46 (18 males, 28 females) cases (Table 1).
Most of the patients were in the age group <15 years.
The highest number of dengue cases (16 out of 55) were detected in October, followed
by 15 (out of 66) cases in September. The least numbers of dengue cases (6 out of 49) were
detected in July and 9 (out of 57) cases in August (Figure 2). The highest number of dengue
positive cases (31) were detected in the post-monsoon season and 15 cases were detected
in the monsoon season.
Out of 159 wet containers that were searched for the presence of vector larvae, 71
were searched in the monsoon period (37 in July and 34 in August) and 88 were searched
in the post-monsoon period (37 in September and 51 in October). Thirteen containers were
positive for vector larvae during the monsoon period with CI of 18.3% and 49 containers
were positive during the post-monsoon period with CI 60.3% (Table 2). Among the different
searched breeding sites, BPR was highest in the case of discarded tyres, with larvae being
found in 54 cases out of 120 wet containers (Table 3). The relation between the number of
dengue cases and CI is presented in Figure 3.
Table 1: Demographic distribution of dengue cases
Total no. of
samples
No. of positive
samples (%)
Male
94
18 (39.2)
Female
133
28 (68.8)
< 15
58
13 (28.3)
16-30
36
6 (13.0)
31-45
49
11 (23.9)
46-60
40
6 (13.0)
>60
44
10 (21.8)
227
46 (100)
Demographic characters
p value
Sex
0.73
Age in years
Total
100
0.83
Figure 2: Distribution of dengue cases
90
80
70
Suspected Cases
Positive Cases
60
50
40
30
20
10
0
July
August
September
October
Table 2: Comparison of month-wise contaner index with IgM seropositivity
Total
containers
searched
Total
containers
positive
Container
index (CI)
IgM
seropositivity
July
37
5
13.5%
13.1%
August
34
8
23.5%
19.6%
September
37
22
59.45%
32.6%
October
51
27
52.94%
34.7%
Month
Table 3: Breeding preference ratio of the vector larvae
Container with
water
X (%)
Container with
larvae
Y (%)
BPR (Y/X)
Discarded tyres
120
75.5
54
87.1
1.15
Plastic buckets
16
10
5
8
0.8
Metal drums
4
2.5
1
1.6
0.64
Earthen pot
19
12
2
3.3
0.28
Total
159
100
62
100
Container types
101
Figure 3: Relation between serology and entomological results
70
18
16
60
no. of DV cases
CI
14
12
50
10
40
8
30
6
20
4
10
2
0
July
August
September
October
0
Discussion
It is plausible to assume that DENV could have been introduced into Nepal from India, due
to the open border between the two countries. This hypothesis is further supported with the
finding of nucleotide sequences of the Nepalese dengue strain that have been described to
be very similar to the dengue strains circulating in India.12,26 The emergence and reemergence
of dengue is directly related to the geographic distribution and increase in density of the
mosquito vectors. The factors that promote vector proliferation, including environmental
conditions (temperature, humidity and altitude), poor sanitation or availability of potential
breeding sites are important constituents of spreading dengue.27 An investigation of the
seasonal distribution during April 2009 – March 2010 of potential artificial breeding habitats
of Ae. albopictus in urban agglomeration of Kathmandu and Lalitpur districts of Nepal was
performed. The breeding preference ratio during all seasons was highest for discarded tyres
lying outdoors in both Kathmandu and Lalitpur districts. Among nine container types searched
and examined, 95% of discarded tyres were found positive for Ae. albopictus larvae and
pupae, followed by metal drums (2%) and plastic drums (1.25%).13 This entomological study,
recommended in various countries endemic for dengue, was primarily conducted to measure
the relative presence of disease-carrying arthropod vectors to emphasize its the usefulness
for identifying possible causes of dengue outbreaks28, for identifying key containers29,30 and
for identifying new breeding sites of vectors.
102
In addition, the study was conducted in Chitwan because it is the central part of
Nepal and many people from Eastern to the Far Western Regions travel in and through the
district. In addition, the district was the most affected district of 2010 epidemics with 739
reported dengue cases (data obtained from District Public Health Office, Chitwan). Further,
previous studies have been performed in this region to assess for the serological, clinical and
hematological results31 but the entomological studies have not been reported so far.
Comparatively higher numbers of dengue positive cases were observed in September
and October than in July and August, which is in accordance with the entomological finding
as CI is also high in September and October. As the CI is the proportion of larvae positive
containers, higher CI suggest high numbers of mosquitoes were active in these two months
for their life cycle and transmission of disease. During the outbreak of dengue in Nepal in
2006, 75% of DF cases were reported in October and a few positive cases in September and
November.32 A high number of dengue cases was recorded in October and November in
the epidemic of 2010.33 A similar result was obtained in India in 2003 where the maximum
number of cases 583 (65.3%) was reported in October.34 There was also an increase in the
number of samples received in the post-monsoon period with a peak in the second and
third week of October.35
Unusually heavy rainfall subsequently led to a decrease in temperature during the latter
part of the monsoon period. The temperature showed a decline and remained almost constant
during August (33.8 °C), continuous heavy rainfall subsequently led to a further decrease in
the temperature during September to 33.3 °C (data obtained from Department of Hydrology
and Meteorology). This might have caused an increase in the number of dengue cases in the
post-monsoon period. It can be further explained by the fact that the stagnant fresh water
during the post-rainy seasons favoured the breeding of the vector mosquitoes.36 As regards
the seasonal prevalence, it is evident from the result that dengue cases started from July with
the maximum number of cases in post-monsoon period.
BPR estimates the degree of breeding affinity of dengue vectors towards a particular
container type. In this study four different types of containers were searched for the presence
of immature dengue vectors, which revealed that discarded tyres followed by old plastic
buckets, metal drums and earthen pots were the preferred breeding habitat for the vector
mosquito. Similar studies conducted in Philippines37 and in India38 also recorded the highest
positivity of immature dengue vectors in discarded tyres. Growing urbanization which
demands excessive use of auto mobiles and lack of discarded tyre management system is the
main cause of rampant presence of discarded tyres in urban settings, as Chitwan is the central
region of Nepal and is the hub for transportation. Discarded tyres were mainly placed near
automobile workshops, above the steel tin roof for support in small houses of slum area and
small shops with steel tin roof. Discarded tyres unlike other containers hold stagnant water
and remain untouched for a long time making it a favourable and safe place of mosquito
103
breeding even in the rainy season. The potential of other artificial containers for breeding by
vectors was found to be less during the study period. This might be due to local awareness
campaigns in the region following the heavy rain to destroy the breeding habitat of vectors.
Performing a repeat survey afterwards to check for an improvement in the larval indices may
help determine the effectiveness of the campaigns. The environmental education strategies
aimed at reducing potential breeding habitats of Aedes mosquitoes must be innovative. If
the larvae of this vector remain in even a few households, it will be sufficient to produce
the winged form of the mosquito that is capable of infesting neighbouring houses, putting
the surrounding population at risk.
The limitations of the study include the use of simple tools for the identification of
vector mosquitoes, short duration of the study and the small sample size. Further, the use
of single serum sample for ELISA instead of paired sera and the unavailability of Reverse
Transcriptase - Polymerase Chain Reaction (RT-PCR), Hemagglutination Inhibition (HI) tests
and testing for NS1 antigen in the field was a major limitation of our study. In spite of these
limitations, the results of this study are potentially helpful in suggesting that used tyres are the
major cause of proliferation of the vector mosquitoes. The identification of other biotic and
abiotic factors responsible for the process was beyond the scope of the study. The results of
the study regarding the breeding sites and the seasonal patterns of the disease and vectors
can help the local and national health authorities to formulate different programme aimed
to minimize the effect of dengue in the near future.
Conclusion
The entomological study showed a higher number of Aedes larvae in the post monsoon period
which is associated with the higher number of dengue cases in the post-monsoon period.
Determination of BPR revealed the degree of larval breeding affinities toward particular
container type and the results indicate discarded tyres were the preferable breeding habitat
for the dengue vector. So, a proper vector management programme and environmental
education strategies are essential for reducing vectors in future.
Acknowledgements
We thank the staff of the Everest International Clinic and Research Centre, Kathmandu
and the Natural History Museum, Swayambhu, Kathmandu, for their technical help. We
are extremely grateful to the medical superintendents, doctors, nurses, staff and patients of
the respective hospitals for their kind support during the study. We would also like to thank
Mr Jitendra Balami and Mr Subarna Subedi for their assistance in sample collection.
104
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107
Short Note
The first tetravalent dengue vaccine is poised to
combat dengue
Usa Thisyakorna, Maria Rosario Capedingb & Sri Rezeki Hadinegoroc
Faculty of Medicine, Chulalongkorn University and consultant to Faculty of Tropical Medicine,
Mahidol University, Department of Health, Bangkok Metropolitan Administration, HRH Princess
Maha Chakri Sirindhorn Medical Center, Faculty of Medicine, Srinakarinwirot University and Faculty
of Medicine, Thammasat University
a
b
Professor, Research Institute for Tropical Medicine, Muntinlupa City, Philippines
Staff member, Infection and Tropical Pediatric Division, Department of Child Health, Medical
School, University of Indonesia, Chair of Pediatric Research Centre, Department of Child Health,
Medical School, University of Indonesia, and Chair of Indonesia Technical Advisory Group on
Immunization (ITAGI), Indonesian Ministry of Health
c
Dengue, along with the mosquito vectors that transmit it, is now endemic in over 120
countries throughout the tropical and subtropical regions of the world.1-3 It is nearly ubiquitous
in the tropics and has continued to emerge or become hyperendemic in new areas as the
range of the Aedes mosquito vectors continue to expand. Global dengue transmission has
increased at least 30-fold in the past 50 years4 so that approximately 3.6 billion people are
currently at risk for dengue infection.3 The total number of infections per year has been
estimated at 390 million, of which 96 million are symptomatic; 500 000 are severe requiring
hospitalization, and 20 000 are fatal.1-3
The burden borne by the health and medical resources of affected countries is enormous
but nowhere is the burden greater than in the South East Asia (SEA) and the Western Pacific
Regions of WHO where the incidence of dengue continues to increase, causing larger
and more geographically dispersed outbreaks in seasonal or cyclical epidemic patterns.1,5,6
Currently over 70% of the global population at risk for dengue lives in these Regions.7
A recent study to ascertain the true global burden of dengue found most estimated rates
to be substantially higher than those currently reported to WHO (see Table 1). India and
China are estimated to account for up to 40% of the global burden.1 The estimated annual
economic burden for South-East Asia, excluding prevention and vector control, was nearly
$1 billion or $1.65 per capita, with two countries (Indonesia and Thailand) accounting
for over 60% of this burden. Dengue infections led to an annual estimated average of
372 DALYs per million inhabitants, with about 45% of the burden in Indonesia and 18%
in the Philippines. The dengue burden ranks higher than 17 other conditions, including
#
E-mail: uthisyakorn@gmail.com
108
The first tetravalent dengue vaccine is poised to combat dengue
Table 1: Model-based estimated numbers of apparent and inapparent dengue infections
per year and estimated global burden rank for countries in South-East Asia and Western
Pacific Regions, 2010.1
Annual apparent
infections, mean
Annual
inapparent
infections, mean
WHO
estimate
32 541 392
99 692 319
12 484
1
Indonesia
7 590 213
23 009 108
130 575
2
China
6 523 946
20 062 625
186
3
Philippines
3 076 863
9 339 425
77 598
5
Bangladesh
4 097 833
12 581 091
568
7
Viet Nam
2 603 443
7 965 912
110 217
9
Thailand
1 903 694
5 823 012
57 589
11
Malaysia
983 619
2 969 671
45 664
12
Myanmar
992 954
3 056 420
16 824
14
Sri Lanka
673 544
2 042 226
22 902
18
Singapore
180 895
543 970
5 631
23
Nepal
571 773
1 769 014
13
26
Hong Kong
304 782
924 234
0
32
Cambodia
404 533
1 243 325
11 247
33
Papua New Guinea
89 943
279 597
9
70
Macao
23 158
69 833
3
78
Samoa
16 759
51 096
226
90
Fiji
24 969
76 371
759
93
Brunei Darussalam
12 732
38 421
116
94
9 879
29 763
968
95
14 586
45 345
278
97
Maldives
6 372
19 735
933
103
New Caledonia
7 423
22 609
3 301
105
Solomon Islands
8 250
25 552
1
107
Country
India
French Polynesia
Timor-Leste
Absolute
global ranka
*Adapted from Bhatt et al. 2013 (reference 1) Supplementary Table T4, Apparent and Inapparent mean and
confidence (95%) burden estimates per country. aThe global rank was determined by the rank index of the difference
(upper limit minus the lower limit) in the 95% confidence interval of the mean annual apparent infections.
109
Japanese encephalitis and hepatitis B5. In the absence of a dengue vaccine, the measures
for controlling dengue in these regions and elsewhere have focused primarily on diagnosis
and case management, integrated surveillance, and vector management.4,7 Despite current
efforts the disease has continued to spread and cause epidemics, pointing to the need
to increase these efforts and to the need for a vaccine. Developing an effective vaccine
against all four dengue virus serotypes has been a tremendous challenge, and not without
theoretical safety concerns associated with antibody-dependent enhanced disease. Now,
after years of research a tetravalent vaccine was found to be safe and efficacious in a Phase
3 study (clinicaltrials.gov NCT01373281). The CYD-TDV live attenuated dengue vaccine
being developed by Sanofi Pasteur has demonstrated clinical efficacy and a good safety
profile in two recent large-scale clinical trials,9,10 with the results of another phase 3 trial in
Latin America due shortly (clinicaltrials.gov NCT01374516). In the pivotal phase 3 study
conducted in over 10 000 subjects in five Asian-Pacific countries (Indonesia, Malaysia, the
Philippines, Thailand, and Viet Nam), the tetravalent vaccine showed an overall efficacy of
56.5% [95% CI 43.8−66.4] against clinically apparent dengue caused by any serotype10.
During the 25 months observation of the study, the observed efficacy was consistent across
countries and appeared to vary by serotype (between 34.7% and 72.4%) and by age.
Importantly, there was no evidence of disease enhancement in breakthrough episodes and
a reduction of 67.2% [95% CI 50.3−78.6] in hospitalization was observed and 88.5% (95%
CI 58.2−97.9) reduction against dengue haemorrhagic fever. These results emphasize the
potential public health value of the vaccine in substantially reducing the burden and cost of
dengue across different epidemiological settings.
WHO has taken strides to reduce dengue morbidity and mortality, and since 2012
has focused efforts toward three objectives: reducing dengue mortality by at least 50% by
2020 and dengue morbidity by at least 25% by 2020, compared with 2010 baseline rates;
and estimating the true burden of disease by 2015.7 Attaining these objectives will require
confronting the disease on all fronts. With early diagnosis along with timely and appropriate
clinical case management, mortality rates of severe dengue have decreased and are now
<1% in many countries, although they can be substantially higher during epidemics.4 Dengue
morbidity and rate of hospitalizations, however, remain substantial economic burdens.
Increasing surveillance efforts and improving the integration of surveillance data in health care
systems can help identify outbreaks more quickly and reduce delays in outbreak management,
while adequate preparation for outbreaks can facilitate containment and minimize the scale
of epidemics. Integrated vector management programmes involving strategic approaches to
vector control, such as community advocacy and awareness, collaboration with private and
public health sectors, and evidence-based interventions can reduce mosquito populations
and dengue transmission. However, to date, these programmes have failed to prevent the
increase in dengue cases and other new tools or approaches are urgently needed which can
be monitored and sustained for several years with community involvement.
110
A dengue vaccine could greatly alter the disease landscape, but this goal can only be
realized if the many challenges to its implementation are addressed effectively.11 We have
waited a long time for an effective intervention against dengue. Informed decisions must be
made for each setting to determine dengue vaccination can be implemented into existing
national vaccinations programmes with catch-up campaigns; optimal vaccination strategies
must be defined and post-approval safety and efficacy monitored. Countries need to plan
for the vaccine introduction, in particular, to identify priority target groups and how the
vaccine will complement existing integrated vector management, and to strengthen dengue
surveillance, which will be essential to assess the appropriate implementation of dengue
vaccination / prevention strategy for each epidemiological setting.
It is good news that a safe, effective dengue vaccine is on the horizon. While this stands
to be a critically important achievement in the fight against dengue, we need to understand
how to implement this new tool effectively and this will require firm commitments from all
affected countries if the WHO objectives are to be met.
Declaration
U. Thisyakorn, M. R. Capeding and S.R. Hadinegoro received a principle investigator research
grant for the CYD14 dengue vaccine trial by Sanofi Pasteur.
Prof Thisyakorn is supported by grants from Children’s Hospital Foundation, Thailand; the
Ministry of University Affairs, Thailand; the Faculty of Medicine, Chulalongkorn University;
the Rockerfeller Foundation, USA; the Centers for Disease Control, USA; UNICEF; the
Pediatrics AIDS Foundation; amfAR, USA; UNAIDS; WHO; the Ministry of Foreign Affairs,
Thailand; UNDP.
The authors thank Kurt Liittschwager (4Clinics), supported by Sanofi Pasteur, for assistance
in preparing the first draft.
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Rusmil K, Wirawan DN, Nallusamy R, Pitisuttithum P, Thisyakorn U, Yoon IK, van der Vliet D, Langevin
E, Laot T, Hutagalung Y, Frago C, Boaz M, Wartel TA, Tornieporth NG, Saville M, Bouckenooghe A;
CYD14 Study Group. Clinical efficacy and safety of a novel tetravalent dengue vaccine in healthy
children in Asia: a phase 3, randomised, observer-masked, placebo-controlled trial. Lancet. 2014 Oct
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[11]Thisyakorn U, Capeding MR, Goh DY, Hadinegoro SR, Ismail Z, Tantawichien T, Yoksan S, Pang T.
Preparing for dengue vaccine introduction in ASEAN countries: recommendations from the first ADVA
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112
Short Note
Trends of imported dengue fever cases in Japan,
2010 to 2013
Meng Ling Moi1, Akira Kotaki1, Shigeru Tajima1, Makiko Ikeda1, Kazumi Yagasaki1,
Chang-kweng Lim1, Hitomi Kinoshita2 , Eri Nakayama1, Yuka Saito1, Ichiro Kurane3,
Kazunori Oishi2, Masayuki Saijo1, Tomohiko Takasaki1,#
Department of Virology I, National Institute of Infectious Diseases, Tokyo, Japan.
1
Infectious Disease Surveillance Center, National Institute of Infectious Diseases, Tokyo, Japan.
2
National Institute of Infectious Diseases, Tokyo, Japan.
3
Dengue fever and dengue hemorrhagic fever is a major public health threat in the tropical
and subtropical regions. The disease is estimated to infect 400 million people annually and
a third of the world population is at risk of developing the disease.1 The rapid increase in
dengue cases has been speculated to be related to factors including increased population
movement, urbanization and increased international travels. Autochthonous transmission of
the disease has also been documented in non-endemic countries including France, Nepal,
Bhutan and Croatia. Endemic dengue virus (DENV) transmission was last confirmed in Japan
during a series of outbreaks from 1942 to 1944.2,3 Dengue was reported in Nagasaki in 1942,
and soon spread north to other densely populated cities including Hiroshima and Osaka,
resulting in an epidemic of 200,000 cases. Recently, the number of imported dengue cases
has increased; from 92 cases in 2009 to 249 cases in 2013.4,5,6 In this report, we present the
demographic features of imported dengue fever and dengue hemorrhagic fever cases in Japan
from 2010 to 2013, and cases that were confirmed at the national research facility of the
Ministry of Health, Labour and Welfare, the National Institute of Infectious Diseases, Japan.
The number of imported cases has increased 8-folds from 32 cases in 2003 to 249 cases
in 2013 (Figure 1). Concurrently, the number of dengue hemorrhagic fever cases has increased
5-folds from 2 cases in 2003 to 11 cases in 2013. Annually, the number of Japanese overseas
travelers has increased from 16.6 million in 2010 to 17.5 million in 2013. The number of
dengue fever patients was lowest in 2011 during the 4-year period, at 113 cases, as compared
to 244 cases in 2010, 221 cases in 2012 and 249 cases in 2013. The decrease in number
of patients coincident with the decrease in the percentage of Japanese overseas travelers as
compared to 2010, during (March, -9.1%) and in the months (April to June, -8.1% to -3.5%)
#
E-mail: takasaki@nih.go.jp
113
Trends of imported dengue fever cases in Japan, 2010 to 2013
following the Tohoku earthquake and tsunami in 2011, although other factors including
milder disease outbreaks in endemic regions may be involved in the decrease in number
of dengue patients in 2011. A high percentage of the imported cases were confirmed in
the densely populated Tokyo metropolitan and Osaka prefecture; 36.3% (41/113) in 2011,
39.8% (88/221) in 2012 and 40.9% (102/249) in 2013 (Table 2). In 2013, an autochthonous
DENV infection was reported in a German traveler from Japan.7 The German traveler had
visited Ueda (Nagano, 19–21 August), Fuefuki (Yamanashi, 21–24 August), Hiroshima
(24–25 August), Kyoto (25–28 August) and Tokyo (28–31 August) during her two-week trip to
Japan, and returned by direct flight to Germany. Although she claimed to have experienced
mosquito bites in Yamanashi, there were no confirmed imported dengue cases in Yamanashi
for two-consecutive years, 2012 and 2013 (Table 2). Further studies would be required
to determine the risk of DENV transmission in these areas, particularly in areas with high
population density and imported dengue cases.
Table 1: Number of dengue fever cases confirmed at the National Institute of Infectious
Diseases (NIID), Japan, 2010–2013
Cases examined and confirmed at NIID
Year
No. of Cases
Examined
No. of Cases
Confirmed
Positive Rate
(%)
Number of imported dengue
cases in Japan
(% confirmed cases in NIID)
2010
183
124
68
244 (51)
2011
129
57
44
113 (50)
2012
231
101
44
221 (46)
2013
262
113
43
249 (45)
Total
805
395
49
827 (48)
Table 2: Number of imported dengue cases in Japan according to prefecture
Rank
(Population)
1
2
3
4
5
6
7
8
9
10
11
114
Prefecture
Tokyo
Kanagawa
Osaka
Aichi
Saitama
Chiba
Hyogo
Hokkaido
Fukuoka
Shizuoka
Ibaraki
Population*
(in thousand)
13 159
9 048
8 865
7 410
7 194
6 216
5 588
5 506
5 071
3 765
2 969
Total number of imported dengue cases
Year
2011
2012
2013
25
56
66
10
19
16
16
32
36
9
13
14
4
5
7
4
14
20
4
8
9
10
5
4
3
7
12
5
6
4
1
3
5
Rank
(Population)
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
Prefecture
Hiroshima
Kyoto
Niigata
Miyagi
Nagano
Gifu
Fukushima
Gunma
Tochigi
Okayama
Mie
Kumamoto
Kagoshima
Yamaguchi
Ehime
Nagasaki
Shiga
Nara
Okinawa
Aomori
Iwate
Oita
Ishikawa
Yamagata
Miyazaki
Toyama
Akita
Wakayama
Kagawa
Yamanashi
Saga
Fukui
Tokushima
Kochi
Shimane
Tottori
Total
Population*
(in thousand)
2 860
2 636
2 374
2 348
2 152
2 080
2 029
2 008
2 007
1 945
1 854
1 817
1 706
1 451
1 431
1 426
1 410
1 400
1 392
1 373
1 330
1 196
1 169
1 168
1 135
1 093
1 085
1 002
995
863
849
806
785
764
717
588
128 057
Total number of imported dengue cases
Year
2011
2012
2013
1
3
3
3
7
11
0
0
0
0
4
2
0
2
1
1
0
4
0
1
0
2
2
2
0
3
4
0
1
0
1
4
0
0
1
2
1
1
5
1
1
0
0
0
1
0
3
1
1
2
0
0
5
2
5
1
1
0
1
0
1
1
0
2
1
1
0
1
1
0
0
1
0
2
3
0
0
0
0
0
0
0
1
3
1
2
2
1
0
0
0
0
1
0
1
2
1
1
0
0
0
3
0
1
0
0
0
0
113
221
249
* Population consensus of 2010 (Statistics Bureau, Ministry of Internal Affairs and Communications, Japan).
115
Because of global-wide DENV epidemics and the presence of DENV vector, Aedes
albopictus mosquitoes in Japan, dengue fever is a disease that requires high priority in
surveillance and disease control. Dengue is a notifiable disease as required by the Infectious
Disease Control Law. Between 2010 and 2013, a total of 827 cases of dengue fever were
confirmed in Japan. Of the 827 cases, 395 cases (48%) were confirmed at the National Institute
of Infectious Diseases between 2010 and 2013. The disease was confirmed by detection of
viral genomic RNA by RT-PCR in serum samples or urine samples8, NS1 antigen9 and a 4-fold
increase in antibody titers.10 Of the 395 cases, a high percentage (96.7%) of imported dengue
cases had recent travel history in Asian regions, followed by Americas (1.3%), Africa (1.3%)
and Oceania (0.8%). A total of 287 cases (287/382, 72.7%) had returned from Indonesia
(114/328, 28.9%), 86 cases from Philippines (86/382, 21.8%), 44 cases from Thailand (44/382,
11.1%) followed by 43 cases from India (43/382, 10.9%) (Table 3). The incidence of dengue
fever in Japanese travelers returning from Indonesia was 10.5; Thailand 1.2; Philippines
4.2, and India 14.8 per 100 000 travelers in 2010. Interestingly, 5 cases of dengue fever
was confirmed in travelers from Benin11, Ghana, Kenya and Tanzania12, suggesting dengue
outbreaks in these regions. Additionally, a traveler returning from Australia was confirmed
with dengue fever in 2013. Our data concurs with those of other investigators that wider
geographic regions are affected with dengue epidemics.1
Table 3: Travel destinations of travelers returning to Japan, 2010–2013
Year
2010
2011
2012
2013
Asia
116
Total cases+
(% of total cases)
382 (96.7)
Bangladesh
1
4
1
0
6 (1.5)
Cambodia
4
2
5
3
14 (3.5)
East Timor
1
0
4
0
5 (1.3)
India
25
6
10
2
43 (10.9)
Indonesia
44
13
16
41
114 (28.9)
Laos
4
0
0
0
4 (1.0)
Malaysia
2
2
1
2
7 (1.8)
Maldives
0
2
0
1
3 (0.8)
Myanmar
0
0
3
3
6 (1.5)
Pakistan
1
2
0
0
3 (0.8)
Philippines
15
16
34
21
86 (21.8)
Saudi Arabia
0
0
0
2
2 (0.5)
Singapore
0
1
1
2
4 (1.0)
Sri Lanka
1
0
3
3
7 (1.8)
Thailand
12
4
10
18
44 (11.1)
Vietnam
4
2
2
2
10 (2.5)
Year
Undetermined*
2010
2011
2012
2013
Total cases+
(% of total cases)
5
2
9
8
24 (6.1)
Americas
5 (1.3)
Brazil
0
1
0
0
1 (0.3)
Jamaica
0
0
1
0
1 (0.3)
Paraguay
1
0
0
1
2 (0.5)
Venezuela
1
0
0
0
Africa
1 (0.3)
5 (1.3)
Benin
1
0
0
0
1 (0.3)
Ghana
0
0
0
1
1 (0.3)
Kenya
0
0
0
1
1 (0.3)
Tanzania
2
0
0
0
2 (0.5)
Oceania
3 (0.8)
Australia
0
0
0
1
1 (0.3)
Marshall Islands
0
0
1
0
1 (0.3)
New Caledonia
0
0
0
1
1 (0.3)
124
57
101
113
395+
Total cases
*Undetermined indicates that traveler visited multiple countries during stay and site of infection could not be
determined, +total number of dengue fever cases confirmed at the National Institute of Infectious Diseases, Japan.
Viremic travelers may present a route of introducing DENV to non-endemic regions.
Of 375 travelers, 270 (72.0%) travelers were viremic upon their return to Japan from 2010–
2013. DENV-1 was detected in 131 cases of dengue fever (48.5%), followed by DENV-2
(68/270, 25.2%), DENV-3 (47/270, 17.4%) and DENV-4 (24/270, 8.9%) (Table 4). Amongst
the 395 dengue cases in 2010–2013, a high percentage (72.2%, 285/395) of travelers were
from the age group of 20–49 (Figure 2). The higher percentage of travelers at the age group
of 20–49 returning with dengue fever is likely to be activity-related. The percentage of all
Japanese overseas travelers at the age group of 20–49 was constant at 55.3% in 2010, 56.0%
in 2011 and 55.6% as compared to other age-groups.13 The youngest traveler confirmed
with DENV infection was a one year-old infant and the oldest was 90 years old. Most of
the travelers (62.5%, 247/395) were males, the percentage of female travelers with dengue
fever was lower at 37.5% (148/395; male:female ratio=1.7). The higher percentage of male
travelers returning with dengue fever is also likely to be activity-related; the male:female
ratio of travelers were constant at a ratio of 1.2:1, from 2010 to 2012.13 Additionally, 49.6%
(196/395) of travelers were confirmed with acute dengue fever between August and October
(Figure 3). The period coincides with an increase in travelers going overseas during the
summer vacation. Our data demonstrated that a high percentage of travelers were viraemic
upon return, and that male travelers at the age group of 20–49 years old are potentially at a
117
higher risk of spread of DENV infection. A potential DENV vector mosquito, Ae. albopictus,
is highly active during summer and autumn, but activity is absent during winter in Japan.
Due to high activity of vector mosquito during summer and autumn, and the high proportion
of travelers returning with dengue fever during this period, dengue needs higher attention
with regard to disease management and control, particularly during the summer and autumn
period in Japan.
Table 4: Dengue serotypes confirmed in Japan, 2010–2013*
Dengue virus
serotype
Year
2010
2011
2012
2013
Total (Percentage
of total, %)
DENV-1
35
22
27
47
131 (48.5)
DENV-2
27
8
17
16
68 (25.2)
DENV-3
13
6
14
14
47 (17.4)
DENV-4
10
2
4
8
24 (8.9)
Total
85
38
62
85
270
*All cases were confirmed at the National Institute of Infectious Diseases, Japan.
There are currently no endemic dengue cases confirmed in Japan, with the exception
of a dengue fever case in a German traveler returning from Japan in 2013.7 Emergence of
dengue in geographically diverse areas, presence of DENV vector mosquito, and annual
reoccurrence of DENV in previously non-endemic regions including Taiwan14 and Nepal15,
suggests the urgent need of higher awareness and attention with regard to identification of
dengue cases, not only in travelers, but of potential local dengue outbreaks in non-endemic
regions.
Acknowledgements
We would like to thank the staff of local health centers and public health institutes/laboratories
all over the country for regularly reporting dengue cases and kindly answering our inquiries.
This work was supported by grants from Research on Emerging and Re-emerging Infectious
Diseases H23-shinkou-ippan-010), from the Ministry of Health, Labour and Welfare, Japan.
References
The global distribution and burden of dengue. Nature. 2013;496(7446):504-7.
[2] Hotta S. Dengue epidemics in Japan, 1942-1945. J Trop Med Hyg. 1953;56(4):83.
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[3] Konishi E, Kuno G. In memoriam: Susumu Hotta (1918-2011). Emerg Infect Dis. 2013;19(5):843-4.
[4] Japan, Ministry of Health, Labour and Welfare, Department of Virology 1, National Institute of Infectious
Diseases. http://www0.nih.go.jp/vir1/ NVL/dengue.htm - accessed 18 December 2014.
[5] Takasaki T, Kotaki A, Tajima S, Omatsu T, Harada F, C-K Lim, ML Moi, Ito M, Ikeda M, Kurane I.
Demographic features of imported dengue fever and dengue haemorrhagic fever in Japan from 2006
to 2009. Dengue Bulletin. 2011;35:217-22.
[6] Nakamura N, Arima Y, Shimada T, Matsui T, Tada Y, Okabe N. Incidence of dengue virus infection
among Japanese travelers: 2006 to 2010. Western Pac Surveill Response J. 2012;3(2):39-45. http://
www.ncbi.nlm.nih.gov/pmc/articles/ PMC3729080/ - accessed 18 December 2014.
[7] Schmidt-Chanasit J, Emmerich P, Tappe D, Günther S, Schmidt S, Wolff D, Hentschel K, Sagebiel D,
Schöneberg I, Stark K, Frank C. Autochthonous dengue virus infection in Japan imported into Germany,
2013. Euro Surveill. 2014;19(3):pii=20681. http://www.eurosurveillance.org/images/dynamic/EE/
V19N03/art20681.pdf - accessed 18 December 2014.
[8] Hirayama T, Mizuno Y, Takeshita N, Kotaki A, Tajima S, Omatsu T, Sano K, Kurane I, Takasaki T. Detection
of dengue virus genome in urine by real-time reverse transcriptase PCR: a laboratory diagnostic method
useful after disappearance of the genome in serum. J Clin Microbiol. 2012;50(6):2047-52.
[9] Moi ML, Omatsu T, Tajima S, Lim CK, Kotaki A, Ikeda M, Harada F, Ito M, Saijo M, Kurane I, Takasaki T.
Detection of dengue virus nonstructural protein 1 (NS1) by using ELISA as a useful laboratory diagnostic
method for dengue virus infection of international travelers. J Travel Med. 2013;20(3):185-93.
[10]World Health Organization. Dengue. guidelines for diagnosis, treatment, prevention and control.
Geneva: WHO, 2009. http://www.who.int/rpc/guidelines/ 9789241547871/en/ - accessed 18 December
2014.
[11]Ujiie M, Moi ML, Kobayashi T, Takeshita N, Kato Y, Takasaki T, Kanagawa S. Dengue virus type-3
infection in a traveler returning from Benin to Japan. J Travel Med. 2012;19(4):255-7.
[12]Moi ML, Takasaki T, Kotaki A, Tajima S, Lim CK, Sakamoto M, Iwagoe H, Kobayashi K, Kurane I.
Importation of dengue virus type 3 to Japan from Tanzania and Cote d’Ivoire. Emerg Infect Dis.
2010;16(11):1770-2.
[13]Japan National Tourism Organization, http://www.jnto.go.jp/jpn/news/ data_info_listing/index.html accessed 18 December 2014.
[14]Huang JH, Liao TL, Chang SF, Su CL, Chien LJ, Kuo YC, Yang CF, Lin CC, Shu PY. Laboratory-based dengue
surveillance in Taiwan, 2005: a molecular epidemiologic study. Am J Trop Med Hyg. 2007;77(5):903-9.
[15]Pandey BD, Nabeshima T, Pandey K, Rajendra SP, Shah Y, Adhikari BR, Gupta G, Gautam I, Tun MM,
Uchida R, Shrestha M, Kurane I, Morita K. First isolation of dengue virus from the 2010 epidemic in
Nepal. Trop Med Health. 2013;41(3):103-11.
119
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
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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);
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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.
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121

Dengue Bulletin – Volume 38

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