Dengue: Lessons, Challenges and New Approaches · 2012-10-18 · The goal of the journal is to ... reported incident dengue fever cases in six Asian countries 17 Anker M and Arima

Western Pacifi c Surveillance and Response

Open access journal with continuous publication

Western Pacifi c Surveillance and Response (WPSAR) is an open access journal dedicated to the surveillance of and response to public health events The goal of the journal is to create a platform for timely information sharing both within our region and globally to enhance surveillance and response activities WPSAR is a continuous publication which means articles will be published online as soon as they have completed the review and editing process Every three months articles will be batched for a print issue

EditorialChallenges in dengue surveillance and control 1Ng LC

Regional AnalysesEpidemiologic update on the dengue situation in the Western Pacifi c Region 2010 4Arima Y and Matsui T on behalf of Emerging Diseases Surveillance and Response Division of Health Security and Emergencies World Health Organization Regional Offi ce for the Western Pacifi c

Challenges and future perspective for dengue vector control in the Western Pacifi c Region 9Chang MC Christophel EM Gopinath D and Abdur RM on behalf of Malaria Other Vectorborne and Parasitic Diseases World Health Organization Regional Offi ce for the Western Pacifi c

Male-female differences in the number of reported incident dengue fever cases in six Asian countries 17Anker M and Arima Y

Original Research Epidemiological characteristics of the 2005 and 2007 dengue epidemics in Singapore - similarities and distinctions 24Ler TS Ang LW Siew GSL Ng LC Tai JC James L and Goh KT

Other topicsOriginal Research Surveillance of hospitalizations with pandemic A(H1N1) 2009 infl uenza infection in Queensland Australia 30Phung H Beard F Selvey C Appuhamy R and Birrell F

Western Pacifi c Surveillance and Response Instructions to authors 36

Dengue Lessons Challenges and New Approaches

Volume 2 Number 2 2011 Pages 1 - 37p-ISSN 2094-7321 e-ISSN 2094-7313

Photo by Kevin Hamdorf

wwwwprowhointwpsarWPSAR Vol 2 No 2 2011 | Dengue Lessons Challenges and New Approaches

EDITORIAL TEAM

Takeshi KasaiExecutive Editor

Emma FieldCoordinating Editor

Elizabeth MangaliAssistant Editor

Associate Editors

Jorge Mendoza AldanaJenny Bishop

Nobuyuki NishikioriJeffrey PartridgeArturo Pesigan

Manju RaniDongbao Yu

Western Pacific Surveillance and Response (WPSAR) is a publication managed by the World Health Organization Regional Office for the Western Pacific

To contact us

Western Pacific Surveillance and ResponseWorld Health Organization Office for the Western Pacific RegionUnited Nations Avenue1000 Manila Philippineswpsarwprowhointwwwwprowhointwpsar

Copyright noticecopy World Health Organization 2010

p-ISSN 2094-7321e-ISSN 2094-7313

All rights reserved The information presented in the various pages of this journal is issued by the World Health Organization for general distribution and is protected under the Berne Convention for the Protection of Literature and Artistic Works under national laws on copyright and neighbouring rights

The World Health Organization does not warrant that the information contained in this publication is complete and correct and shall not be liable for any damages incurred as a result of its use

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Disclaimer

The designations employed and the presentation of the information in this publication do not imply the expression of any opinion whatsoever on the part of the World Health Organization concerning the legal status of any country territory city or area or of its authorities or concerning the delimitation of its frontiers or boundaries

The mention of specific companies or of certain manufacturers products does not imply that they are endorsed or recommended by the World Health Organization in preference to others of a similar nature that are not mentioned Errors and omissions excepted the names of proprietary products are distinguished by initial capital letters

WPSAR Vol 2 No 2 2011 | doi 105365wpsar201122001wwwwprowhointwpsar 1

Ng Lee Ching Challenges in dengue surveillance and control

Challenges in dengue surveillance and controlLee Ching Ng

Environmental Health Institute National Environment Agency Singapore (e-mail NG_Lee_Chingneagovsg)doi 105365wpsar201122001

RESURGENCE OF DENGUE

Globally the challenge posed by dengue has escalated at an astonishing rate in the last three decades with no sign of abating It is estimated that dengue affects at least 50 million ndash 100 million people every year With more than 120 dengue-endemic countries 36 billion people are at risk of infection1 More than 70 of those at risk reside in the Asia Pacific region making this region an epicentre of dengue activity

In addition to making a comeback in places such as the Americas and Singapore where dengue was previously successfully controlled for decades23 the virus has also breached the subtropical-temperate barrier as it claims new territories In the last decade dengue transmission has extended its reach into places as far north as Nepal4 Ningbo in China5 and France6 and as far south as Bueno Aires in Argentina7 The Pacific islands with much lower population densities have also not been spared with increasing dengue outbreaks since the 1970s8

The direct economic and social impact of dengue on dengue-endemic regions is high9-12 and the burden in other aspects such as the security of blood supplies is increasingly being recognized13 Denguersquos threat to travellers has also been systematically demonstrated by a 2008 study on 6957 travellers who returned ill and sought treatment from EuroTravNet centres Of those travellers 19 were diagnosed with dengue and one of the three deaths reported was due to dengue shock syndrome14

FACTORS THAT CONTRIBUTED TO THE CHALLENGE

Key contributing factors to the worldwide resurgence of dengue in the last few decades include the rise in number and size of densely populated urban cities that are conducive for the spread of the disease and

the adaptation and proliferation of dengue vectors particularly the primary carrier of dengue virus Aedes aegypti In the last three decades the number of people living in cities around the world has doubled from 17 billion to 35 billion The number is expected to rise to 5 billion by 2030 and most of this is projected to occur in Asia15 Furthermore increased global travel has facilitated the spread of the virus The resultant increase in transmission of the viruses has brought about genetic expansion of virus providing ample opportunities for successful selections of viral variants of high epidemic potential or virulence as suggested by molecular epidemiological studies on Cuba and Puerto Rico1617 The geographical expansion of the vector Aedes aegypti is also well demonstrated by its recent invasion or reinvasion into temperate regions such as Nepal and Bueno Aires in Argentina418 and into rural areas in Indonesia and Cambodia1920 The vectorial role of Aedes albopictus a mosquito that has successfully established its territory from South-East Asia to northern Asia (Japan and China) the Americas and Europe has also been clearly revealed by dengue outbreaks in many places such as Hawaii Hong Kong (China) and Ningbo China521

Dengue vaccine is not available and its development is hindered by the lack of suitable animal models and the requirement for a robust tetravalent vaccine that covers all four serotypes of dengue With only one vaccine in the third phase of clinical trial it is estimated that a dengue vaccine will not be available for at least the next seven years Vector control remains the key strategy in dengue prevention and control Unfortunately the extensive and often indiscriminate use of insecticides has resulted in a global pandemic of insecticide resistance

STRATEGY

The urban and peridomestic habitats of Aedes aegypti offer an opportunity to suppress the vector population through source reduction careful environment

Editorial

wwwwprowhointwpsar2 WPSAR Vol 2 No 2 2011 | doi 105365wpsar201122001

Ng Lee ChingChallenges in dengue surveillance and control

management and urban planning to deprive the Aedes mosquitoes of stagnant water for breeding The success of this strategy has been demonstrated in the Americas and in Singapore in the 1950s and 1960s Aedes aegypti was either eradicated or suppressed to a population that eliminated dengue or moderated dengue transmission to low endemicity However the recent resurgence has shown the limitation of the traditional strategy It calls for more innovations and a better framework for surveillance and control

INTER-EPIDEMIC SURVEILLANCE AND CONTROL

To battle with a complex disease like dengue four cornerstones are required to support a robust surveillance system human cases virus entomological and ecological surveillance22 Todayrsquos better understanding of the epidemiology of dengue coupled with technologies such as geographical information systems polymerase chain reaction rapid antigen test kits sequencing and bioinformatics have offered us an opportunity to take a holistic approach in our undertaking to suppress the resurgence of dengue

UNITED IN TACKLING EPIDEMIC DENGUE

Dengue does not respect political boundaries neither does it respect divisions of government agencies or communities Formation of linkages among those entities is critical for success of control programmes and is consistent with the Integrated Vector Management strategy promoted by the World Health Organization (WHO) Intersectoral linkage is critical to ensure that the activities of other sectors such as urban development agriculture or water resources do not compromise any vector control programme instead vector control should be an agenda of each sector The complexity of the disease also requires concerted effort among laboratory personnel of multi-disciplines field officers policy-makers and the community The stakeholders are many in the control of dengue An effective programme requires effective communications among various stakeholders with elements of feedback and data sharing The chain of events and measures that support surveillance clinical management and control is not unlike a chain of links ndash the chain is only as strong as its weakest link

Recognizing the importance of cross border-linkages the Asia Pacific Dengue Partnership was formed in March 2006 to support and facilitate effective implementation of a prevention and control strategy so as to reverse the rising trend of dengue in the Asia Pacific region Under the Partnership Member States of the Western Pacific and South-East Asia Regions joined efforts with WHO in formulating the 2008ndash2015 Bi-Regional Dengue Strategic Plan which was subsequently endorsed by the Regional Committees in September 2008 to be employed as a road map for national plans Several activities including the Asia Pacific Dengue Programme Managersrsquo Meeting and Asia Pacific Dengue Workshops have been conducted to support the Plan in knowledge exchange and capacity-building2324 The recently updated Asia Pacific Strategy for Emerging Diseases known as APSED (2010) provides a common strategic framework for countries and partners to work collectively to strengthen the national and regional disease surveillance and response systems and capacities including dengue surveillance outbreak response clinical management and risk communications25

Despite progress made many challenges remain including standardization of classification of dengue enhancement of cases vector and virus surveillance limited resources and infrastructure for surveillance and control quality of diagnostics limited access to good clinical care need for more advance entomological tools and the limited research that are eventually translated to disease prevention and management Dengue is a serious problem that is already challenging us and it threatens to be more aggressive More support attention action and synergistic collaboration among all stakeholders are urgently needed to enhance the current systems

Reference

1 Dengue in the Western Pacific Region Manila World Health Organization 2009 (httpwwwwprowhointhealth_topicsdengue accessed on 8 March 2011)

2 Koh BK et al The 2005 dengue epidemic in Singapore epidemiology prevention and control Annals of the Academy of Medicine Singapore 2008 37538ndash545 pmid18695764

3 Guzman MG Kouri G Dengue and dengue hemorrhagic fever in the Americas lessons and challenges Journal of Clinical Virology 2003 271ndash13 doi101016S1386-6532(03)00010-6 pmid12727523

4 Pandey BD et al Dengue virus Nepal Emerging Infectious Diseases 2008 14514ndash515 doi103201eid1403070473 pmid18325280



5 Xu G et al An outbreak of dengue virus serotype 1 infection in Cixi Ningbo Peoplersquos Republic of China 2004 associated with a traveler from Thailand and high density of Aedes albopictus The American Journal of Tropical Medicine and Hygiene 2007 761182ndash1188 pmid17556633

6 Gould EA et al First cases of autochthonous dengue fever and chikungunya fever in France from bad dream to reality Clinical Microbiology and Infection 2010 161702ndash1704 doi101111j1469-0691201003386x pmid21040155

7 Natiello M et al Indigenous dengue fever Buenos Aires Argentina Emerging Infectious Diseases 2008 141498ndash1499 doi103201eid1409080143 pmid18760035

8 Singh N et al Dengue in the Pacificndashan update of the current situation Pacific Health Dialog 2005 12111ndash119 pmid18181502

9 Anderson KB et al Burden of symptomatic dengue infection in children at primary school in Thailand a prospective study Lancet 2007 3691452ndash1459 doi101016S0140-6736(07)60671-0 pmid17467515

10 Beauteacute J Vong S Cost and disease burden of dengue in Cambodia BMC Public Health 2010 10521 doi1011861471-2458-10-521 pmid20807395

11 Garg P et al Economic burden of dengue infections in India Transactions of the Royal Society of Tropical Medicine and Hygiene 2008 102 570ndash577 doi101016jtrstmh200802015 pmid18402995

12 Halstead SB Suaya JA Shepard DS The burden of dengue infection Lancet 2007 3691410ndash1411 doi101016S0140-6736(07)60645-X pmid17467495

13 Ng LC Lam S Teo D Epidemiology of dengue and chikungunya viruses and their potential impact on the blood supply ISBT Science Series 2009 4357ndash367 doi101111j1751-2824200901274x

14 Field V et al EuroTravNet network Travel and migration associated infectious diseases morbidity in Europe 2008 BMC Infectious Diseases 2010 10330 doi1011861471-2334-10-330 pmid21083874

15 World Urbanization Projects the 2001 Revision Data Tables and Highlights New York United Nations Secretariat 2002

58-59 (httpwwwunorgesapopulationpublicationswup2001WUP2001Annextabpdf accessed on 5 April 2011)

16 Rodriguez-Roche R et al Virus role during intraepidemic increase in dengue disease severity Vector Borne Zoonotic Disease 2011 (httpwwwliebertonlinecomdoiabs101089vbz20100177 accessed on 5 April 2011)

17 Bennett SN et al Molecular evolution of dengue 2 virus in Puerto Rico positive selection in the viral envelope accompanies clade reintroduction Journal of General Virology 2006 87885ndash893 doi101099vir081309-0 pmid16528038

18 Avileacutes G et al Dengue reemergence in Argentina Emerging Infectious Diseases 1999 5575ndash578 doi103201eid0504990424 pmid10460181

9 Seng CM et al Community-based use of the larvivorous fish Poecilia reticulata to control the dengue vector Aedes aegypti in domestic water storage containers in rural Cambodia Journal of Vector Ecology 2008 33139ndash144 doi1033761081-1710(2008)33[139CUOTLF]20CO2 pmid18697316

20 Jumali et al Epidemic dengue hemorrhagic fever in rural Indonesia III Entomological studies The American Journal of Tropical Medicine and Hygiene 1979 28717ndash724 pmid464193

21 Effler PV et al Hawaii Dengue Outbreak Investigation Team Dengue fever Hawaii 2001ndash2002 Emerging Infectious Diseases 2005 11742ndash749 pmid15890132

22 Lee KS et al Dengue virus surveillance for early warning Singapore Emerging Infectious Diseases 2010 16847ndash849 pmid20409381

23 Asia-Pacific Dengue Programme Managers Meeting 2008 Manila World Health Organization Western Pacific Regional Office 2008 (httpwwwwprowhointinternetfilesmvpDengue_Reportpdf accessed on 8 March 2011)

24 Report on First Asia-Pacific Dengue Workshop Singapore Environmental Health Institute 2009 (httpapp2neagovsgdatacmsresource20091022145757271094pdf accessed on 8 March 2011)

25 Asia Pacific Strategy for Emerging Diseases (2010) Manila World Health Organization ndash South-East Asia Region and Western Pacific Region 2011 (httpwwwwprowhointinternetresourcesashxCSRPublicationsASPED_2010pdf accessed on 8 March 2011)

wwwwprowhointwpsar4 WPSAR Vol 2 No 2 2011| doi 105365wpsar201122005

Arima and MatsuiDengue situation in the Western Pacific

Epidemiologic update of dengue in the Western Pacifi c Region 2010Yuzo Arimaa and Tamano Matsuia on behalf of Emerging Diseases Surveillance and Reponse Division of Health Security amd Emergencies World Health Organization Regional Offi ce for the Western Pacifi cCorrespondence to Yuzo Arima (e-mail arimaywprowhoint)

a World Health Organization Regional Offi ce for the Western Pacifi c Manila PhilippinesSubmission date 13 May 2011 Publication date 27 June 2011doi 105365wpsar201122005

Regional Analysis

Dengue is an emerging vectorborne infectious disease that is a major public health concern in the Asia Pacific region Official dengue surveillance data for 2010 provided by ministries of health were summarized as part of routine activities of the World Health Organization Regional Office for the Western Pacific Based on reported data dengue has continued to show an increasing trend in the Western Pacific Region In 2010 countries and areas reported a total of 353 907 dengue cases of which 1073 died for a case fatality ratio of 030 More than 1000 cases were reported each from Australia (North Queensland) Cambodia the Lao Peoplersquos Democratic Republic Malaysia the Philippines Singapore and Viet Nam With the exception of Australia the number of reported cases in 2010 was greater than that reported in 2009 for these countries The elevated number of cases reported in 2010 in some countries such as the Philippines is likely due to several factors such as enhanced reporting and continued epidemic activity However increases in reported number of cases in other areas such as Singapore and Malaysia appear to indicate sustained epidemic activity in those countries The continued epidemic dengue activity in the Region highlights the need for timely and routine regional sharing of information

Dengue is the fastest emerging arbovirus infection in the Asia Pacific region with a high burden of this disease also borne by countries in this

region Multi-year oscillations in disease occurrence have been observed reflecting denguersquos dynamic and complex epidemiology12 Although the number of reported cases dropped to around 50 000 annually in 1999 and 2000 after the large epidemic in 1998 dengue has again increased in overall activity over the past decade During the period 2003ndash2006 the number of reported cases increased to 150 000ndash170 000 per year and since 2007 the region has consistently reported over 200 000 cases annually (Figure 1)

In 2009 there were 242 424 dengue cases and 785 dengue deaths reported in 25 of 37 countries and areas in the World Health Organizationrsquos (WHO) Western Pacific Region Countries and areas that reported more than 1000 cases were Australia (North Queensland) Cambodia French Polynesia the Lao Peoplersquos Democratic Republic Malaysia New Caledonia the Philippines Singapore and Viet Nam Cambodia the Lao Peoplersquos Democratic Republic Malaysia the Philippines Singapore and Viet Nam contributed 781 of the 785 deaths While surveillance is limited in the Pacific islands dengue transmission has been occurring as evidenced by data from the French territories of New Caledonia and French Polynesia

In 2009 14 Pacific island countries and areas reported dengue outbreaks and five reported high dengue incidence American Samoa (644100 000 population) Cook Islands (1090100 000 population) French Polynesia (922100 000 population) New Caledonia (3443100 000 population) and Tonga (263100 000 population) While dengue surveillance is not conducted in Papua New Guinea circulation of dengue virus there is well known by the importation of cases into Australia34

Through this epidemiologic update the WHO Regional Office for the Western Pacific aims to communicate the latest regional dengue situation This report is the first of its kind and the goal is to continue such communication on a routine basis and encourage the countries and areas in the Western Pacific Region to maintain their surveillance and reporting activities

METHODS

This report provides a descriptive summary of the regional dengue situation for 2010 based on data derived from indicator-based surveillance systems in the Region Particular focus is given to dengue-endemic countries where dengue surveillance systems exist (ie Cambodia the Lao Peoplersquos Democratic Republic Malaysia the Philippines Singapore and Viet Nam)


Arima and Matsui Dengue situation in the Western Pacific

Australia is also included as periodic dengue outbreaks occur in North Queensland WHO Regional Office for the Western Pacific with the assistance of WHO country offices obtains these data on a biweekly basis from ministries of health and collection of such information along with periodic risk assessment are routine activities of the Regional Office The timeliness of reporting and completeness of reporting sites and surveillance data vary by country and the latest information available is presented The Regional Office also feeds back these data to countries and areas on a biweekly basis through httpwwwwprowhointhealth_topicsdengue

RESULTS

Dengue in the Western Pacifi c Region

In 2010 Western Pacific Region countries and areas reported a total of 353 907 cases of which 1073 people died for a case fatality ratio (CFR) of 030 While incidence of dengue was largest in the Lao Peoplersquos Democratic Republic the total numbers of cases and deaths reported were largest for the Philippines (Table 1) Summarization and reporting of the 2010 dengue data from the Pacific subregion are ongoing but more than 100 cases were reported each from French Polynesia New Caledonia and Vanuatu (Table 1) While dengue is not endemic in New Zealand 51 cases were reported in 2010 all cases had overseas exposures with 12 of cases associated with travel to Vanuatu Detailed information for countries with more than 1000 reported cases (Australia [North Queensland]

Cambodia the Lao Peoplersquos Democratic Republic Malaysia the Philippines Singapore and Viet Nam) is presented below With the exception of Australia the number of reported cases in 2010 was greater than that reported in 2009 for these countries (Table 2)

Asia Subregion

Cambodia

Under the National Dengue Control Programme suspected or probable dengue cases are reported through seven sentinel sites and other non-sentinel sites In 2010 Cambodia reported 12 500 cases (38 fatal) with a peak (n = 835 cases) during week 31 in August While all four serotypes circulated the predominant serotypes identified were DEN1 and DEN2

The Lao Peoplersquos Democratic Republic

Suspected or probable dengue cases are reported through the National Surveillance System for Selected Notifiable Diseases and the Early Warning and Response Network In 2010 the Lao Peoplersquos Democratic Republic reported 22 929 cases (46 fatal) with a peak (n = 1323 cases) during week 33 in August While all four serotypes circulated the predominant serotype identified was DEN1 followed by DEN2 and DEN3

Malaysia

Suspected or probable dengue cases are reported through the National Notifiable Infectious Diseases

Figure 1 Number of reported dengue cases and case fatality ratios (CFRs) in the Western Pacific Region 1991 to 2010

The 2010 data are preliminary as of 22 May 2011

400

350

300

250

200

150

100

50

0

140

120

100

080

060

040

020

000

1991

1992

1993

1194

1195

1196

1197

1198

1199

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

CFR

all c

ases

()

Num

ber o

f cas

es (x

100

0)

Year

Cases CFR for all cases ()



Table 1 Cases of dengue including imported cases and dengue-attributed deaths in the Western Pacific Region for 2010 (as of 22 May 2011)

Countries and areas No of cases

Incidence per 100 000

No of deaths

Case fatality ratio ()

Population (in thousands)

Asia subregionBrunei Darussalam 298 7317 2 067 407Cambodia 12 500 8310 38 030 15 042China 202 001 0 0 1 353 826Hong Kong (China) 83 118 0 0 7 057Japan 243 019 0 0 127 029Republic of Korea 23 005 0 0 48 526Lao Peoplersquos Democratic Republic 22 929 35636 46 020 6 434Macao (China) 6 109 0 0 550Malaysia 46 171 16528 134 029 27 935Mongolia 0 0 0 0 2 703Philippines 135 355 14455 793 059 93 639Singapore 5 364 11048 4 007 4 855Viet Nam 128 831 14469 55 004 89 038Total for subregion 352 005 1981 1 072 031 1 777 041

Pacifi c subregionAmerican Samoa 51 7703 0 0 66Australia 1 171 544 0 0 21 527Cook Islands 0 0 0 0 16Fiji 8 094 0 0 854French Polynesia 250 9174 0 0 272Guam 3 167 0 0 180Kiribati 1 099 0 0 101Marshall Islands 55Federated States of Micronesia 23 2071 1 435 111Nauru 0 0 0 0 10New Caledonia 113 4451 0 0 254New Zealand 51 118 0 0 4 305Niue 1Commonwealth of the Northern Mariana Islands 0 0 0 0 64Palau 9 4394 0 0 20Papua New Guinea 6 894Pitcairn Islands 0Samoa 179Solomon Islands 0 0 0 0 536Tokelau 1Tonga 30 2870 0 0 105Tuvalu 0 0 0 0 11Vanuatu 192 7811 0 0 246Wallis and Futuna 14Total for subregion 1 902 531 1 005 35 822

TOTAL 353 907 1952 1 073 030 1 812 863

These data are preliminary and subject to change

Table 2 Reported number of dengue cases deaths and case fatality ratios from Cambodia the Lao Peoplersquos Democratic Republic Malaysia the Philippines Singapore Viet Nam and Australia 2006ndash2010

Country

2006 2007 2008 2009 2010

No of cases

No of deaths

CFR ()

No of cases

No of deaths

CFR ()

No of cases

No of deaths

CFR ()

No of cases

No of deaths

CFR ()

No of cases

No of deaths

CFR ()

Cambodia 16 669 158 095 39 851 407 102 9 542 65 068 11 699 38 032 12 500 38 030

Lao Peoplersquos Democratic Republic

6 356 6 009 4 943 4 008 4 149 21 051 7 214 12 017 22 929 46 020

Malaysia 38 556 89 023 48 846 98 020 49 335 112 023 41 486 88 021 46 171 134 029

Philippines 37 101 378 102 55 639 533 096 39 620 373 094 57 819 548 095 135 355 793 059

Singapore 3 127 10 032 8 826 24 027 7 032 10 014 4 497 8 018 5 364 4 007

Viet Nam 68 532 53 008 104 393 88 008 96 451 97 010 105 370 87 008 128 831 55 004

Australia 189 0 000 316 0 0 563 0 0 1 401 0 0 1 171 0 0

Total 170 530 694 041 262 814 1 154 044 206 692 678 033 229 486 781 034 352 321 1 070 030

CFR - case fatality ratio



System In 2010 Malaysia reported 46 171 cases (134 fatal) While the number of cases fluctuated throughout the year the peak (n = 1159 cases) was reported during week 34 in August While all four serotypes circulated the predominant serotype identified was DEN1 followed by DEN3 and DEN2

The Philippines

Suspected or probable dengue cases are reported through the Philippines Integrated Disease Surveillance and Response System In 2010 the Philippines reported 135 355 cases (793 fatal) with a peak (n = 30 009) during the month of August While all four serotypes circulated the predominant serotype identified was DEN3

Singapore

Dengue cases are laboratory-confirmed and reported through the Infectious Diseases Management and Outbreak System During 2010 Singapore reported 5364 cases (4 fatal) with a peak (n = 182) during week 38 in September

Viet Nam

Suspected or probable dengue cases are reported through the National Notifiable Disease Surveillance system In 2010 Viet Nam reported 128 831 cases (55 fatal) While all four serotypes circulated the predominant serotypes identified were DEN1 and DEN2

Pacifi c subregion

Australia

Dengue cases are laboratory-confirmed and reported through the National Notifiable Diseases Surveillance System In 2010 Australia reported 1171 cases (none fatal) with a peak (n = 139) during the month of November Dengue activity in Australia is restricted to North Queensland where the vector Aedes aegypti is present (the dengue virus itself is not endemic) The predominant serotypes identified from outbreaks in North Queensland were DEN1 and DEN2 although all four serotypes have been isolated from imported viraemic cases

DISCUSSION

In 2010 dengue continued to show an increasing trend in the Western Pacific Region as has been observed in the past

decade The countries with the greatest dengue burden in the Asia subregion namely the dengue endemic countries of Cambodia the Lao Peoplersquos Democratic Republic Malaysia the Philippines Singapore and Viet Nam showed an increase in reported number of cases ranging from 11-fold (Malaysia) to 32-fold (the Lao Peoplersquos Democratic Republic) the number of cases reported in 2009 (Table 1) Importantly the Lao Peoplersquos Democratic Republic also reported an increase in CFR relative to 2009 (Table 1) For Cambodia the Lao Peoplersquos Democratic Republic the Philippines and Singapore dengue activity followed historic seasonal trends with peaks occurring shortly after onset of the rainy season during and around the month of August The expansion of the Aedes aegypti habitat is believed to increase overall prevalence of disease in the environment and raise the risk of its spread5 From the Pacific subregion French Polynesia New Caledonia Vanuatu and Australia contributed 91 of reported cases with Australia (North Queensland) reporting more than 1000 laboratory-confirmed cases for two consecutive years

Sharing of regional surveillance data plays an important role in dengue control While vector control activities at the local level are essential to interrupt dengue transmission routine and timely information-sharing of regional data improves countries and areasrsquo understanding of the overall dengue situation including dengue epidemiology in neighbouring countries or other countries of interest with close tradetravel links Indeed dengue does not acknowledge national borders and in the Pacific islands dengue activity has been associated with introductions from various locations in Asia67 Comprehensive regional information provides better-informed risk assessments by each country that directly lead to response activities such as preparation for enhanced education and awareness activities Regional surveillance data showing continued high level dengue activity have also contributed to the recent launch of the Association of Southeast Asian Nations Dengue Day on 15 June 2011 which aimed at improving advocacy and community participation Sharing additional surveillance data such as serotypes and affected age group data can further improve risk assessments since monitoring these data may reveal important changes or features in dengue epidemiology8

As with any surveillance data these data have important limitations attributable to changes in reporting behaviour surveillance systems misclassifications and



underreporting For example a proportion of the excess cases in the Philippines in 2010 (135 355 in 2010 versus 57 819 in 2009) is a result of an ongoing change in the surveillance system Since 2008 the surveillance system has been transitioning from a sentinel (National Epidemic Sentinel Surveillance System) to an all-case reporting system (PIDSR) The extent of this transition has been variable with some areas starting the transition earlier than others (personal communication the Philippines Department of Health) In addition as dengue surveillance in Cambodia the Lao Peoplersquos Democratic Republic Malaysia the Philippines and Viet Nam is based on suspected or probable cases that are not all laboratory-confirmed the number of reported cases should be interpreted with caution Moreover systematic and representative sampling for laboratory confirmation in some of these countries has been challenging limiting interpretability of reported serotype data As dengue surveillance is not standardized across endemic countries comparisons between countries should also be interpreted with caution For example CFRs are affected not only by clinical management but also by case-reporting systems and reporting behaviours of clinicians

While direct comparisons between countries cannot be made these data are important for assessing trends both within and across years The data from 2010 indicate that for the majority of endemic countries dengue activity followed historic seasonality In addition increase in the annual trend of reported cases in Singapore and Malaysia appeared to indicate a true increase in 2010 for these countries As cases are reported from consistent surveillance systems and case definitions misclassification of cases likely remained constant To make dengue surveillance useful for timely and effective public health response trend assessments will continue to be essential both at national and regional levels

The ongoing dengue burden in the Western Pacific Region underscores the continuing need for region-wide sharing of information on a timely and routine basis Countries and areas should continue to maintain their surveillance activities and where they are lacking or deficient enhance or implement dengue surveillance systems Enhanced dengue surveillance could also act as a model system for countries where surveillance capacities are limited for endemic infectious diseases such activities are in line with the biregional Asia Pacific Strategy for Emerging Diseases framework to strengthen

national capacities for surveillance and response Even in countries where dengue is not endemic (eg Australia and Japan) the ever-increasing importation of cases3910 highlights the importance of monitoring and reporting of dengue for all countries and areas in the Region Lastly to improve preparedness and response activities in the face of the ever-evolving epidemiology of dengue there is a need for more systematic surveillance and reporting of serotype and age- and sex-stratified data

Confl icts of Interest

None declared

Funding

This study was undertaken as part of routine surveillance activities of the WHO Western Pacific Regional Office

Acknowledgements

The authors would like to thank all the WHO Western Pacific Regional Country Office staff for assisting with surveillance data collection and reporting

References

1 Kyle JL Harris E Global spread and persistence of dengue Annual Review of Microbiology 2008 6271ndash92 doi101146annurevmicro62081307163005 pmid18429680

2 Cummings DA et al Travelling waves in the occurrence of dengue haemorrhagic fever in Thailand Nature 2004 427344ndash347doi101038nature02225 pmid14737166

3 Hanna JN et al Two contiguous outbreaks of dengue type 2 in North Queensland The Medical Journal of Australia 1998 168221ndash225 pmid9539900

4 Hanna JN Ritchie SA An apparent recent decline in importations of dengue from Papua New Guinea into north Queensland Communicable Diseases Intelligence 2009 3334ndash35 pmid19618767

5 Halstead SB Dengue virus-mosquito interactions Annual Review of Entomology 2008 53273ndash291 doi101146annurevento53103106093326 pmid17803458

6 Wilder-Smith A Gubler DJ Geographic expansion of dengue the impact of international travel The Medical Clinics of North America 2008 921377ndash1390 doi101016jmcna200807002 pmid19061757

7 A-Nuegoonpipat A et al Sustained transmission of dengue virus type 1 in the Pacific due to repeated introductions of different Asian strains Virology 2004 329505ndash512 pmid15518827


9 Tarumoto N et al Dengue fever as an acute febrile disease after overseas travel a report of two cases Japanese Journal of Infectious Diseases 2011 64163ndash164 pmid21519135



Chang et al Dengue control in the Western Pacific Region

Challenges and future perspective for dengue vector control in the Western Pacifi c RegionMoh Seng Changa Eva Maria Christophela Deyer Gopinathb and Rashid Md Abdurc on behalf of Malaria Other Vectorborne and Parasitic Diseases World Health Organization Regional Offi ce for the Western Pacifi cCorrespondence to Moh Seng Chang (e-mail changmwprowhoint)

a Malaria Other Vectorborne and Parasitic Diseases World Health Organization Regional Offi ce for the Western Pacifi c Manila the Philippinesb Malaria Other Vectorborne and Parasitic Diseases World Health Organization the Lao Peoplersquos Democratic Republicc Malaria Other Vectorborne and Parasitic Diseases World Health Organization CambodiaSubmission date 18 February 2011 Publication date 30 June 2011doi 105365wpsar201011012

Dengue remains a significant public health issue in the Western Pacific Region In the absence of a vaccine vector control is the mainstay for dengue prevention and control In this paper we describe vector surveillance and vector control in the Western Pacific countries and areas

Vector surveillance and control strategies used by countries and areas of the Western Pacific Region vary Vector control strategies include chemical biological and environmental management that mainly target larval breeding sites The use of insecticides targeting larvae and adult mosquitoes remains the mainstay of vector control programmes

Existing vector control tools have several limitations in terms of cost delivery and long-term sustainability However there are several new innovative tools in the pipeline These include Release of Insects Carrying a Dominant Lethal system and Wolbachia an endosymbiotic bacterium to inhibit dengue virus in the vector In addition the use of biological control such as larvivorous fish in combination with community participation has potential to be scaled up

Any vector control strategy should be selected based on evidence and appropriateness for the entomological and epidemiological setting and carried out in both inter-epidemic and epidemic periods Community participation and interagency collaboration are required for effective and sustainable dengue prevention and control Countries and areas are now moving towards integrated vector management

Regional Analysis

BACKGROUND

Dengue fever (DF) and dengue haemorrhagic fever (DHF) are on the increase in Asia and the Pacific Countries and areas in the World Health Organization (WHO) Western Pacific Region are reporting more cases and an increase in the frequency of epidemics Four countries in particular Cambodia Malaysia the Philippines and Viet Nam (mainly southern Viet Nam) are facing annual epidemics that constitute over 90 of the total dengue cases reported in the Region1

Given the lack of a dengue vaccine control of dengue depends on vector control Vector control is best achieved through management of breeding sites The primary goal of vector control activities is to reduce vector population density to levels that are believed to correlate with a lower dengue transmission risk2 The most important dengue vector in the Western Pacific Region is Aedes aegypti (Stegomyia aegypti) which is predominately found in densely populated urban areas Dengue outbreaks have also been associated with Aedes albopictus particularly in China3 and several other

Aedes species found in South Pacific countries and areas may also be competent dengue vectors4 Aedes breeding tends to occur in household containers

In this paper we describe dengue vector surveillance and control practices in the Western Pacific Region and provide a perspective for future dengue control

DENGUE VECTOR SURVEILLANCE

While insufficient to accurately predict the risk of human infection dengue vector surveillance employs several entomological indicators that have been developed to assess the risk of outbreaks occurring These include house index Breteau index container index and ovitrap indexes that are solely based on entomological parameters and lack epidemiological input Models have attempted to redress this shortfall including use of a pupal index that has been shown to be correlated to dengue seroprevalence in a population56 A model employing all three parameters of dengue transmission vector density human cases and vector infection rate would probably be the most accurate


Chang et alDengue control in the Western Pacific Region

in determining outbreak thresholds for early outbreak prediction Vector surveillance is conducted using these and other indicators in several Western Pacific Region countries and areas (Table 1)

DENGUE VECTOR CONTROL STRATEGIES

Vector control methods and strategies differ across countries and areas in the Western Pacific Region (Table 2) Strategies depend upon specific dengue vector

ecology case burden availability of resources feasibility of proper application and the cultural context of the country An understanding of local mosquito ecology is important for determining an effective targeted strategy The trend for dengue vector control in the Region has shifted from relying solely on insecticides to include source reduction biological control and environmental management through community participation However insecticide use is still the mainstay of dengue vector control during outbreaks

Table 1 Description of dengue vector surveillance in selected countries and areas of the Western Pacific Region

Selected countryarea Vector surveillance description Types of Aedes indices

used Geographical areas Frequency

Australia (North Queensland)Australia (Northern Territory)

- BG-Sentineltrade or BG traps and net traps for adult vector monitoring

- Ovitraps (lethal traps) in sentinel urban areas

- Larval surveys for presence of vectors and to assess residual applications to receptacles

- Larval surveys standard ovitraps BG and Encephalitis Vector Survey traps for vector importation presence

House and BreteauAdult BG trap presence

only (vector free but frequent importations)

Selected sites in sentinel urban areas and port areas

Principal overseas port areas selected urban sentinel sites

Regular monthly during summer rainy season and outbreaks

Weekly to fortnightly

Cambodia

Larvalpupal surveys in sentinel surveillance sites to assess high-risk areas and mass larvicide control measures

House Breteau container and pupal density

Sentinel sites in urban semi-urban and rural areas

Not regularRainy and dry seasons

China - Human landing catch- Light trap and net trap for vector

monitoring


Selected sites in urban and semi-urban areas

Not regularAs study projects

Hong Kong (China)

Routine ovitrap surveillance in sentinel sites to monitor vector density and generate ovitrap index as dengue risk indicator

Ovitrap Sentinel sites in urban residential areas

Regular throughout the year


Sentinel surveillance sites to assess high-risk areas and community participation

House Breteau and container


Not regular

Malaysia

Larval surveys to assess the density of vector breeding sites and high risk areas

- Ovitrap surveys as research projects- Surveys as part of epidemic response

activities for law enforcement


Urban suburban and nationwide

Routine

Philippines- Larvalpupal surveys in selected sites

for community-based vector control- Vector surveys as part of

entomological research activities


Urban suburban Not regular

Singapore

- Larval surveys to assess the presence of vector vector activity and distribution and to monitor breeding habitats

- Ovitrap to assess the effectiveness of control measures and to monitor high-risk areas

House Breteau container and ovitrap


Routine

Viet Nam Sentinel surveillance sites to assess

high-risk areas and community-based vector control



Not regular



A systematic literature review and case studies describing dengue vector control services by the WHO Special Programme for Research and Training in Tropical Diseases have been published elsewhere7 The following review provides information on national dengue control operational strategies implemented at the programmatic level

(1) Chemical treatment of breeding sites

Larvicides to prevent vector breeding are used in several countries and areas in the Western Pacific Region In Cambodia timely larviciding before the dengue season in targeted densely populated areas has been designed as a short-term intervention since 2000 The intervention was reported to have reduced the number of dengue cases and deaths by 538 Targeted containers in stratified dengue high risk areas are treated twice annually to prevent outbreaks Large containers can also be specifically targeted both as a preventive method and during outbreaks8

Application to every possible breeding container in the Greater Mekong Subregion countries is not feasible due to cost and operational delivery shortfalls Larvicides should be used in tandem with community mobilization and environmental management Larvicides furthermore carry the risk of development of insecticide resistance and community dependence on expensive centrally planned interventions Wide-scale outbreaks in Cambodia in 2007 outside the stratified high-risk areas and presence of abundant discarded containers and cryptic breeding sites underline the possibility of dengue spreading into new rural areas where the control programme cannot easily use larvicides for outbreak mitigation and prevention

During outbreaks chemical larvicides are used to target containers breeding vectors in houses near case clusters While larviciding is effective at lowering vector density infectious adult mosquitoes are not affected and transmission may continue for the remaining

Table 2 Control of dengue virus vectors (Aedes aegypti and Aedes albopictus) in Western Pacific Region

CountryareasSpace

spraying (outbreak)

Larviciding (chemical amp biological larvicide)

Biological control

Environmental management

(source reduction)

Health education and

community mobilization)

LegislationIntersectoral and agency

collaboration

Australia (North Queensland ++ ++ ++ ++ + +

Australia (Northern Territory ++ ++ ++ ++

Cambodia + +++ (guppy fi sh as operational

research)+ + (school

based) - +

China + - - + + - +

Hong Kong (China) amp Macau (China) + - - + + + +

Lao Peoplersquos Democratic Republic + +

+ (guppy fi sh as operational

research)+ ++ - +

Fiji + + - + + - -

Malaysia + + - + + ++ +

Philippines + ++ (guppy fi sh as operational

research)+ + - +

Solomon Islands + - - - + - -

Singapore + + - + + ++ ++

Vanuatu + + - + + - +

Viet Nam + + + (Mesocyclops) + ++ + +

++ Exists and is a regularcore programme activity+ Exists but irregular only used under field research condition Does not existSource Country Reports 2008 World Health Organization Western Pacific Region



lifetime of the infectious adult mosquito In Australia (North Queensland) a residual insect growth regulator (methoprene) is regularly used in discarded and disused containers roof gutters rainwater tanks and other rainwater-collecting containers to reduce overall populations seasonally and for outbreak control9

The World Health Organization Pesticide Evaluation Scheme recommends several larvicides including temephos insect growth regulators and Bacillus thuringiensis that are safe for drinking-water treatment10 There are reports from Malaysia on the high efficacy of Bacillus thuringiensis var israelensis distributed by space spraying for vector control1112

(2) Insecticide spraying

Chemical insecticide spraying is designed to reduce disease transmission by lowering the adult vector population and targeting infectious adults through reducing their longevity The writers are of the opinion that spraying is recommended only as a method of controlling ongoing or preventing incipient outbreaks through a single massive reduction in adult vector density However the practice of indiscriminate or wide-scale outdoor spraying is of questionable effectiveness since many mosquitoes may be inaccessible and would be unaffected In addition the insecticidal effects of spraying are transient and depend on persistence of the insecticide used and method of application

A long timelag between reporting of human cases and commencement of spraying also minimizes the effects of intervention This lag is likely longest in resource-constrained countries with rural populations where reporting of cases and commencement of vector control activities take longest Clinicians at lower levels of the health systems may not recognize dengue symptoms and the surveillance system in rural areas may be relatively poor In these situations spraying operations will take longer to implement Poor functionality of sprayers insufficient coverage of spraying and incorrect dosage of chemical insecticides coupled with poor public acceptance and compliance also affect the effectiveness of operations While local teams should have the expertise to conduct spraying effectively central-level Ministry of Health staff may be required to supervise to ensure the quality of operations

(3) Biological control

Biological control of dengue vectors is based on the concept of introducing organisms that prey upon

compete with or otherwise reduce the density of vectors In the case of Aedes aegypti the immature stages of the vectors in household water containers provide a suitable target for the introduction of biological control agents Their introduction must be safe inexpensive easy to produce on a large scale and be culturally and socially acceptable to the target population In the case of Aedes mosquitoes certain species of fish and predatory copepods have proven effective13-15

Viet Nam has experimented with the use of the copepod Mesocyclops as a community-based biological control agent1314 The project yielded promising results and within three years less than 15 of houses were positive for dengue vectors in the project areas This successful model was due to a combination of vertical and horizontal approaches identification of key Aedes breeding sites and strong multisectoral cooperation When used in combination with community source reduction the use of Mesocyclops is an easy and inexpensive method of Aedes aegypti control that should be effective for many communities in Viet Nam and elsewhere13

In Cambodia a successful trial of the effectiveness of introducing larvivorous guppy fish (Poecilia reticulata) into water storage containers has taken place in a single commune The trial was successful with households receiving the intervention exhibiting a 790 reduction in Aedes container index compared with control houses15 This trial used community volunteers to colonize and distribute guppies and showed a clear impact on entomological indices in the 14-village trial area Communities were enthusiastic regarding the intervention which offers greater convenience than emptyingwashing containers and only two to three guppy fish are required to control mosquito and planktonalgal growth in each 200ndash400 litre water container To assess the effectiveness of the intervention on a larger scale a communication for behavioural impact16 (COMBI) project advocating the use of guppies in tandem with source reduction is currently being implemented in districts of Cambodia and the Lao Peoplersquos Democratic Republic17

(4) Environmental management and vector control

In some areas of the Greater Mekong Subregion over 80 of households harbour breeding dengue vectors largely as a result of water storage practices17 Households often feature water storage containers kept outside These containers used to store rain river or well



water for household use and drinking-water for animals are extremely difficult to protect from Aedes aegypti infestation In addition discarded containers tyres and other vessels collect rainwater during the rainy season providing excellent Aedes aegypti breeding sites In some countries and areas water storage containers are scarce and breeding sites are more difficult to locate In Macau (China) for example key breeding sites of Aedes albopictus larvae and pupae include water collection wells of closed underground drains lotus flower jars garden stone pools and fountains In Malaysia breeding sites are often discarded and neglected containers rather than domestic water storage containers Other potential breeding sites are containers found in parks empty land industry buildings construction sites and blocked cement drains and septic tanks Vector control should be targeted to key breeding sites as identified from vector surveillance

Environmental management aims to alter the environment to minimize vector breeding sites especially in close proximity with humans and therefore minimize human-vector contact These modifications may be long-lasting measures and include modifying building designs such as roof gutters to prevent Aedes breeding18 installing flip type water tank covers to deny gravid female Aedes entry and repairing blocked cement drains Short-term environmental modification measures involve local agencies and engagement of the community General household sanitation is key to preventing Aedes breeding in domestic environments and the local authorityrsquos role is to ensure no accumulation of water containers in public places

(5) Community mobilization

Community-based dengue vector control using COMBI as a planning tool is being incorporated into dengue control programmes in Malaysia the Lao Peoplersquos Democratic Republic and the Philippines Since 2007 the Lao Peoplersquos Democratic Republic Womenrsquos Union has been involved in community mobilization for dengue awareness and larvae detection in households in provinces It is also involved in distribution of larvicide for dengue outbreak intervention Community mobilization and school-based dengue control activities have been also piloted19

Similar approaches have already been shown to be effective in Singapore through intensified community action using simple dengue prevention messages through community outreach teams After a

2005 outbreak Singapore intensified community dengue prevention adopting ldquo10-Minute Mozzie Wipeoutrdquo using simple dengue prevention messages targeting residents construction workers factory workers and foreign maids Community engagement also takes place using dengue volunteers delivering dengue prevention messages in the community18

While COMBI projects adapted from the field of marketing have the potential to make a sustained impact on dengue vector density there has been little evidence of the impact of COMBI interventions on dengue transmission or outbreak prevention Projects implemented in the Region have lacked sufficient evaluation of the sustainability of behavioural changes or the impact on vector control and dengue transmission Despite advocacy of community participation and mobilization communities may be reluctant to take appropriate dengue preventive measures except during outbreaks when the effects of dengue are clearest In the Greater Mekong Subregion reports of weekly washing of large water storage containers may not reflect actual community practice Frequent washing of these large containers is not practical particularly when they are full of scarce water and are in frequent daily use COMBI processes should be used to effectively communicate and deliver proven tools for dengue prevention One of the objectives of the current guppy fish project in Cambodia and the Lao Peoplersquos Democratic Republic is to identify a community-based dengue vector control tool and use the COMBI process to deliver this tool in the community and thus achieve behavioural change In this case a key behavioural change message has been ldquoinspect your water containers for guppy fish on a weekly basisrdquo

INTERAGENCY COLLABORATION FOR DENGUE CONTROL IN THE REGION

The WHO Asia-Pacific Dengue Strategic Plan (2008ndash2015) consists of six components two of these related to vector control are integrated vector management (IVM) and social mobilization and communication20 These dengue control activities require interagency collaboration and partnership with other agencies in promoting community-based dengue control Many countries and areas of the Western Pacific Region use this approach

Dengue control activities in cities and townships in Malaysia are the responsibility of local authorities21 The Minister of Local Government and Housing has equal responsibility with the Ministry of Health for dengue



control Other agencies involved in dengue prevention and control are the Ministry of Education Ministry of Environment Judicial Department and community organization groups The Ministry of Agriculture is the pesticide regulatory agency However there is also a pesticide board responsible for pesticide registration and monitoring use Most recently the Ministry of Health is adapting COMBI planning tools aimed at behavioural change in several states in Peninsular Malaysia

In Singapore the National Environment Agency (NEA) is the main agency for dengue vector control while cases are reported from the Ministry of Health When mounting search destroy and fogging operations the NEA also alerts residents and involves the community to remove breeding habitats from homes Private pest management operators land agencies and town councils also coordinate with the NEA to maintain close surveillance and carry out intensive mosquito treatment especially in endemic areas18 For community-based activities the NEA works in partnership with Community Development Councils and construction firms to curb Aedes mosquito breeding at homes and construction sites

In Australia Queensland Health has formulated a Dengue Fever Management Plan for North Queensland where Ae aegypti is widespread The plan focuses on disease surveillance mosquito control and surveillance and education Mosquito control is managed by a special unit of Queensland Health the Dengue Action Response Team (DART) DART operates under the Queensland Public Health Act 2005 that allows the right of access to all yards (excluding houses) to set lethal ovitraps and apply pesticides to any container with mosquitoes9

In 2002 the Fifty-fifth World Health Assembly adopted resolution WHA5517 which addressed dengue and dengue haemorrhagic fever prevention and control22 thereby creating a political environment supportive of international regional and national dengue activities In response to this resolution the Government of Cambodia worked in collaboration with international and bilateral agencies to strengthen the surveillance capacity of the National Dengue Control Programme to intensify training on clinical management of dengue haemorrhagic fever and to develop finance and begin implementation of a five-year vector control plan from 2001 A national dengue control committee was set up and established at Ministry level to plan coordinate and implement the national strategy Based on vector ecology

dengue endemicity and the socioeconomic situation in Cambodia the programme focused on lowering epidemic potential through timely application of larvicide via mobilization of thousands of citizens including local authorities community volunteer networks and Red Cross workers In collaboration with the Ministry of Education School Health Department a school-based dengue control pilot project was launched in 2005 Several community-based vector control projects have also been implemented and are undergoing field trials including community use of insecticidal impregnated jar covers integrated vector control using guppy fish and source reduction activities23

FUTURE PERSPECTIVE

Despite recent heightened awareness for dengue prevention various challenges still exist These include inadequate funding and resources and the lack of a sound strategy to respond to the increasing problem of dengue outbreaks in a growing number of geographical areas Rapid urbanization lack of basic sanitation increased mobility of populations and international travel has compounded the problem in some countries and areas and there is no promising solution for sustainable control of dengue vectors Given the complexity of dengue vector control at national level a well-organized dengue control programme should be established to collaborate with different sectors ministries agencies and partners to plan implement and facilitate these activities

For vector control there is a need for increased capacity in outbreak response as a component of a three-pronged strategy This strategy should include community-based larvae control (using environmental management and other technologies as appropriate) adult mosquito management (including research into novel insecticides and their application) and use of personal protection (including research on repellents adult reduction devices and their mode of delivery)

Preventive activities should be built into existing health care systems and be well coordinated within primary health care activities rather than within the dengue control programme of Ministries of Health WHO is advocating Integrated Vector Management (IVM) as a further method of dengue vector control24 IVM is defined as ldquoa rational decision-making process for the optimal use of resources for vector controlrdquo The important attributes of IVM are advocacy social mobilization and legislation collaboration within the



health sector and with other sectors an integrated intervention methods approach evidence-based decision-making and capacity-building25 IVM is suited to dengue management and control programmes in dengue endemic countries and should be used when planning dengue prevention in the Region To improve the efficiency and effectiveness of dengue vector control increasing the capacity of countries to implement IVM is critical The basic elements of dengue control under IVM are to adopt evidence-based selection and delivery of different interventions (or combinations of interventions) based on local settings to increase country vector control delivery capacity in all geographical areas and to implement monitoring and evaluation tools

New vector control tools for Aedes aegypti population suppression and replacement are currently under investigation The use of Sterile Insect Technique is not a new approach and it has been used for insect population control against a wide range of agriculture pest insect species26 The recently developed Release of Insects Carrying a Dominant Lethal (RIDL) system incorporates a novel genetic sexing system for mass rearing of male mosquitoes27 Under this new technology a lethal gene was micro-injected into the eggs of Aedes aegypti The gene subsequently integrated into the genome of the mosquito The gene regulates the production of toxic metabolites in the larval stage killing the larva The antibiotic tetracycline is used to rear larvae and to maintain the mosquito in the laboratory This antibiotic inhibits the lethal gene and produces no toxin allowing larvae to develop fully into adults In actual control RIDL males will be released to mate with wild females Fertilized females will produce eggs that hatch into larvae carrying the RIDL gene All those carrying the gene will die at late larval or early pupal stage The Malaysia Institute for Medical Research (IMR) has conducted this project in three phases (1) establishment of the transgenic Malaysian strain of Aedes aegypti (2) simulation release trial inside a field house and (3) field release in a suitable experimental field site Currently IMR is implementing the third phase

Another development in terms of novel vector control is the discovery that the naturally occurring endosymbiotic bacterium Wolbachia ndash commonly present in insect populations ndash can inhibit replication of the dengue virus in Aedes aegypti mosquitoes28 The idea is to introduce these strains of Wolbachia into wild populations of Aedes aegypti potentially replacing

field populations in a way that could suppress or even possibly eliminate dengue transmission

Vector surveillance must also be improved including data on key and target container types for better breeding site management A geographic information system (GIS)-based approach to dengue control and surveillance can link relevant spatial data to identify key patterns and relationships aiding in planning and strategic decision-making29 Thematic maps can be produced to visualize the spatial distribution of dengue vectors in relation to relevant environmental and climatic indicators Similarly dengue cases and vector densities can be mapped to view the spatial patterns of dengue distribution over time and to monitor potential movements of dengue transmission foci after outbreaks have been identified Through the combination and integration of detailed spatial information into a centralized GIS database programme managers will be equipped with a simple yet powerful decision-making planning surveillance and community education tool for dengue management

CONCLUSIONS

Although intense efforts are under way to develop a vaccine there is neither vaccine to prevent dengue nor are there any effective antiviral drugs to treat the disease To minimize the impact of dengue outbreaks countries and areas should strengthen their vector control programmes both during inter-epidemic and epidemic periods Control strategies should use integrated approaches with evidencendashbased selection and delivery of different interventions or combinations of interventions adapted to different entomological and epidemiological settings Dengue prevention and control should include individuals families and the wider community and encourage community participation to have the best chances of success

Confl ict of interest

None declared

Funding

This study was undertaken as part of routine activities of the WHO Western Pacific Regional Office

References

1 Dengue in the Western Pacific Region (cited 2000ndash2009) Manila World Health Organization for the Western Pacific Region (httpwwwwprowhointtopicsdengueen accessed on 10 June 2011)



2 Eisen L et al Proactive vector control strategies and improved monitoring and evaluation practices for dengue prevention Journal of Medical Entomology 2009 461245ndash1255 doi1016030330460601 pmid19960667

3 Wu JY et al Dengue fever in mainland China The American Journal of Tropical Medicine and Hygiene 2010 83664ndash671 doi104269ajtmh201009-0755 pmid20810836

4 Belkin JN Mosquitoes of the South Pacific (Diptera Culicidae) Berkeley University of California Press 1962

5 Focks DA A review of entomological sampling methods and indicators for dengue vectors Geneva World Health Organization on behalf of the Special Programme for Research and Training in Tropical Diseases 2003 (httpwwwwhointtdrpublicationsdocumentsdengue_vectorspdf accessed on 18 May 2011)

6 Focks DA Alexander N Multicountry study of Aedes aegypti pupal productivity survey methodology findings and recommendations Geneva World Health Organization on behalf of the Special Programme for Research and Training in Tropical Diseases 2006 (httpwwwwhointtdrpublicationsdocumentsaedes_aegyptipdf accessed on 18 May 2011)

7 Horstick O et al Dengue vector-control services how do they work A systematic literature review and country case studies Transactions of the Royal Society of Tropical Medicine and Hygiene 2010 104 379ndash386 doi101016jtrstmh200907027 pmid20400169

8 Suaya JD et al Cost-effectiveness of annual targeted larviciding campaigns in Cambodia against the dengue vector Aedes aegypti Tropical Medicine amp International Health 2007 12 1ndash11 doi101111j1365-3156200701889x pmid17207142

9 Ritchie SA Evolution of dengue control strategies in North Queensland Australia Arborvirus Research in Australia 2005 9 324ndash330 (httpwwwmosquitosciencenetpdfsRitchie-evolution-dengue-TPHU-ARA-05-mspdf accessed on 18 May 2011)

10 Pesticides and their application for the control of vectors and pests of public health importance Geneva WHO Pesticide evaluation scheme Department of Control of Neglected Tropical Diseases 200631 (httpwhqlibdocwhointhq2006WHO_CDS_NTD_WHOPES_GCDPP_20061_engpdf accessed on 18 May 2011)

11 Lam PHY et al Aedes albopictus control with spray application of Bacillus thuringiensis israelensis strain AM 65ndash52 The Southeast Asian Journal of Tropical Medicine and Public Health 2010 411071ndash1081 pmid21073027

12 Lee HL et al Impact of larviciding with a Bacillus thuringiensis israelensis formulation VectoBac WG on dengue mosquito vectors in a dengue endemic site in Selangor State Malaysia The Southeast Asian Journal of Tropical Medicine and Public Health 2008 39601ndash609 pmid19058596

13 Kay BH Vu SN New strategy against Aedes aegypti in Vietnam Lancet 2005 365613ndash617 pmid15708107

14 Nam VS et al National progress in dengue vector control in Vietnam survey for Mesocyclops (Copepoda) Micronecta (Corixidae) and fish as biological control agents The American Journal of Tropical Medicine and Hygiene 2000 625ndash10 pmid10761718


16 Parks W Lloyd L Planning social mobilization and communication for dengue fever prevention and control - a step-by-step guide

Geneva World Health Organization 2004 (httpwhqlibdocwhointpublications20049241591072pdf accessed on 18 May 2011)

17 Beaver C Palmer KTA No 7268 ndashREG Regional Public Goods for Health Combating Dengue in ASEAN Inception Report Manila Asian Development Bank 2010 (httpgms-cdcorgresourcedoc_view788-inception-report-28-feb-2010rawtmpl=component accessed on 10 June 2011)

18 Ng LC Singaporersquos dengue control programme in the face of new challenges In Asia-Pacific dengue programme managers meeting 5 to 9 May 2008 Singapore Manila World Health Organization Western Pacific Regional Office 200833ndash39

19 Chang MS Dengue in the Greater Mekong Sub-region status epidemiology and control Report presented in the GMS public health forum 5ndash7 November 2007 Vientiane The Lao Peoplersquos Democratic Republic

20 The dengue strategic plan for the Asia Pacific Region 2008ndash2015 Manila World Health Organization South-East Asia Region and Western Pacific Region 2005 (httpwwwwprowhointinternetresourcesashxMVPDengue+Strategic+Planpdf accessed on 18 May 2011)

21 Yusoff HM National dengue programme in Malaysia In AsiandashPacific dengue programme managers meeting 3ndash9 May 2008 Singapore Manila World Health Organization Western Pacific Regional Office 2008 83ndash86 (httpwwwwprowhointinternetfilesmvpDengue_Reportpdf accessed on 19 May 2011)

22 Resolution WHA 5517 Agenda item 1314 Dengue fever and Dengue haemorrhagic fever prevention and control Geneva World Health Organization (httpwwwwhointneglected_diseasesmediacentreWHA_5517_Engpdf accessed on 10 June 2011)

23 Seng CM et al The effect of long-lasting insecticidal water container covers on field populations of Aedes aegypti (L) mosquitoes in Cambodia Journal of Vector Ecology 2008 33333ndash341 doi1033761081-1710-332333 pmid19263854

24 Global Strategic Framework for Integrated Vector Management Geneva World Health Organization 2004 (httpwhqlibdocwhointhq2004WHO_CDS_CPE_PVC_2004_10pdf accessed on 18 May 2011)

25 Report of the WHO Consultation on Integrated Vector Management (IVM) WHO Headquarters Geneva Switzerland 1ndash4 May 2007 Geneva World Health Organization 2007 (httpwwwsearowhointLinkFilesPublications_and_Documents_Report_of_the_WHO_consultation_on_IVMpdf accessed on 18 May 2011)

26 Krafsur E Sterile insect technique for suppressing and eradicating insect populations 55 years and counting Journal of Agricultural Entomology 1998 15303ndash317

27 Alphey L et al Insect population suppression using engineered insects In Serap Aksoy Landes Bioscience and Springer Science+Business Media eds Transgenesis and the management of vector borne diseases New York Springer 2008 93ndash104

28 Jeffery JAL et al Characterizing the Aedes aegypti population in a Vietnamese village in preparation for a Wolbachia-based mosquito control strategy to eliminate dengue PLoS 2009 3e1371 (httpwwweliminatedenguecomPortals58PDFsjournalpntd0000552pdf accessed on 10 June 2011)

29 Eisen L Lozano-Fuentes S Use of mapping and spatial and space-time modelling approaches in operational control of Aedes aegypti and Dengue Plos Neglected Tropical Medicine 2009 3e411 doi101371journalpntd0000411 pmcidpmc2668799


Anker and Arima Male-female differences in dengue incidence in Asia

Malendashfemale differences in the number of reported incident dengue fever cases in six Asian countriesMartha Ankera and Yuzo Arimab on behalf of Emerging Diseases Surveillance and Response Division of Health Security and Emergencies World Health Organization Regional Offi ce for the Western Pacifi cCorrespondence to Yuzo Arima (e-mail arimaywprowhoint)

a School of Public Health and Health Sciences University of Massachusetts Amherst Massachusetts United States of Americab World Health Organization Regional Offi ce for the Western Pacifi c Manila the PhilippinesSubmission date 24 February 2011 Publication date 30 June 2011doi 105365wpsar201121002

Regional Analysis

Introduction Demographic factors such as age and sex are associated with the likelihood of exposure to Aedes aegypti the vector for dengue However dengue data disaggregated by both sex and age are not routinely reported or analyzed by national surveillance systems This study analysed the reported number of incident dengue cases by age and sex for six countries in Asia

Methods Data for the Lao Peoplersquos Democratic Republic the Philippines Singapore and Sri Lanka were obtained from DengueNet the number of male and female dengue cases was available for four age groups (lt 1 1ndash4 5ndash14 and 15 years) over a cumulative period of six to 10 years Data for Cambodia (2010) and Malaysia (1997ndash2008) were obtained from their respective ministries of health

Results An excess of males was found among reported dengue cases 15 years of age This pattern was observed consistently over several years across six culturally and economically diverse countries

Discussion These data indicated the importance of reporting data stratified by both sex and age since collapsing the data over all ages would have masked some of the male-female differences In order to target preventive measures appropriately assessment of gender by age is important for dengue because biological or gender-related factors can change over the human lifespan and gender-related factors may differ across countries

Dengue is a tropical and subtropical mosquito-borne infection that can cause severe illness and death During the last 30 years dengue fever

has dramatically expanded its geographical range and shortened its epidemic cycle in many places According to the World Health Organization (WHO) dengue is endemic in over 100 countries and approximately two-fifths of the worldrsquos population is currently at risk for dengue fever with an estimated 50 million infections annually1 Among the estimated 25 billion people at risk globally for dengue about 18 billion (ie more than 70) reside in Asia Pacific countries2

The most important vector for dengue Aedes aegypti is a predominantly urban mosquito species that favours particular environments such as locations where water storage is common and waste disposal services are inadequate13 While exposure to such environments may be related to specific demographic factors such as age and sex there is a scarcity of sex-specific dengue data Indeed sex-disaggregated dengue data are not

routinely reported or analysed by surveillance systems The few studies from Asia such as those from Singapore that have examined male and female dengue incidence have tended to find greater male incidence4 Differences in dengue incidence have been attributed to gender-related differences in exposures such as time away from home45 As gender roles and thus exposures change over the human lifespan it is important to examine dengue cases by both sex and age While there are recent studies that provide age-6 or sex-specific3 incident dengue surveillance data few studies provide incident dengue data stratified by both age and sex This study describes the reported number of incident dengue cases by age and sex for six countries in Asia

METHODS

The current study analysed national surveillance data on the annual number of reported dengue cases by age and sex for six Asian countries Reported cases included all reported dengue fever cases dengue haemorrhagic fever


Anker and ArimaMale-female differences in dengue incidence in Asia

cases and cases of dengue shock syndrome The six countries were selected because their data either were available in DengueNet (part of the WHO Global Atlas that contains national data on select health conditions provided by the ministries of health of participating countries7) or were provided to the WHO Western Pacific Regional Office by their ministries of health Data for the Lao Peoplersquos Democratic Republic the Philippines Singapore and Sri Lanka were from DengueNet For these four countries the number of male and female dengue cases was reported for four age groups (1 1ndash4 5ndash14 and ge 15 years) over a period of six to 10 years Data from Cambodia and Malaysia were provided directly to WHO by their ministries of health For Cambodia male and female cases for age groups le 4 5ndash9 10ndash14 and ge 15 years were available for 2010 (through 24 December 2010) For Malaysia the reported number of dengue cases from 1997 to 2008 was available by both sex and age-group separately but not in a form stratified for both Subnational data were available for four countries This included the 18 provinces of the Lao Peoplersquos Democratic Republic the 15 states of Malaysia (for 2007 and 2008) the 16 regions of the Philippines and the nine provinces of Sri Lanka For the Philippines DengueNet used the same administrative regions that were in existence in 1998 the first year data were submitted to DengueNet from the Philippines

Since the implications of sex and gender for infectious disease differ with age age groups were examined separately Sex refers to biological characteristics of males and females while gender refers to male and female norms that are socially and culturally constructed For each country and age group 2 goodness of fit tests were used to compare the observed proportion of males among reported dengue cases to the expected proportion of males among reported cases based on the age group specific sex distribution of the national population Demographic data for the year 2000 from the United Nations8 were used to calculate the proportion of males in the national population for each age group for which we had reported dengue data (namely lt 1 1ndash4 5ndash14 and ge 15 years for the four DengueNet countries and 0ndash4 5ndash14 and ge 15 years for Cambodia and all ages combined for Malaysia) The United Nations report included the numbers of males and females in five-year age groups For the 5ndash14 and the ge 15 year age groups the numbers of males and females in their respective age groups were summed For age lt 1 year numbers of

males and females were calculated as the mean of the numbers of males and females born and the numbers of males and females expected to be alive at the end of one year using data on the sex ratio at birth number of births and sex-specific infant mortality rates from the United Nations8 The numbers of males and females in age group 1ndash4 years were then calculated by subtracting those lt 1 year from those aged 0ndash4 years

The consistency over time and location of differences between the proportion of males among reported cases and the proportion of males in the general population was examined in two ways First variations in annual data were examined and data for each year were tested for statistical significance Second for the ge 15 year old age group in which the percent male among reported cases was found to be significantly higher than the percent male in the general population in all countries subnational data were examined to see how consistently the excess of males was reported in subnational areas No statistical tests were conducted on subnational data as age- and sex-stratified population figures were not available for subnational administrative regions

RESULTS

The total number of reported dengue cases and the proportion of reported cases that were male by age group for the Lao Peoplersquos Democratic Republic the Philippines Singapore Sri Lanka and Cambodia were calculated (Table 1) The proportion of men in the general population for each age group is also provided for comparison The number and percent male of dengue cases for each subnational administrative region of the Lao Peoplersquos Democratic Republic the Philippines and Sri Lanka for the ge 15 year age group and for all age groups combined were calculated (Table 2) Results for Malaysia are presented separately (Table 3)


Malendashfemale ratios in dengue cases reported from the Lao Peoplersquos Democratic Republic were variable over time and location (Tables 1 and 2) From 2000 to 2006 among infants percent male of reported cases was similar to the percent male in the general population and no significant differences were found for any year or for all years combined There was a small excess of reported male cases among 1ndash4 year olds and this male excess was statistically significant for all years combined and for five of the seven years



(Table 1) For 5ndash14 year olds there was a slightly lower than expected proportion of males among reported cases However results were inconsistent from year to year with some years reporting proportionately more and others proportionately fewer male cases than expected The most pronounced difference in the Lao Peoplersquos Democratic Republic was found among those ge 15 years of age (58 male cases compared to 49 male in the general population) a significant male excess in this age group was observed in four of

the seven years assessed Much of the male excess in this age group was driven by the larger than expected male cases who were ge 15 years of age in the regions of Savannakhet Province and Vientiane Municipality (Table 2)

The Philippines

The age and sex distribution of reported dengue cases was consistent for 1998ndash1999 and 2001ndash2005 in the

Table 1 Reported number of dengue cases percent male of reported cases and percent male in the general population by age group and year for the Lao Peoplersquos Democratic Republic the Philippines Singapore Sri Lanka and Cambodiaa

Country yearlt1 1 to 4 5 to 14 ge 15

No of cases male No of cases male No of cases male No of cases maleLao Peoplersquos 2000 67 478 124 565 266 568 917 566

Democratic 2001 179 536 427 614 1 402 581 1 960 715Republic 2002 581 485 1 213 592 2 425 463 4 957 548

2003 1 052 520 3 876 530 4 491 464 8 224 6352004 200 550 502 560 1 278 518 1 434 462 2005 551 488 1 051 481 1 847 520 2 022 485 2006 712 531 1 133 539 1 777 519 2 846 506 Total 3 342 513 8 326 541 13 486 498 22 360 579

Populationb 511 510 508 493 Philippinesc 1998 973 581 6 451 508 19 818 497 8 406 543

1999 242 574 1 785 508 5 021 509 2 358 5892001 607 521 3 814 507 13 399 504 7 132 5842002 361 535 3 055 505 8 645 506 4 428 5822003 650 534 4 866 509 15 749 505 8 260 5622004 561 504 3 583 497 12 426 499 6 470 5842005 806 553 4 915 510 17 202 505 10 472 578Total 4 200 545 28 469 507 92 260 503 47 526 572

Populationb 513 515 510 500 Singapore 1999 6 667 16 625 129 612 1 204 681

2000 5 400 17 529 96 583 555 6632001 5 800 27 667 243 580 2 097 6192002 12 333 23 652 429 632 3 481 6482003 22 591 30 567 532 560 4 204 5872004 22 818 87 529 1 223 597 8 127 6182005 32 500 160 569 2 126 541 11 891 583Total 104 587 360 572 4 778 570 31 559 607

Populationb 517 516 517 500 Sri Lanka 1996 6 500 191 455 506 433 398 583

1997 11 364 142 458 341 487 285 6951998 24 542 218 514 479 501 249 6671999 27 593 219 447 469 557 417 6382000 45 511 320 500 856 481 1 134 6162001 28 607 248 460 687 476 1 590 6182002 38 579 209 459 665 448 2 011 5912003 16 375 106 585 356 478 1 119 6362004 33 606 236 475 878 495 2 623 6182005 28 500 115 496 235 502 654 627Total 256 539 2 004 481 5 472 484 10 480 618

Populationb 509 509 509 494 Cambodia 2010 3 948d 501 8 123 489 276 601

Populationb 510 510 480a These are the only countries with data by age group See table 3 for data for total population of Malaysiab Population data are for the year 2000c Data from the Philippines are not available in DengueNet for the year 2000d Reported cases for age group 0-4 years Reported dengue cases for age group lt1 were not available for Cambodia and denote years and age groups for which the percent male among reported dengue cases was significantly different from the percent male in the population at the α=005 001 and 0001 levels respectively



Philippines Reported number of cases by age and sex was not available for the year 2000 Over these seven years there was a significant excess of male cases among those ge 15 years of age and among infants

(Table 1) Subnational data on the sex distribution of cases ge 15 years of age were also consistent showing an excess of male cases in all regions in this age group (Table 2) For the 1ndash4 and 5ndash14 year age groups the

Table 2 Number and percent male of reported dengue cases in the ge 15 year age group and for all ages combined for the regions of the Lao Peoplersquos Democratic Republic 2001ndash2005 the Philippines 1998ndash1999 and 2001ndash2005 and Sri Lanka 1996ndash2003

Country Administrative region or province Number of cases age 15 years

male cases age ge 15 years

Number of casesall ages

male cases all ages

Lao Peoplersquos Democratic Republicb

Attapeu 95 421 269 461Bokeo 18 444 68 574Borikhamxay 1 140 497 2 837 509Champasack 2 557 440 6 358 480Huaphanh 14 714 25 600Khammuane 1 310 610 3 132 529Luangnamtha 0 00 9 556Luangprabang 558 407 1 777 490Oudomxay 5 400 12 333Phongsaly 0 00 2 500Saravane 83 542 279 509Savannakhet 7 894 643 14 080 578Sekong 26 385 69 522Vientiane 1 016 523 2 705 542Vientiane Municipality 7 319 594 14 719 563Xayabury 287 460 1 082 513Xaysomboun Special Rega 22 591 57 561Xiengkhuang 3 667 3 667All regions combined 22 347 579 47 483 545 Male in population ge15 years 493

Philippinesb

Autonomous Region of Muslim Mindanao 333 583 1 106 534Bicol 2 687 529 8 713 517Cordillera Administrative Region 2 238 557 3 668 550Cagayan Valley 3 292 546 10 049 521Caraga 1 062 590 3 717 525Central Luzon 8 073 599 25 274 535Central Mindanao 2 442 577 5 975 531Central Visayas 3 552 574 20 120 509Eastern Visayas 2 463 555 11 399 520Ilocos 632 561 3 847 527National Capital Region 8 673 586 27 946 537Northern Mindanao 3 193 554 14 811 510Southern Mindanao 3 174 567 12 256 510Southern Tagalog 1 498 635 7 541 529Western Mindanao 2 593 527 7 360 513Western Visayas 1 545 547 8 506 517All regions combined 47 450 571 172 288 523 Male in population ge 15 years 500

Sri Lankabc

Central 666 635 1 163 567Eastern 209 617 428 624North Central 236 682 346 630North Western 730 640 1 117 633Northern 149 597 187 594Sabaragamuwa 434 634 645 581Southern 953 659 1 440 590Uva 132 667 213 573Western 3 349 591 7 407 539All regions combined 6 858 618 12 946 559 Male in population ge 15 years 494

a Reported numbers of dengue cases by sex missing for Xaysomboun Special Region for the year 2006b Total number of cases reported from regions was less than the total number reported at the national level in Table 1c No provincial data available for Sri Lanka for the years 2004 and 2005



proportions of males among reported cases were similar to the male proportion in the population differing by less that 1 (Table 1)

Singapore

Among the countries assessed Singapore had the largest proportion of male dengue cases reported The proportion of men among reported cases was significantly larger relative to the general population ranging from 57 in the 5ndash14 year age group to 61 in the ge 15 year age group The difference was significant in all age groups except in infants where the numbers were small with a consistent pattern over time from 1999 to 2005 (Table 1)

Sri Lanka

In Sri Lanka there was a consistent and significantly larger proportion of males among reported dengue cases than expected in the ge 15 year old age group from 1996 to 2005 (Table 1) This male excess was reported in every province (Table 2) Among 1ndash4 and 5ndash14 year olds there were significantly fewer male cases than expected although there was some annual variation

Dengue epidemiology in Sri Lanka underwent changes during 1996ndash2005 The proportion of reported cases from Western Province which contains

the countryrsquos largest city Colombo decreased from 84 in 1999 to 37 in 2003 (data not shown) The age distribution of reported cases changed from children less than 15 years of age making up more than 60 of cases in 1996ndash1999 to less than 40 of cases in 2001ndash2005 (Table 1)

Malaysia

In Malaysia only the total number of reported male and female dengue cases was available from 1997ndash2008 (Table 3) The majority of reported cases were persons over 15 years of age (between 76 and 82 for the years 1997ndash2008 data not shown) Although dengue data stratified for both age and sex were not available for Malaysia the majority of reported cases were consistently male significantly more than expected (Table 3) For each of the two years for which subnational data were available there was a consistent pattern of excess in reported male cases from each state for 2007 percent male ranged from 56 to 72 with an overall 59 and for 2008 percent male ranged from 58 to 67 with an overall 62

Cambodia

Dengue data for Cambodia were available for 2010 In Cambodia 6116 of 12 347 (496) cases reported in 2010 (through 24 December 2010) were male The proportion of reported male cases by age group were 501 among those aged 4 years or less 489 among those aged 5ndash14 years (significantly less than expected) and 601 among those aged 15 years or more (significantly more than expected) (Table 1)

DISCUSSION

This study based on reported dengue cases from national surveillance systems found a consistent and significant excess among males ge 15 years of age This pattern was consistent over a period of six to 10 years in three culturally and economically diverse countries and over geographically diverse subnational areas within two countries Although age- and sex-stratified data were not available for Malaysia most of reported cases were for persons over 15 years of age and there was a consistent excess of male cases over a 12-year period In a previous study of dengue incidence in Malaysia between 1973 and 1987 the majority of reported cases were also found to be male9 The observed overall pattern of male excess among reported cases in older age groups agrees with

Table 3 Total number of reported dengue cases and percent male among reported dengue cases Malaysia 1997ndash2008a

Year Number of cases male cases

1997 19 429 5441998 27 381 5561999 10 146 5962000 7 103 5922001 16 368 5622002 32 767 5472003 31 545 5612004 33 895 6142005 39 686 5812006 38 556 5812007 48 846 5932008 49 335 615

Percent male in Populationb 508

Denotes years and age groups for which the percent male among reported cases was significantly different from the percent male in the general population at the α=0001 level

a Malaysia did not report male and female dengue cases by age groupb Population data are for the year 2000



previous studies in Singapore41011 and has also been found in more recent dengue surveillance data from the Philippines for 2010 (the Philippines Department of Health personal communication) and Singapore for 200912 Taken together these findings suggest that there may be gender-related differences in dengue incidence which might be due to exposure differences among older adolescents and adults These results in Asia are in contrast to studies in South America which have found either equal proportions of male and female dengue cases or a greater proportion of female cases5713ndash15

The reasons for the excess of reported male dengue cases among older adolescents and adults in Asia observed in this study need further exploration In Singapore a careful analysis attributed greater reported male incidence of dengue from 1998 to 2000 to greater male exposures to dengue-carrying mosquitoes during daytime hours either at the workplace or while travelling to and from work4 This theory is supported by the fact that aggressive public health measures in Singapore have been able to greatly reduce the mean number of mosquitoes in the home10 and the fact that the labour force in Singapore has more males than females4 However this hypothesis has been questioned by a recent serological study of adults by Yew et al11 which 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 Yew et al suggested that malendashfemale differences in the use of health services andor malendashfemale differences in disease severity might account for this discrepancy For example working adults in Singapore (who are more likely to be male)416 may be more likely to seek treatment and be reported to the Ministry of Health when ill because they require medical certification for absences

Yew et al did find males to be significantly more likely to have had a past dengue infection in a multivariate analysis which adjusted for ethnicity age and work status11 The authors felt that the greater presence of males in the workforce could not explain this difference however since housewives retirees and the unemployed were found to have proportionally larger seropositivity than those employed Moreover after adjusting for work status male gender remained significantly associated with past infection status which indicates that the higher seroprevalence could not be fully or explained by employment status alone It was

suggested that movement history should be studied as a possible contributing factor of dengue infection in Singapore

For those le 15 years of age sex differences in the reported number of cases were less striking The differences found among those aged 1ndash4 years and 5ndash14 years were not consistent and the magnitude of the difference was relatively small except in Singapore However the excess number of male infants with dengue in the Philippines and Singapore deserves further study Although there were relatively few reported cases among infants the relatively high dengue case fatality during infancy makes infants an important risk group Male excess in infants was also reported in more recent dengue surveillance data from the Philippines for 2010 (the Philippines Department of Health personal communication) and for those aged 4 years or less from Singapore for 200912

Since the data assessed in this paper are based on national surveillance systems they are subject to the limitations inherent in surveillance data such as underreporting misreporting and reporting biases Evidence from several studies suggests that only a minority of dengue infections are reported to surveillance systems partly because a large proportion of dengue infections are either subclinical or asymptomatic11 While differential reporting by sex is unlikely to fully explain the observed excess in adult males any gender bias that exists in the use of health services could affect the number of reported male and female cases For example since adults appear to be more susceptible than children to developing symptoms after dengue virus infection61718 and if adult men are more likely to seek health care than adult women there may be a larger number of reported adult male cases even if there is no difference in the underlying incidence rates An important limitation was our inability to assess sex differences in reported dengue cases among adults more precisely This was not ideal particularly for comparing working adults and retirees Since the epidemiology of dengue is rapidly changing and has evolved into more of an adult disease rather than a paediatric disease in some countries610 continued monitoring and assessment by appropriate age groups are important Lastly there are also likely to be variations over time and across countries in reporting practices and case definitions While one of the aims of DengueNet was to harmonize case definitions case definitions are not provided on DengueNet Due to such



variability it is inappropriate to combine data from all countries The fact that we found a consistent excess of males in the older age group across many years and in both national and subnational data from several Asian countries is an important strength of this study

In conclusion the current study found a consistent pattern of male predominance in the reported number of incident dengue cases among persons 15 years or older in several Asian countries Since collapsing the data over all ages would have masked some of the observed differences the findings indicate the importance of reporting sex and age stratified data for dengue surveillance Assessment of how dengue differs for males and females by age is important because biological and gender-related factors can change over the human lifespan and gender-related factors can differ across countries Further research is required to identify the cause(s) of such sex-specific differences to target preventive measures to reduce the dengue burden in the region

Confl icts of interest

None declared

Funding


Acknowledgements

The authors would like to thank the WHO Western Pacific Region Country Office staff for assisting with surveillance data collection and reporting We would also like to thank Renu Dayal Drager and Richard Anker for their comments

References

1 Fact sheet Ndeg117 Dengue and dengue hemorrhagic fever March 2009 Geneva World Health Organization (httpwwwwhointmediacentrefactsheetsfs117en accessed on 26 December 2010)

2 Dengue in the Western Pacific Manila World Health Organization Western Pacific Regional Office (httpwwwwprowhointtopicsdengueen accessed on 20 December 2010)

3 Huy R et al National dengue surveillance in Cambodia 1980ndash2008 epidemiological and virological trends and the impact of vector

control Bulletin of World Health Organization 2010 88(9)650ndash657 doi102471BLT10081729 pmid20865059

4 Eong OE Changing pattern of dengue transmission in Singapore Dengue Bulletin 2001 2540ndash4 (httpwwwsearowhointLinkFilesDengue_Bulletin_Volume_25_ch7pdf accessed on 6 June 2011)

5 Kaplan JE et al Epidemiologic investigations of dengue infection in Mexico 1980 American Journal of Epidemiology 1983 117335ndash343 pmid6829561

6 Lin CC et al Characteristic of dengue disease in Taiwan 2002ndash2007 American Journal of Tropical Medicine and Hygiene 2010 82(4) 731ndash739 doi104269ajtmh201009-0549pmid20238527

7 Global Health Atlas Geneva World Health Organization (httpappswhointglobalatlasdefaultasp accessed on 26 December 2010)

8 World Population Prospects The 2008 Revision Highlights Working Paper No ESAPWP210 New York United Nations Department of Economic and Social Affairs 2009 (httpwwwunorgesapopulationpublicationswpp2008wpp2008_highlightspdf accessed on 6 June 2011)

9 Shekhar KC Huat OL Epidemiology of denguedengue hemorrhagic fever in Malaysiandasha retrospective epidemiological study 1973ndash1987 Part I Dengue hemorrhagic fever (DHF) [Review] Asia-Pacific Journal of Public Health 1992-1993 615ndash25 doi101177101053959300600203 pmid1308765

10 Ooi EE Goh KT Gubler DJ Dengue prevention and 35 years of vector control in Singapore Emerging Infectious Diseases 2006 12(6)887ndash893 pmid16707042

11 Yew YW et al Seroepidemiology of dengue virus infection among adults in Singapore Annals of the Academy of Medicine Singapore 2009 38667ndash675 pmid19736569

12 Communicable Diseases Surveillance in Singapore 2009 Singapore Ministry of Health 2010 (httpwwwmohgovsgcontentmoh_webhomePublicat ionsRepor ts2010communicable_diseasessurveillanceinsingapore2009html accessed on 26 December 2010)

13 Guumlnther J et al Distribution of dengue cases in the state of Oaxaca Mexico during the period 2004ndash2006 Journal of Clinical Virology 2009 45218ndash222 doi101016jjcv200905007 pmid19487157

14 Ameacutelia PA et al Dengue epidemic in Beleacutem Paraacute Brazil 1996ndash1997 Emerging Infectious Diseases 2000 6(3) pmid10827121

15 Garciacutea-Rivera EJ Rigau-Peacuterez JG Dengue severity in the elderly in Puerto Rico Pan American Journal of Public Health 2003 13362ndash368 (httpwwwscielosporgscielophpscript=sci_arttextamppid=S1020-49892003000500004amplng=enampnrm=isoamptlng=en accessed on 6 June 2011)

16 Ooi EE et al Dengue seroepidemiology in Singapore Lancet 2001 3357(9257)685ndash686 pmid11247554

17 Endy TP et al Epidemiology of inapparent and symptomatic acute dengue virus infection a prospective study of primary school children in Kamphaeng Phet Thailand American Journal of Epidemiology 2002 156(1) 40ndash51 doi101093ajekwf005 pmid12076887

18 Burke DS et al A prospective study of dengue infections in Bangkok American Journal Tropical Medicine and Hygiene 1988 38(1)172ndash180 pmid3341519


Ler et alThe 2005 and 2007 dengue epidemics in Singapore

Epidemiological characteristics of the 2005 and 2007 dengue epidemics in Singapore ndash similarities and distinctionsTeck Siang Lera Li Wei Angb Grace Siew Lian Yapc Lee Ching Ngc Ji Choong Taid Lyn Jamesb and Kee Tai Gohe

Correspondence to Teck Siang Ler (e-mail tslermecom)

a Hospital Services Division Ministry of Health Singaporeb Communicable Diseases Division Ministry of Health Singaporec Environmental Health Institute National Environment Agency Singapored Environmental Health Department National Environment Agency Singaporee Offi ce of the Director of Medical Services Ministry of Health Singapore Submission date 29 November 2010 Publication date 20 May 2011doi 105365wpsar201011011

Introduction We investigated the epidemiological features of the 2007 dengue outbreak to determine the factors that could have triggered it two years after the previous large outbreak in 2005

Methods All laboratory-confirmed cases of dengue reported during the year as well as entomological and virological data were analysed

Results A total of 8826 cases including 24 deaths were reported in 2007 giving an incidence of 1923 cases per 100 000 residents and a case-fatality rate of 027 The median age of the cases was 37 years (interquartile range 25 to 50) with an age range from two days to 101 years which was higher than the median age of 31 years (interquartile range 20 to 42) with a range from four days to 98 years in 2005 The overall Aedes premises index in 2007 was 068 lower than the 115 observed in 2005 The predominant dengue serotype in 2007 was dengue virus DENV-2 which re-emerged with a clade replacement in early 2007 and overtook the predominant serotype (DENV-1) of 2005 Seroprevalence studies conducted in the three largest outbreak clusters revealed that 732 of residents with recent infection were asymptomatic

Discussion With the exception of an increase in the median age of the cases and a change in the predominant dengue serotype the epidemiological features of the 2007 epidemic were largely similar to those of 2005 Singapore remains vulnerable to major outbreaks of dengue despite sustained vector control measures to maintain a consistently low Aedes premises index

Original Research

The four serotypes of dengue virus (DENV) (family Flaviviridae) are transmitted from infected to susceptible humans primarily by Aedes

mosquitoes1 Following infection an individual remains vulnerable to re-infection with a different serotype of the virus Clinically-apparent disease usually occurs with the first or second infections rarely with the third or fourth2 There is a wide spectrum of clinical manifestations from asymptomatic to undifferentiated fever dengue fever (DF) dengue haemorrhagic fever (DHF) and dengue shock syndrome (DSS)3

With an estimated 50 million infections annually3 the burden of dengue is a heavy one indeed4 especially to countries in the Asia Pacific region5 Despite sustained vector control efforts Singapore has also not been spared from the disease Although the Aedes premises index (percentage of premises found breeding Aedes mosquitoes) has been consistently maintained at

between 1 and 2 since the 1980s Singapore still experienced successive dengue outbreaks at intervals of five to seven years6ndash10

In 2005 Singapore experienced its largest dengue outbreak on record10 Only two years thereafter another outbreak ensued As this was not in keeping with the five-to-seven-year cycles previously experienced we undertook epidemiological entomological and virological studies to investigate the features of the 2007 dengue outbreak and compared them with those of 2005 to determine the factors that triggered the outbreak

METHODS

Dengue surveillance and control in Singapore

In Singapore the Ministry of Health is responsible for the epidemiological surveillance and clinical management of dengue The National Environment Agency (NEA)


Ler et al The 2005 and 2007 dengue epidemics in Singapore

Ministry of Environment and Water Resources takes charge of vector surveillance control and research

Notifi cation

All medical practitioners are required by the Infectious Diseases Act to report all clinically-diagnosed and laboratory-confirmed dengue cases and deaths to the Ministry of Health by facsimile or by online electronic notification within 24 hours They also are required to report cases that were initially diagnosed as DF but that later satisfied criteria for DHF11 Directors of clinical laboratories also are mandated to notify the Ministry of Health whenever any blood sample provides evidence of recent dengue infection Laboratory tests used in Singapore are RTndashPCR12 immunochromatographic assays and commercial kits for the detection of NS1 or anti-DENV IgM Epidemiological data routinely collected included name identification number age ethnicity gender occupation residential and workplaceschool addresses and date of onset of illness

Vector control

On receipt of notification epidemiological data are immediately transmitted to the NEA which undertakes field epidemiological investigations if necessary All reported cases and breeding habitats are plotted using a geographical information system to determine clustering of cases and to identify high-risk areas for priority vector control13

Serotype surveillance

The Environmental Health Institute (EHI) at the NEA monitors the circulating DENV serotypes and genotypes using samples submitted by Tan Tock Seng Hospital and by a network of sentinel private medical practitioners Detection of dengue virus RNA and serotyping was performed with an in-house real-time PCR12 Phylogenetic analyses of the dengue virus envelope protein gene has been described elsewhere14 Serotyping of dengue virus was also carried out at the Department of Pathology Singapore General Hospital National University Hospital and Kandang Kerbau Hospital

Data analysis

Only laboratory-confirmed cases reported to the Ministry of Health were included in the analysis reported here we further restricted these cases to those who were Singaporean citizens or permanent residents All

duplicate notifications were removed before analysis Cases with a history of travel within seven days before the onset of illness to countries where dengue also occurred were classified as imported and were not included in the analysis A cluster was defined as two or more cases within a 150 meter radius (based on residential or workplaceschool addresses) and with the onset of illness within a 14-day period Denominators for the calculation of incidence rates were based on the estimated mid-year population obtained from the Singapore Department of Statistics Ministry of Trade and Industry15

Seroprevalence survey

To determine the proportion of asymptomatic infections voluntary blood sampling was carried out in 2007 in the three largest clusters of cases at Bukit Batok Woodlands and Pasir Ris where all household members residing in each site were invited to participate A recruitment and sampling site was set up within each of the clusters to take blood samples (3 ml) and to conduct face-to-face interviews Only residents who gave written consent were interviewed Individuals whose serum samples contained anti-DENV IgM were scored as having a recent infection and those whose serum samples contained anti-DENV IgM but could not recall any recent symptoms of dengue infection were classified as asymptomatic16

Statistical analysis

Microsoft Office Excel 2007 and SPSS 150 were used for statistical analyses Differences between the age-gender-standardized incidence rates were computed and tested for statistical significance using the Z-test17 Statistical significance was taken at P lt 005 level

Ethics

The study was conducted primarily as part of a national public health programme with supplemental data obtained from a community seroprevalence study which had been approved by the National Environment Agency Bioethics Review Committee (IRB 0052) in 2007

RESULTS

Epidemiological fi ndings

A total of 8826 laboratory-confirmed cases of dengue were reported in 2007 an incidence rate of 1923 per 100 000 population Of these 8637 (979) were DF and 189 (21) were DHF Twenty-four fatalities were



reported in 2007 comprised of eight DF and 16 DHF cases a case-fatality rate (CFR) of 027 for all dengue cases and 85 for all DHF cases comparable to the outbreak in 2005 In 2005 27 fatalities were reported comprising three DF and 24 DHF cases a CFR of 019 for all dengue cases and 61 for all DHF cases10 The outbreaks in 2005 and 2007 differed in that 257 cases of DFDHF were reported in January 2007 far fewer than the 1262 cases reported in the same period of 200510 Most cases (1633) were reported in July 2007 two months earlier than the peak of 2770 cases that were reported in September 200510 (Figure 1)

The median age of DFDHF cases among Singapore residents in 2007 was 37 years (interquartile range 25 to 50) with a range from two days to 101 years higher than the median age of 31 years (interquartile range 20 to 42) with a range from four days to 98 years in 200510 The age-specific incidence rate for dengue was

highest in the age group 55 years and above in 2007 In 2005 it was highest in the 15 to 24-year-old age group (Table 1)10

The incidence in males was significantly higher than in females (2093 per 100 000 and 1503 per 100 000 respectively) and that was true for all ethnic groups (P lt 001) Among Singapore residents in 2007 the age-gender-adjusted incidence rate of DFDHF was highest in the Chinese (1723 per 100 000) (P lt 001) followed by the Malays (1469 per 100 000) (P lt 005) and the Indians (1209 per 100 000) Among Singapore residents in 2005 the age-gender-adjusted incidence rate of DFDHF was also highest in the Chinese (3128 per 100 000) followed by the Malays (2884 per 100 000) and the Indians (1739 per 100 000)10

The incidence rate in 2007 was highest among those residing in private condominiums (4538 per

Table 1 Age-specific incidence rates of reported indigenous cases of dengue Singapore 2005 and 2007

Age group (years)

2005 2007

Number () Incidence rate (per 100 000) Number () Incidence rate

(per 100 000)0ndash4 184 (13) 869 100 (12) 4805ndash14 1 749 (125) 3343 530 (64) 102615ndash24 3 078 (219) 4743 1 270 (153) 176725ndash34 3 253 (232) 3768 1 802 (217) 188835ndash44 2 762 (197) 3628 1 777 (214) 219745ndash54 1 587 (113) 2621 1 134 (137) 174455+ 1 419 (101) 2177 1 674 (202) 2289

Total 14 032 (1000) 3289 8 287 (1000) 1806

Figure 1 Monthly distribution of dengue cases in 2005 and 2007

3000

2500

2000

1500

1000

500

0Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Months

Num

ber o

f cas

es 2007 2005



100 000) and was 13 times that of those residing in compound houses (3511 per 100 000) and almost three times that of those residing in high-rise public housing apartments (1565 per 100 000) This was different from 2005 when the lowest rate (2988 per 100 000) was found in residents of private condominiums while the incidence rate of those residing in compound houses was 7107 per 100 000 and 3321 per 100 000 for those living in high-rise public housing apartments10

Cases were concentrated in the urban and suburban centres of the central (290) and south-eastern (204) parts of Singapore with further geographical extension to the western suburban areas (Figure 2) A total of 3877 cases from 949 clusters (median three cases range two to 117 cases) were identified The total number of cases from reported clusters constituted less than half (468) of all reported cases

The largest clusters were at Bukit Batok (117 cases July to September) Pasir Ris (71 cases May to July) and Woodlands (67 cases July to August) Two of these localities (Woodlands and Bukit Batok) also were affected in 2005 but with fewer cases10 The seroprevalence study involving 1708 residents conducted in these three localities revealed that 33 (n = 56) had recent dengue infections Among these residents with recent infection 732 ranging from 571 at Woodlands to 818 at Pasir Ris did not recall any symptoms within the previous three months

Virological fi ndings

All four dengue virus serotypes circulated in Singapore from 2005 to 2007 The predominant

serotype circulating in 2005 was DENV-110 but in January 2007 it was overtaken by DENV-2 which re-emerged with a clade replacement14 and has since remained the predominant serotype (Figure 3) In 2007 RNA from 1044 confirmed cases of acute dengue infection were serotyped at the EHI NEA Department of Pathology Singapore General Hospital and the laboratories at Tan Tock Seng Hospital and National University Hospital and comprised 883 DENV-2 64 DENV-1 46 DENV-3 and 07 DENV-4

Entomological fi ndings

As in 2005 the distribution of dengue cases in 2007 was more closely associated with Aedes aegypti than with Aedes albopictus breeding sites (Figure 2)10 The overall Aedes premises index was 068 in 2007 lower than the 115 observed in 200510

The top three breeding habitats for Aedes aegypti in 2005 and 2007 were similar with domestic containers (26 in 2005 32 in 2007) ornamental containers (24 in 2005 21 in 2007) and flower pot plates (7 in 2005 11 in 2007) constituting more than half of all breeding habitats10 However for Aedes albopictus there was a decrease in the number of breeding sites found in discarded receptacles (from 21 in 2005 to 4 in 2007)10

DISCUSSION

With the exception of median age of the cases and the predominant dengue serotype the epidemiological features of the 2007 epidemic were largely similar to those of 2005 The increase in median age and the

Figure 2 Geographical distribution of Aedes albopictus Aedes aegypti and dengue cases Singapore 2005 and 2007

Aedes albopictusAedes aegyptiDengue cases


Year 2005 Year 2007



finding that those aged more than 55 years had the highest incidence are poorly understood It is interesting to note that this phenomenon has accompanied the switch to DENV-2 and both the phenomenon and predominance of DENV-2 have persisted till 2010

After the 2005 outbreak the dengue control system was enhanced going into 2007 First manpower that routinely carried out Aedes surveillance and source reduction was increased from 250 in 2005 to about 500 in 2007 On average 116 764 residential premises and 3011 non-residential premises (eg construction sites schools) were inspected every month in 2007 resulting in almost all premises being inspected within the year13 Second an intensive source reduction exercise was conducted by NEA officers two to three months before the expected dengue season to remove breeding and potential breeding grounds Third early warnings systems were developed through virological surveillance and ambient temperature monitoring providing temporal risk stratification14 Lastly qualitative spatial risk stratification was performed using case virus and larva surveillance data to guide the deployment of staff Despite the enhanced vector control which led to a premises index of 068 which was significantly lower than the 224 17 and 2 found from 2002 to 2004 (when the same cosmopolitan genotype DENV was predominant) respectively an outbreak still ensued

Phylogenetic analyses of DENV-2 envelope gene sequences at EHI NEA revealed that the switch in predominant serotype in early 2007 coincided with a clade replacement within DENV-2 Within the Cosmopolitan genotype of DENV-2 there were two distinct subclades with strong temporal topology The old clade was detected from 2000 to 2005 and the new clade from 2007 to 200814 The role of the small genetic changes between the two clades in viral fitness is being investigated A similar observation was reported in Cuba where the authors hypothesized that the 1997 severe outbreak in Cuba was a result of a small mutation that improved the fitness of DENV-218

The epidemiology of dengue in Singapore has evolved from a paediatric problem in the 1960s to an adult infection since the 1980s The median age has shifted from 14 years in 197319 to 37 years in 2007 This has been attributed to the lower transmission rate which was demonstrated by a mathematical model that showed a declining trend in the force of infection (defined as per capita rate at which susceptible individuals in the community acquire infection)20 since the nationwide vector control programme was first implemented in the late 1960s

Previous studies have demonstrated that more than 90 of dengue infections were asymptomatic21 In a survey representative of the adult general population

Figure 3 Dengue virus serotypes identified at Environmental Health Institute Department of Pathology Singapore General Hospital and laboratories at Tan Tock Seng Hospital and National University Hospital Singapore 2005ndash2007

0

10

20

30

40

50

60

70

80

90

100Ja

n-05 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec

Jan-

06 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec

Jan-

07 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec

DENV-1 DENV-2 DENV-3 DENV-4

Month-Year

Dist

ribut

ion

of s

erot

ype



conducted in 2004 the prevalence of asymptomatic infections was found to be 9522 The prevalence of asymptomatic dengue infections in surveys conducted during the 2007 outbreak in three public housing estates ranged from 571 to 818 The differences could be due to different methodologies

A limitation on this study would be the reliance on notification data The incidence rate is actually the case notificationdetection rate Although medical practitioners and directors of clinical laboratories were required to report all cases of DFDHF to the Ministry of Health mild cases with undifferentiated fevers may not seek medical care and so may not be reported The actual incidence of dengue infection in 2007 therefore could be higher than was reported A limitation of the seroprevalance survey was that convenience sampling was done and data collected may not be representative of the population Nevertheless it gives us an idea of the prevalence of asymptomatic infections in these outbreak areas

The 2007 dengue epidemic in Singapore demonstrated the dynamic interactions of the virus human host vector and the environment as evidenced by the resurgence caused by introduction of a new clade of DENV-2 despite sustained vector control efforts Given the large estimated proportion of asymptomatic infections the real extent of the problem could be much larger than what is currently known Singapore remains vulnerable to major outbreaks of dengue through the constant introduction of viruses from travellers and through local evolution of the virus


None declared

Funding

None

References

1 Halstead SB Pathogenesis of dengue challenges to molecular biology Science 1988 239 476ndash81 doi101126science3277268 pmid3277268

2 Sabin AB Schlesinger RW Production of immunity to dengue with virus modified by propagation in mice Science 1945 101 640ndash642 doi101126science1012634640 pmid17844088

3 Dengue guidelines for diagnosis treatment prevention and control ndash New edition Geneva World Health Organization 2009 (httpwhqlibdocwhointpublications20099789241547871_engpdf accessed on 28 February 2011)

4 Suaya JA et al Cost of dengue cases in eight countries in the Americas and Asia a prospective study The American Journal of Tropical Medicine and Hygiene 2009 80846ndash855 pmid19407136

5 The Dengue Strategic Plan for the Asia Pacific Region 2008ndash2015 New Delhi (SEARO) and Manila (WPRO) World Health Organization 2008 (httpwwwsearowhointLinkFilesDengue_Dengue_Strategic_Plan_for_the_Asia-Pacific_Region_(2008-2015)pdf accessed on 28 February 2011)

6 Goh KT et al Epidemiological aspects of an outbreak of dengue feverdengue haemorrhagic fever in Singapore The Southeast Asian Journal of Tropical Medicine and Public Health 1987 18295ndash302 pmid3433161

7 Epidemiology of dengue feverdengue haemorrhagic fever World Health Organization World Epidemiological Report 1990 65101ndash108 (httpwhqlibdocwhointwerWHO_WER_1990WER1990_65_101-10820(NC2B014)pdf accessed on 28 February 2011)

8 Ministry of Health Committee of Epidemic Diseases Surveillance of dengue feverdengue haemorrhagic fever 1992 Epidemiological News Bulletin (Singapore) 1993 1913ndash17

9 Ministry of Health Committee of Epidemic Diseases Dengue surveillance in Singapore 1998 Epidemiological News Bulletin (Singapore) 1999 251ndash3


11 Goh KT Ong A Low J editors A guide on infectious diseases of public health importance in Singapore 6th ed Singapore Ministry of Health and Tan Tock Seng Hospital 2004

12 Lai YL et al Cost-effective real-time reverse transcriptase PCR (RT-PCR) to screen for dengue virus followed by rapid single-tube multiplex RT-PCR for serotyping of the virus Journal of Clinical Microbiology 2007 45935ndash941 doi101128JCM01258-06 pmid17215345

13 Tang CS et al Surveillance and control of dengue vectors in Singapore Epidemiological News Bulletin 2006 32 1ndash9 (httpwwwmohgovsgdammoh_webStatisticsEpidemiological_News_Bulletin2006ENB01Q_06pdf accessed on 28 February 2011)


15 Singapore Resident Population 2003ndash2008 Singapore Department of Statistics 2009


17 Armitage P Berry G Statistical Methods in Medical Research 2nd ed Oxford Blackwell Scientific 1987

18 Rodriquez-Roche R et al Virus role during intraepidemic increase in dengue disease severity Vector-Borne and Zoonotic Diseases 2011 1100

19 Goh KT Changing epidemiology of dengue in Singapore Lancet 1995 346 1098 doi101016S0140-6736(95)91771-3 pmid7564804

20 Egger JR et al Reconstructing historical changes in the force of infection of dengue fever in Singapore implications for surveillance and control Bulletin of the World Health Organization 2008 86187ndash196 doi102471BLT07040170 pmid 18368205

21 Goh KT Seroepidemiology of dengue virus infection in Singapore In Goh KT (ed) Singapore Ministry of the Environment 1998 50ndash72

22 Ye T et al Seroprevalence study on past and recent dengue virus infection in Singapore Epidemiological News Bulletin (Singapore) 2007 3336ndash41 (httpwwwmohgovsgcontentdammoh_webStatisticsEpidemiological_News_Bulletin2007ENB03Q_07pdf accessed on 28 February 2011)


Phung et alPandemic A(H1N1) 2009 infection in Queensland Australia

Surveillance of hospitalizations with pandemic A(H1N1) 2009 infl uenza infection in Queensland AustraliaHai Phungab Frank Bearda Christine Selveya Ranil Appuhamya and Frances Birrellab

Correspondence to Hai Phung (e-mail Hai_Phunghealthqldgovau)

a Communicable Diseases Branch Queensland Health Brisbane Queensland Australiab School of Public Health Queensland University of Technology Brisbane Queensland AustraliaSubmission date 29 November 2010 Publication date 30 May 2011doi 105365wpsar201011013

Original Research

Objective To describe the demographic and clinical characteristics of patients hospitalized with pandemic A(H1N1) 2009 infection in Queensland Australia between 25 May and 3 October 2009 and to examine the relationship between timing of antiviral treatment and severity of illness

Method Using data from the Queensland Health EpiLog information system descriptive analysis and logistic regression modelling were used to describe and model factors which influence patient outcomes (death admission to intensive care unit andor special care unit) Data on patients admitted to hospital in Queensland with confirmed pandemic A(H1N1) 2009 infection were included in this analysis

Results 1236 patients with pandemic A(H1N1) 2009 infection were admitted to hospitals in Queensland during the study period Of the total group 15 were admitted to an intensive care unit or special care unit 3 died 34 were under the age of 18 years and 8 were 65 years of age or older and 55 had at least one underlying medical condition Among the 842 patients for whom data were available regarding the use of antiviral drugs antiviral treatment was initiated in 737 (875) patients treatment commenced at a median of one day (range 1ndash33 days) after onset of illness Admission to an intensive care unit or special care unit (ICUSCU) or death was significantly associated with increased age lack of timeliness of antiviral treatment chronic renal disease and morbid obesity

Discussion Early antiviral treatment was significantly associated with lower likelihood of ICUSCU admission or death Early antiviral treatment for influenza cases may therefore have important public health implications

The first case of pandemic A(H1N1) 2009 influenza infection in Australia was reported in a 28-year-old female in Queensland on 9 May

2009 Queensland along with other Australian states and territories invested in intense public health efforts to manage and control the outbreak1 Information on the clinical spectrum of pandemic A(H1N1) 2009 illness and factors associated with admission to hospital is scarce in Australia Internationally it had been reported that the majority of the early cases reported mild influenza-like illnesses with fever and respiratory symptoms but more severe infections have also occurred2ndash6 Obesity underlying health conditions and delayed neuraminidase inhibitor treatment were the major risk factors for a poor outcome of infection45 Risk factors for poor clinical outcomes for pandemic A(H1N1) 2009 infection in Australia warrant further investigation to help clinicians indentify patients at high risk of severe disease

Several surveillance systems were used to monitor and evaluate the progression of the outbreak

in Queensland These systems initially focused on notification data from public health units and laboratories However as the pandemic progressed hospitalization data became of paramount importance for health planners A new state-wide hospital-based surveillance application EpiLog was developed to monitor real-time admissions of patients with pandemic A(H1N1) 2009 infection to all public hospitals in Queensland Data were also received from major private hospitals This allowed monitoring of the outbreak and its impact on the hospital system

We present findings from a retrospective analysis of data collected by this new surveillance system The aims of the analysis were to describe the demographic and clinical characteristics of patients hospitalized with pandemic A(H1N1) 2009 infection in Queensland (between 25 May and 3 October 2009) and to examine the relationship between timing of antiviral treatment and severity of illness


Phung et al Pandemic A(H1N1) 2009 infection in Queensland Australia

METHODS AND DATA COLLECTION

The data for this analysis were extracted from EpiLog This web-based application was developed in Queensland for the surveillance of patients admitted to public hospitals with suspected or confirmed pandemic A(H1N1) 2009 influenza infection The same data elements were provided by major private hospitals using a purpose-designed Microsoft Excel spreadsheet

Data elements entered into EpiLog included pandemic A(H1N1) 2009 influenza infection status self-reported medical conditions (morbid obesity pregnancy immunocompromised status diabetes chronic respiratory disease renal disease and cardiac disease) time of antiviral treatment initiation and intubation or ventilation status EpiLog is linked to the Hospital Based Clinical Information System (HBCIS) used in public hospitals which stores data relating to patient demographics and hospital stay with a unique patient identifier Patient demographic data admission and discharge details and ward transfer details were updated in EpiLog via this interface

Data were extracted from EpiLog for analysis and aggregated with data received from private hospitals Data on patients with confirmed pandemic A(H1N1) 2009 influenza infection who were admitted to hospitals in Queensland between 25 May and 3 October 2009 were analysed Admission to an intensive care unit (ICU) or a special care unit (SCU) was used as a proxy for severity of illness


The proportion of ICUSCU admissions among hospitalized patients with pandemic A(H1N1) 2009 infection was calculated Univariate association of various factors were evaluated using descriptive statistical techniques The association between ICUSCU admission and patient characteristics (age sex indigenous status underlying medical conditions and whether antiviral treatment was received) was evaluated using univariate logistic regression followed by multivariate forward stepwise logistic regression test

To assess the predictive value of various factors the area under the receiver-operating characteristic (ROC) curves was calculated The ROC curve evaluates the ability of the full logistic regression model to discriminate7 patients admitted to ICUSCU from those with no ICU

SCU admission The SPSS package (Version 12) was used for all analyses8

Ethical clearance was not required for this analysis This analysis was conducted as a clinical audit (during a public health emergency event) required under the Health Services Act (1991)

RESULTS

Patient characteristics

There were 1236 hospitalized patients recorded in Queensland with confirmed pandemic A(H1N1) 2009 infection between 25 May and 3 October 2009 Table 1 summarizes selected demographic and clinical characteristics of these patients The median age was 29 years (range less than 1 month to 90 years) Eighty-four patients (7) were less than one year of age 420 (34) were under 18 years of age and 96 (8) were aged 65 years or over Of the total study sample 686 (55) were recorded as having at least one underlying medical condition and 162 (13) had at least two such conditions A total of 80 patients were pregnant (31 of female patients between 18ndash45 years old) Sixty patients (5) were morbidly obese with all but one of these patients (98) being aged 25 years or older Fifteen per cent of the patients admitted to hospital with confirmed pandemic A(H1N1) 2009 infection were indigenous

Antiviral drug administration data were available for 842 patients with 703 (83) recorded as receiving oseltamivir 9 (1) zanamivir and 25 (3) treated with an unspecified antiviral and 105 (13) as not having received any antiviral drugs The median time from the onset of illness to the initiation of antiviral therapy was one day (range less than 1 day to 33 days) Among patients for whom data on antiviral therapy timing were available (842) 561 (67) received antiviral treatment within 48 hours of the onset of symptoms

Intensive care unit and special care unit admissions and mortality

Patients admitted to ICUSCU represented 189 of the 1236 (15) patients The median age was 49 years (range 1 to 84 years) Patients who were admitted to ICU or SCU were more likely to be older have diabetes or chronic cardiac or renal disease be morbidly obese and not have received antiviral treatment within 48 hours of



disease onset compared to those that were not admitted to ICU or SCU (Table 2) The median time from the onset of illness to the initiation of antiviral therapy was 3 days (range zero to 28 days) for patients admitted to ICU or SCU Among patients who were admitted to ICU or SCU 12 (67189) received antiviral drugs within 48 hours of the onset of illness There was no

significant difference in the proportion of indigenous and non-indigenous patients admitted to ICU or SCU

Forty-one patients (3) hospitalized with pandemic (H1N1) 2009 infection died The median age of patients who died was 51 years (range 13 to 84 years) the median time from the onset of illness to death was

Table 1 Characteristics of hospitalized patients withconfirmed pandemic A(H1N1) 2009 infection (N=1236) Queensland Australia (May to October 2009)

Frequency ()

Hospital TypePublic 1019 (175)Private 217 (825)

Patientrsquos age (years)Less than 10 305 (247)10ndash17 115 (93)18ndash24 109 (88)25ndash44 280 (227)45ndash64 326 (264)65+ 96 (78)

Indigenous statusIndigenous 191 (154)Non-indigenous 924 (748)Unknown 121 (97)

SexMale 568 (459)Female 669 (541)

Underlying medical conditionsChronic respiratory disease 415 (335)Diabetes 122 (99)Morbid obesity 60 (49)Immunocompromised 87 (70)Chronic cardiac disease 97 (76)Chronic renal disease 40 (32)Pregnancy (N=669) 80 (120)

Number of medical conditionsNone 550 (445)One 524 (424)Two 117 (95)Three 37 (30)Four 8 (06)

Antiviral treatment (N=842)Yes 737 (875)No 105 (125)

Antiviral treatment initiated within 48 hours of onset (N=842)

Yes 561 (667)No 281 (333)

Only femaleNote numbers may not add to total due to missing data

Table 2 Characteristics and univariate analysis of factorsassociated with ICUSCU admission in hospitalized patients with confirmed pandemic A(H1N1) 2009 infection Queensland Australia (May to October 2009)

Admission to ICU or SCUNo Yes Yes () OR (95 CI)

Hospital typePublic 857 162 146 19 (06ndash56)Private 190 27 165 1

Age (years)Less than 10 296 7 23 052 (016ndash17)10ndash17 110 5 43 118ndash44 308 75 196 54 (21ndash135)45ndash64 233 87 272 82 (32ndash208)65+ 69 24 258 77 (28ndash210)

SexMale 471 91 162 1Female 548 110 167 13 (08ndash19)

Indigenous statusIndigenous 165 26 152 12 (05ndash14)Non-indigenous 784 140 164 1

Chronic respiratory diseaseYes 335 60 145 14 (04ndash11)No 578 115 177 1

DiabetesYes 96 26 213 12 (07ndash22)No 815 143 149 1

Pregnantdagger

Yes 61 17 213 11 (04ndash26)No 442 85 127 1

ImmunocompromisedYes 79 8 92 14 (03ndash13)No 834 161 162 1

Morbid obesityYes 37 23 383 36 (21ndash62)No 871 151 148 1

Chronic renal diseaseYes 27 13 325 37 (18ndash68)No 882 156 150 1

Chronic cardiac diseaseYes 73 24 302 24 (15ndash38)No 840 144 153 1

Antiviral treatment initiated within 48 hours of onsetYes 484 69 125 1No 194 85 305 21(14ndash30)

Odds Ratio and 95 Confi dence Interval daggerOnly femaleNote numbers may not add to total due to missing data



within 48 hours of onset When these variables were included in a single model adjusting for each other all factors remained significant except for chronic cardiac disease Compared to patients who had received antiviral treatment within 48 hours of onset patients who had not received antiviral drugs or received antiviral treatment later than 48 hours of onset were twice as likely to be admitted to ICU or SCU A ROC curve was developed (Figure 1) from the fitted predicted value from the final logistic regression model The area under the operator characteristic curve was 076

DISCUSSION

Using data from a newly established hospitalisation surveillance system we examined the epidemiological profile of 1236 patients admitted to hospitals in Queensland Australia with confirmed pandemic A(H1N1) 2009 infection We found that 34 of the hospitalized patients were under the age of 18 years more than one third were between the ages of 18 and 49 years and only 8 were 65 years of age or older This pattern is similar to results reported elsewhere4ndash6

Pregnancy has been associated with increased hospitalization and severity of illness due to pandemic

14 days (range 1 to 68 days) and 27 (67) had an underlying medical condition Of the patients who died 80 had received antiviral drugs Among the patients who died who received antiviral treatment the median time from the onset of illness to the initiation of antiviral therapy was 3 days (range less than 1 day to 28 days) Forty-eight per cent of those who died received antiviral therapy within 48 hours of the onset of symptoms

Patients with any severe outcome (defined as those admitted to an ICU or SCU plus those who died) were older (median age 50 years range from less than 1 to 85) and had a longer median time (4 days range between less than 1 day to 28 days) between onset of illness and the initiation of antiviral therapy compared to other hospitalized patients in whom the median age was 30 years (range from less than 1 to 90) and the median time between onset and receiving antiviral drugs was 1 day (range from less than 1 day to 33 days)

Tables 2 and 3 show the univariate and multivariate results of the logistic regression analysis In the unadjusted model factors significantly associated with increased likelihood of admission to ICU or SCU were older age chronic renal disease chronic cardiac disease morbid obesity and not receiving antiviral treatment

Table 3 Multivariate analysis of factors associated with admission to ICU or SCU in hospitalized patients with confirmed pandemic A(H1N1) 2009 infection Queensland Australia (May to October 2009)

OR (95 CI)

Age (years)

Less than 10 01 (01ndash07)

10ndash17 1

18ndash44 39 (14ndash112)


65+ 57 (18ndash182)

Antiviral treatment initiated within 48 hours of onset

Yesdagger 1

No 21 (134ndash33)

Chronic renal disease

Nodagger 1

Yes 27 (13ndash57)

Morbid obesity

Nodagger 1

Yes 19 (14ndash36)

Odds Ratio and 95 Confi dence Interval dagger Reference group

Figure 1 Receiver-operating characteristic curve for multivariate logistic regression model to predict admission to ICU or SCU in hospitalised patients with confirmed pandemic A(H1N1) 2009 infection Queensland Australia (May to October 2009) [Area under curve = 076 (95 Confidence Interval = 072 ndash 079 Plt0001)]

10

08

06

04

02

0000 02 04 06 08 10

1-Specifi cityDiagonal segments are produced by ties

Sens

itivi

ty

ROC Curve



A(H1N1) 2009 infection49ndash11 In our study 7 of hospitalized patients with confirmed pandemic A(H1N1) 2009 infection were pregnant compared to the 1 prevalence of pregnancy in the general population12 Although a slightly higher proportion of pregnant patients were admitted to ICU or SCU this did not reach statistical significance

We found that morbid obesity and chronic renal disease were associated with increased odds of admission to ICU or SCU Morbid obesity has been associated with increased severity of illness due to pandemic A(H1N1) 2009 infection in previous studies4513ndash15 Similarly chronic renal disease has also been reported as a potential risk factor for severity of illness due to pandemic A(H1N1) 2009 infection1516

Considerably higher rates of hospital admission due to pandemic A(H1N1) 2009 influenza infection have been reported among indigenous people in other Australian states1516 New Zealand and Canada compared to those of European descent1417 This is possibly due to a higher prevalence of medical risk factors poorer access to primary health care services and socioeconomic factors in this community18 However we found that the proportion of hospitalized patients admitted to ICU or SCU was similar among indigenous and non-indigenous Queenslanders Missing data from indigenous status may influence the proportion of hospital admission recorded as indigenous Ten per cent of data on indigenous status was unknown or missing which limited our interpretation of the association between ICUSCU admission and indigenous status

Our final logistic regression model revealed that factors such as older age initiation of antiviral treatment later than 48 hours and presence of morbid obesity andor chronic renal disease were significantly associated with admission to ICUSCU This model had reasonable predictive accuracy for admission to ICU or SCU with the area under the ROC curve being 076 (1 indicating perfect predictive accuracy and 05 no predictive accuracy above chance)19

Our analysis has several limitations Analysis was undertaken using only data on patients with laboratory-confirmed pandemic A(H1N1) 2009 infection This may underestimate the true number of cases as some may not have been tested or have tested negative due

to technical or timing factors The data on underlying medical conditions were from patient self-report and were not clinically validated Body mass index values were not recorded so it is unclear what role clinical judgement may have played in categorization of morbid obesity (or other medical conditions for that matter) There is also the possibility of reporting bias which may results in confounding in our logistic regression model Despite the use of a standardized data collection template not all information was captured for all cases and some data fields were incomplete The study used data from two sources EpiLog for public hospitals and separately submitted spreadsheets for private hospitals It was not possible to verify the data recorded Finally as social-demographic data were collated by linking the EpiLog system and HBCIS missing data were unavoidable

Despite these limitations EpiLog provides an example of a new surveillance application that was rapidly developed to meet an urgent public health need It enabled close to real-time monitoring of the severity of pandemic A(H1N1) 2009 infection and its impact on Queenslandrsquos hospital system and critical care services It was possible to monitor the progress of the pandemic and gain rapid information on risk factors for severe disease and patient outcomes Reflection on the use of EpiLog during the 2009 influenza pandemic led to several enhancements of the application Many of the improvements related to streamlining the interface between EpiLog and HBCIS and the efficient management of data quality and reporting issues

Finally there is growing evidence that early treatment with antiviral medication may reduce the likelihood of hospitalization and death due to pandemic A(H1N1) 2009 infection520 Our study supports these findings Patients admitted to an ICU or SCU or who died were less likely to have received antiviral therapy within 48 hours of the onset of symptoms compared to other hospitalized patients Early antiviral treatment for influenza cases may therefore have important public health implications for example for reducing the severity of the impact of pandemic A(H1N1) 2009 infection


None declared

Funding

None



2009 302 1872ndash1879 doi101001jama20091496 pmid19822627

12 Australian Bureau of Statistics 32010 - population by age and sex Australian states and territories June 2008 (httpwwwabsgovauAUSSTATSabsnsfMF32010 accessed on 21 March 2011)

13 Centers for Disease Control and Prevention Intensive-care patients with severe novel influenza A (H1N1) virus infection Michigan June 2009 MMWR Morbidity and Mortality Weekly Report 2009 58749ndash752

14 Morgan OW et al Morbid obesity as a risk factor for hospitalization and death due to 2009 pandemic influenza A(H1N1) disease PLoS ONE 2010 59694 doi101371journalpone0009694 pmid20300571

15 Australian Government Department of Health and Ageing Australian influenza surveillance summary report no 21 2009 reporting period 26 September 2009ndash2 October 2009 (h t tp wwwhea l themergencygovau in te rne t hea l themergencypublishingnsfContent18D06BAC4644C98DCA25763E00823442$Fileozflu-no21-2009pdf accessed on 21 March 2011)

16 Flint SM et al Disproportionate impact of pandemic (H1N1) 2009 influenza on Indigenous people in the Top End of Australiarsquos Northern territory Medical Journal of Australia 2010 (httpwwwmjacomaupublicissues192_10_170510fli10103_fmhtml accessed 21 March 2011)

17 Baker MG et al Pandemic influenza A(H1N1)v in New Zealand the experience from April to August 2009 Euro Surveillance European Communicable Disease Bulletin 2009 14(34)pii=19319 pmid19712648

18 Australiarsquos health 2008 Catno AUS 99 Canberra Australian Institute of Health and Welfare 2008

19 Harrell FE Jr Lee KL Mark DB Multivariable prognostic models issues in developing models evaluating assumptions and adequacy and measuring and reducing errors Statistics in Medicine 1996 15361ndash387 doi101002(SICI)1097-0258(19960229)154lt361AID-SIM168gt30CO2-4 pmid8668867

20 Jain S et al 2009 Pandemic Influenza A (H1N1) Virus Hospitalizations Investigation Team Hospitalized patients with 2009 H1N1 influenza in the United States April-June 2009 The New England Journal of Medicine 2009 3611935ndash1944 doi101056NEJMoa0906695 pmid19815859

References

1 Appuhamy RD et al The changing phases of pandemic (H1N1) 2009 in Queensland an overview of public health actions and epidemiology The Medical Journal of Australia 2010 19294ndash97 doi101126science3277268 pmid20078411

2 Cao B et al National Influenza A Pandemic (H1N1) 2009 Clinical Investigation Group of China Clinical features of the initial cases of 2009 pandemic influenza A(H1N1) virus infection in China New England Journal of Medicine 2009 3612507ndash2517 doi101056NEJMoa0906612 pmid20007555

3 Louie JK et al California Pandemic (H1N1) Working Group Factors associated with death or hospitalization due to pandemic 2009 influenza A(H1N1) infection in California JAMA The Journal of the American Medical Association 2009 3021896ndash1902 doi101001jama20091583 pmid19887665

4 Fuhrman C et al Severe hospitalised 2009 pandemic influenza A (H1N1) cases in France 1 July-15 November 2009 Euro Surveillance European Communicable Disease Bulletin 2010 15(2)17ndash21 pmid20085690

5 Zarychanski R et al Correlates of severe disease in patients with 2009 pandemic influenza (H1N1) virus infection Canadian Medical Association Journal 2010 182257ndash264 doi101503cmaj091884 pmid20093297

6 Campbell A et al Risk of severe outcomes among patients admitted to hospital with pandemic (H1N1) influenza Canadian Medical Association Journal 2010 182349ndash355 doi101503cmaj091823 pmid20159893

7 Hanley JA McNeil BJ The meaning and use of the area under a receiving operating characteristic (ROC) curve Radiology 1986 5023ndash36

8 Statistical Package for Social Scientist Chicago

9 Jamieson DJ et al Novel Influenza A (H1N1) Pregnancy Working Group H1N1 2009 influenza virus infection during pregnancy in the USA Lancet 2009 374451ndash458 doi101016S0140-6736(09)61304-0 pmid19643469

10 Webb SA et al ANZIC Influenza Investigators Critical care services and 2009 H1N1 influenza in Australia and New Zealand The New England Journal of Medicine 2009 3611925ndash1934 doi101056NEJMoa0908481 pmid19815860

11 Kumar A et al Critically ill patients with 2009 influenza A (H1N1) infection in Canada JAMA The Journal of American Association

wwwwprowhointwpsar36 WPSAR Vol 2 No 2 2011

WPSAR Instructions to authors

Aim of Western Pacifi c Surveillance and ResponseTo create a platform for sharing information to improve surveillance of and response to public health events in the Western Pacific Region

Objectives bull To produce a web-based publication on surveillance and response

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bull To promote information sharing on experiences and lessons learnt in surveillance and response for public health events in the Western Pacific Region and globally

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bull To highlight new and relevant technical or guidance documents and meeting reports published by the World Health Organization Western Pacific Regional Office

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Scope WPSAR covers all activities related to the surveillance of and response to public health events Such activities may be implementation or evaluation of surveillance systems investigations of public health events risk assessments both in rapid responses and policy development outbreak investigations and research on routine public health activities Public health events may be in any of the following areas communicable diseases natural disasters bioterrorism and chemical and radiological events

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Journal articles will be published an article at a time building up to an issue every quarter This means that articles will be uploaded onto the website after the review and editing process therefore allowing timely dissemination Printed copies of the journal are available for areas with limited internet access on request after the end of each quarter

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WPSAR follows the guidelines from the Uniform Requirements for Manuscripts Submitted to Biomedical Journals by the International Committee for Medical Journal Editors (ICMJE httpwwwicmjeorg)

Format for Manuscripts

Please submit all articles in double spaced 12 point Arial font in a Microsoftreg Office Word file or a compatible file in English

The format of the article will depend on the type There are letters to the editor perspectives case reportscase series lessons from the field surveillance reports surveillance system implementationevaluation risk assessments original research news items and meetingconference reports

Letters to the EditorA letter commenting on a previously published article OR a letter commenting on the theme of the issue

bull Word limit le500 words

bull le5 references

bull le1 illustration

PerspectivesAn unstructured article discussing an issue regarding surveillance of and response to public health events The scope of the discussion must be clearly defined


bull le10 references


Case ReportCase SeriesAn unstructured article describing an unusual case or series of cases of public health significance Sub-headings may be used to increase the readability of the article

bull Unstructured abstract of le250 words



bull le3 figuresgraphspictures

Lessons from the Field

An article describing an issue faced in field epidemiology and the experience in trying to overcome the issue

bull Structured article with an abstract of le250 words and sections for problem context action outcome and discussion

bull The abstract should also be structured with problem context action outcome and discussion




Surveillance ReportsAn article of a summary and interpretation of surveillance data for a given period of time A description of the surveillance system and the limitations of the data collected must be included





Surveillance System ImplementationEvaluation An article describing the implementation of a new surveillance system or an evaluation of an existing surveillance system used to detect public health events





Risk AssessmentsAn article detailing a risk assessment of a public health threat or event The risk assessment may be planned and formal or rapid and informal The scope and methods of the risk assessment must be clearly defined

bull Structured article with an abstract of le250 words introduction methods results and discussion

bull The abstract should also be structured with objective methods results and discussion




Western Pacifi c Surveillance and ResponseInstructions to Authors

wwwwprowhointwpsar 37WPSAR Vol 2 No 2 2011


Original Research

Original research articles may include epidemiological studies including outbreak investigations


bull The abstract should also be structured with introduction methods results discussion




News Meeting and Conference ReportsNews items and meeting and conference reports will not undergo peer review Please contact the Editor at WPSARwprowhoint if you intend on submitting such an article

IllustrationsRefer to the article type for the limit on illustrations (graphs tables or diagrams) Please insert all illustrations at the end of the manuscript with a title The illustration must be referred to in the text and must be able to be understood on its own Use Microsoftreg Office Excel for graphs and Microsoftreg Office Word for tables and diagrams Additionally please provide a Microsoftreg Office Excel spreadsheet of the data used to create a graph Footnotes for illustrations should have superscript letters assigned and an explanation provided below the illustration

References

Reference the most recent and relevant publications Please use Vancouver style referencing Sample references can be viewed onlinehttpwwwnlmnihgovbsduniform_requirementshtml

Place the bibliography at the end of the article text and not as footnotes Write journal names in full Use superscript sequential numbering in the text Place the number after any punctuation For example

These results are consistent with the original study11

Reference personal communication in the text only and include the personrsquos full name and institution

Peer Review Process

Every article will be reviewed firstly by the editorial team to ensure the article is within the scope of WPSAR and the quality is sufficient for undergoing peer review All articles with the exception of news items and meeting and conference reports will undergo external peer review by two reviewers This will be a blinded peer review process where the reviewer does not know the identity of the author(s) and the author(s) do not know the identity of the reviewer Author(s) may be asked to revise the manuscript as a result of the peer review After satisfactory revision accepted manuscripts will be edited and sent to the author(s) for final approval before publication

Authorship

All authors should have contributed significantly to the article through one or more of the following in each category A B and C

Abull Study design

bull Data collection

bull Data analysis

bull Data interpretation

bull Writing the article

Bbull Drafting the manuscript

bull Critically revising the manuscript

Cbull Final approval of the manuscript for submission

Any other contributors may be listed in the Acknowledgements section

AcknowledgementsContributors who do not fulfil the requirements to be an author may be acknowledged Permission from all contributors in the acknowledgement section should be given

Ethics and PermissionsIt is the responsibility of authors to gain appropriate ethics approval for their work A statement of ethics approval obtained or permission to publish sensitive material is required for all articles during the submission process

Licence

A licence will be obtained from authors granting exclusive use of the article for publication to the World Health Organization for all accepted articles


A conflict of interest is defined by the ICMJE as lsquowhen an author or authorrsquos institution reviewer or editor has financial or personal relationships that inappropriately influence (bias) his or her actionsrsquo Conflicts of interest may be financial institutional research or personal A relationship does not always represent a conflict of interest and does not necessarily preclude publication in WPSAR All authors and reviewers will be required to state any potential conflicts of interest at the end of the article

FundingAuthors will be required to state the sources of funding for their work after the statement of conflicts of interest

PhotographsIf authors have taken digital photographs that are relevant to their article they may be submitted for consideration for publication on the cover of the issue Submission of a photograph does not guarantee its publication

LanguageManuscripts should be written in English Authors who require assistance with preparing their manuscripts in English should contact WPSAR at WPSARwprowhoint

Article submissionSubmit articles to the Editor through the WPSAR website (wwwwprowhointwpsar) When submitting the article you will be requested to provide the following

bull A cover letter describing the article and why it should be published

bull A title page with the article title short title brief description of the article of le 50 words le 7 keywords full names of all authors and institutions and full contact details of the corresponding author This must be a separate file to the article to ensure a blind review

bull A Microsoftreg Office Word file of the article

bull Scanned copy of the licence for publication provided during the submission process signed by all authors

Corrections

If authors of a published article become aware of any errors with the article they should contact the Editor at WPSARwprowhoint Corrections will be published online

wpsarwprowhoint l wwwwprowhointwpsar

wwwwprowhointwpsarWPSAR Vol 2 No 2 2011 | Dengue Lessons Challenges and New Approaches

EDITORIAL TEAM

Takeshi KasaiExecutive Editor

Emma FieldCoordinating Editor

Elizabeth MangaliAssistant Editor

Associate Editors

Jorge Mendoza AldanaJenny Bishop

Nobuyuki NishikioriJeffrey PartridgeArturo Pesigan

Manju RaniDongbao Yu

Western Pacific Surveillance and Response (WPSAR) is a publication managed by the World Health Organization Regional Office for the Western Pacific

To contact us

Western Pacific Surveillance and ResponseWorld Health Organization Office for the Western Pacific RegionUnited Nations Avenue1000 Manila Philippineswpsarwprowhointwwwwprowhointwpsar

Copyright noticecopy World Health Organization 2010

p-ISSN 2094-7321e-ISSN 2094-7313

All rights reserved The information presented in the various pages of this journal is issued by the World Health Organization for general distribution and is protected under the Berne Convention for the Protection of Literature and Artistic Works under national laws on copyright and neighbouring rights

The World Health Organization does not warrant that the information contained in this publication is complete and correct and shall not be liable for any damages incurred as a result of its use

Publications of the World Health Organization can be obtained from Marketing and Dissemination World Health Organization 20 Avenue Appia 1211 Geneva 27 Switzerland (tel +41 22 791 3264 fax +41 22 791 4857 email bookorderswhoint) Requests for permission to reproduce WHO publications in part or in whole or to translate them ndash whether for sale or for non-commercial distribution ndash should be addressed to Publications at the above address (+41 22 791 4806 e-mail permissionswhoint) For WHO Western Pacific Regional Publications request for permission to reproduce should be addressed to Publications Office World Health Organization Regional Office for the Western Pacific PO Box 2932 1000 Manila Philippines fax +632 521 1036 e-mail publicationswprowhoint

Disclaimer

The designations employed and the presentation of the information in this publication do not imply the expression of any opinion whatsoever on the part of the World Health Organization concerning the legal status of any country territory city or area or of its authorities or concerning the delimitation of its frontiers or boundaries

The mention of specific companies or of certain manufacturers products does not imply that they are endorsed or recommended by the World Health Organization in preference to others of a similar nature that are not mentioned Errors and omissions excepted the names of proprietary products are distinguished by initial capital letters













STRATEGY


Editorial










Reference

































Regional Analysis







METHODS





RESULTS




Asia Subregion

Cambodia




Malaysia




400

350

300

250

200

150

100

50

0

140

120

100

080

060

040

020

000

1991

1992

1993

1194

1195

1196

1197

1198

1199

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

CFR

all c

ases

()

Num

ber o

f cas

es (x

100

0)

Year







No of deaths





TOTAL 353 907 1952 1 073 030 1 812 863



Country

2006 2007 2008 2009 2010

No of cases

No of deaths

CFR ()

No of cases

No of deaths

CFR ()

No of cases

No of deaths

CFR ()

No of cases

No of deaths

CFR ()

No of cases

No of deaths

CFR ()

Cambodia 16 669 158 095 39 851 407 102 9 542 65 068 11 699 38 032 12 500 38 030


6 356 6 009 4 943 4 008 4 149 21 051 7 214 12 017 22 929 46 020

Malaysia 38 556 89 023 48 846 98 020 49 335 112 023 41 486 88 021 46 171 134 029

Philippines 37 101 378 102 55 639 533 096 39 620 373 094 57 819 548 095 135 355 793 059

Singapore 3 127 10 032 8 826 24 027 7 032 10 014 4 497 8 018 5 364 4 007

Viet Nam 68 532 53 008 104 393 88 008 96 451 97 010 105 370 87 008 128 831 55 004

Australia 189 0 000 316 0 0 563 0 0 1 401 0 0 1 171 0 0

Total 170 530 694 041 262 814 1 154 044 206 692 678 033 229 486 781 034 352 321 1 070 030





The Philippines


Singapore


Viet Nam


Pacifi c subregion

Australia


DISCUSSION












None declared

Funding


Acknowledgements


References



















Regional Analysis

BACKGROUND



























Cambodia






monitoring




Hong Kong (China)








Not regular

Malaysia






Routine






Singapore





Routine





Not regular









CountryareasSpace

spraying (outbreak)


Biological control


(source reduction)




collaboration





based) - +

China + - - + + - +




research)+ ++ - +

Fiji + + - + + - -

Malaysia + + - + + ++ +


research)+ + - +


Singapore + + - + + ++ ++

Vanuatu + + - + + - +




































FUTURE PERSPECTIVE











CONCLUSIONS



None declared

Funding


References





































Regional Analysis









METHODS








RESULTS








The Philippines






2003 1 052 520 3 876 530 4 491 464 8 224 6352004 200 550 502 560 1 278 518 1 434 462 2005 551 488 1 051 481 1 847 520 2 022 485 2006 712 531 1 133 539 1 777 519 2 846 506 Total 3 342 513 8 326 541 13 486 498 22 360 579


1999 242 574 1 785 508 5 021 509 2 358 5892001 607 521 3 814 507 13 399 504 7 132 5842002 361 535 3 055 505 8 645 506 4 428 5822003 650 534 4 866 509 15 749 505 8 260 5622004 561 504 3 583 497 12 426 499 6 470 5842005 806 553 4 915 510 17 202 505 10 472 578Total 4 200 545 28 469 507 92 260 503 47 526 572


2000 5 400 17 529 96 583 555 6632001 5 800 27 667 243 580 2 097 6192002 12 333 23 652 429 632 3 481 6482003 22 591 30 567 532 560 4 204 5872004 22 818 87 529 1 223 597 8 127 6182005 32 500 160 569 2 126 541 11 891 583Total 104 587 360 572 4 778 570 31 559 607


1997 11 364 142 458 341 487 285 6951998 24 542 218 514 479 501 249 6671999 27 593 219 447 469 557 417 6382000 45 511 320 500 856 481 1 134 6162001 28 607 248 460 687 476 1 590 6182002 38 579 209 459 665 448 2 011 5912003 16 375 106 585 356 478 1 119 6362004 33 606 236 475 878 495 2 623 6182005 28 500 115 496 235 502 654 627Total 256 539 2 004 481 5 472 484 10 480 618











male cases all ages



Philippinesb


Sri Lankabc






Singapore


Sri Lanka




Malaysia


Cambodia


DISCUSSION




1997 19 429 5441998 27 381 5561999 10 146 5962000 7 103 5922001 16 368 5622002 32 767 5472003 31 545 5612004 33 895 6142005 39 686 5812006 38 556 5812007 48 846 5932008 49 335 615

















None declared

Funding


Acknowledgements


References





























Original Research






METHODS






Notifi cation


Vector control




Data analysis







Ethics


RESULTS











Age group (years)

2005 2007



Total 14 032 (1000) 3289 8 287 (1000) 1806


3000

2500

2000

1500

1000

500


Months

Num

ber o

f cas

es 2007 2005












DISCUSSION





Year 2005 Year 2007









0

10

20

30

40

50

60

70

80

90

100Ja

n-05 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec

Jan-

06 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec

Jan-

07 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec


Month-Year

Dist

ribut

ion

of s

erot

ype







None declared

Funding

None

References




























Original Research





















RESULTS












Frequency ()




SexMale 568 (459)Female 669 (541)





Yes 561 (667)No 281 (333)










Pregnantdagger

Yes 61 17 213 11 (04ndash26)No 442 85 127 1










DISCUSSION







OR (95 CI)

Age (years)


10ndash17 1



65+ 57 (18ndash182)


Yesdagger 1

No 21 (134ndash33)


Nodagger 1

Yes 27 (13ndash57)

Morbid obesity

Nodagger 1

Yes 19 (14ndash36)



10

08

06

04

02

0000 02 04 06 08 10


Sens

itivi

ty

ROC Curve












None declared

Funding

None













References






















Frequency









bull le5 references





































Original Research









References





Peer Review Process


Authorship


Abull Study design


bull Data analysis









Licence












Corrections















STRATEGY


Editorial










Reference

































Regional Analysis







METHODS





RESULTS




Asia Subregion

Cambodia




Malaysia




400

350

300

250

200

150

100

50

0

140

120

100

080

060

040

020

000

1991

1992

1993

1194

1195

1196

1197

1198

1199

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

CFR

all c

ases

()

Num

ber o

f cas

es (x

100

0)

Year







No of deaths





TOTAL 353 907 1952 1 073 030 1 812 863



Country

2006 2007 2008 2009 2010

No of cases

No of deaths

CFR ()

No of cases

No of deaths

CFR ()

No of cases

No of deaths

CFR ()

No of cases

No of deaths

CFR ()

No of cases

No of deaths

CFR ()

Cambodia 16 669 158 095 39 851 407 102 9 542 65 068 11 699 38 032 12 500 38 030


6 356 6 009 4 943 4 008 4 149 21 051 7 214 12 017 22 929 46 020

Malaysia 38 556 89 023 48 846 98 020 49 335 112 023 41 486 88 021 46 171 134 029

Philippines 37 101 378 102 55 639 533 096 39 620 373 094 57 819 548 095 135 355 793 059

Singapore 3 127 10 032 8 826 24 027 7 032 10 014 4 497 8 018 5 364 4 007

Viet Nam 68 532 53 008 104 393 88 008 96 451 97 010 105 370 87 008 128 831 55 004

Australia 189 0 000 316 0 0 563 0 0 1 401 0 0 1 171 0 0

Total 170 530 694 041 262 814 1 154 044 206 692 678 033 229 486 781 034 352 321 1 070 030





The Philippines


Singapore


Viet Nam


Pacifi c subregion

Australia


DISCUSSION












None declared

Funding


Acknowledgements


References



















Regional Analysis

BACKGROUND



























Cambodia






monitoring




Hong Kong (China)








Not regular

Malaysia






Routine






Singapore





Routine





Not regular









CountryareasSpace

spraying (outbreak)


Biological control


(source reduction)




collaboration





based) - +

China + - - + + - +




research)+ ++ - +

Fiji + + - + + - -

Malaysia + + - + + ++ +


research)+ + - +


Singapore + + - + + ++ ++

Vanuatu + + - + + - +




































FUTURE PERSPECTIVE











CONCLUSIONS



None declared

Funding


References





































Regional Analysis









METHODS








RESULTS








The Philippines






2003 1 052 520 3 876 530 4 491 464 8 224 6352004 200 550 502 560 1 278 518 1 434 462 2005 551 488 1 051 481 1 847 520 2 022 485 2006 712 531 1 133 539 1 777 519 2 846 506 Total 3 342 513 8 326 541 13 486 498 22 360 579


1999 242 574 1 785 508 5 021 509 2 358 5892001 607 521 3 814 507 13 399 504 7 132 5842002 361 535 3 055 505 8 645 506 4 428 5822003 650 534 4 866 509 15 749 505 8 260 5622004 561 504 3 583 497 12 426 499 6 470 5842005 806 553 4 915 510 17 202 505 10 472 578Total 4 200 545 28 469 507 92 260 503 47 526 572


2000 5 400 17 529 96 583 555 6632001 5 800 27 667 243 580 2 097 6192002 12 333 23 652 429 632 3 481 6482003 22 591 30 567 532 560 4 204 5872004 22 818 87 529 1 223 597 8 127 6182005 32 500 160 569 2 126 541 11 891 583Total 104 587 360 572 4 778 570 31 559 607


1997 11 364 142 458 341 487 285 6951998 24 542 218 514 479 501 249 6671999 27 593 219 447 469 557 417 6382000 45 511 320 500 856 481 1 134 6162001 28 607 248 460 687 476 1 590 6182002 38 579 209 459 665 448 2 011 5912003 16 375 106 585 356 478 1 119 6362004 33 606 236 475 878 495 2 623 6182005 28 500 115 496 235 502 654 627Total 256 539 2 004 481 5 472 484 10 480 618











male cases all ages



Philippinesb


Sri Lankabc






Singapore


Sri Lanka




Malaysia


Cambodia


DISCUSSION




1997 19 429 5441998 27 381 5561999 10 146 5962000 7 103 5922001 16 368 5622002 32 767 5472003 31 545 5612004 33 895 6142005 39 686 5812006 38 556 5812007 48 846 5932008 49 335 615

















None declared

Funding


Acknowledgements


References





























Original Research






METHODS






Notifi cation


Vector control




Data analysis







Ethics


RESULTS











Age group (years)

2005 2007



Total 14 032 (1000) 3289 8 287 (1000) 1806


3000

2500

2000

1500

1000

500


Months

Num

ber o

f cas

es 2007 2005












DISCUSSION





Year 2005 Year 2007









0

10

20

30

40

50

60

70

80

90

100Ja

n-05 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec

Jan-

06 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec

Jan-

07 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec


Month-Year

Dist

ribut

ion

of s

erot

ype







None declared

Funding

None

References




























Original Research





















RESULTS












Frequency ()




SexMale 568 (459)Female 669 (541)





Yes 561 (667)No 281 (333)










Pregnantdagger

Yes 61 17 213 11 (04ndash26)No 442 85 127 1










DISCUSSION







OR (95 CI)

Age (years)


10ndash17 1



65+ 57 (18ndash182)


Yesdagger 1

No 21 (134ndash33)


Nodagger 1

Yes 27 (13ndash57)

Morbid obesity

Nodagger 1

Yes 19 (14ndash36)



10

08

06

04

02

0000 02 04 06 08 10


Sens

itivi

ty

ROC Curve












None declared

Funding

None













References






















Frequency









bull le5 references





































Original Research









References





Peer Review Process


Authorship


Abull Study design


bull Data analysis









Licence












Corrections












Reference

































Regional Analysis







METHODS





RESULTS




Asia Subregion

Cambodia




Malaysia




400

350

300

250

200

150

100

50

0

140

120

100

080

060

040

020

000

1991

1992

1993

1194

1195

1196

1197

1198

1199

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

CFR

all c

ases

()

Num

ber o

f cas

es (x

100

0)

Year







No of deaths





TOTAL 353 907 1952 1 073 030 1 812 863



Country

2006 2007 2008 2009 2010

No of cases

No of deaths

CFR ()

No of cases

No of deaths

CFR ()

No of cases

No of deaths

CFR ()

No of cases

No of deaths

CFR ()

No of cases

No of deaths

CFR ()

Cambodia 16 669 158 095 39 851 407 102 9 542 65 068 11 699 38 032 12 500 38 030


6 356 6 009 4 943 4 008 4 149 21 051 7 214 12 017 22 929 46 020

Malaysia 38 556 89 023 48 846 98 020 49 335 112 023 41 486 88 021 46 171 134 029

Philippines 37 101 378 102 55 639 533 096 39 620 373 094 57 819 548 095 135 355 793 059

Singapore 3 127 10 032 8 826 24 027 7 032 10 014 4 497 8 018 5 364 4 007

Viet Nam 68 532 53 008 104 393 88 008 96 451 97 010 105 370 87 008 128 831 55 004

Australia 189 0 000 316 0 0 563 0 0 1 401 0 0 1 171 0 0

Total 170 530 694 041 262 814 1 154 044 206 692 678 033 229 486 781 034 352 321 1 070 030





The Philippines


Singapore


Viet Nam


Pacifi c subregion

Australia


DISCUSSION












None declared

Funding


Acknowledgements


References



















Regional Analysis

BACKGROUND



























Cambodia






monitoring




Hong Kong (China)








Not regular

Malaysia






Routine






Singapore





Routine





Not regular









CountryareasSpace

spraying (outbreak)


Biological control


(source reduction)




collaboration





based) - +

China + - - + + - +




research)+ ++ - +

Fiji + + - + + - -

Malaysia + + - + + ++ +


research)+ + - +


Singapore + + - + + ++ ++

Vanuatu + + - + + - +




































FUTURE PERSPECTIVE











CONCLUSIONS



None declared

Funding


References





































Regional Analysis









METHODS








RESULTS








The Philippines






2003 1 052 520 3 876 530 4 491 464 8 224 6352004 200 550 502 560 1 278 518 1 434 462 2005 551 488 1 051 481 1 847 520 2 022 485 2006 712 531 1 133 539 1 777 519 2 846 506 Total 3 342 513 8 326 541 13 486 498 22 360 579


1999 242 574 1 785 508 5 021 509 2 358 5892001 607 521 3 814 507 13 399 504 7 132 5842002 361 535 3 055 505 8 645 506 4 428 5822003 650 534 4 866 509 15 749 505 8 260 5622004 561 504 3 583 497 12 426 499 6 470 5842005 806 553 4 915 510 17 202 505 10 472 578Total 4 200 545 28 469 507 92 260 503 47 526 572


2000 5 400 17 529 96 583 555 6632001 5 800 27 667 243 580 2 097 6192002 12 333 23 652 429 632 3 481 6482003 22 591 30 567 532 560 4 204 5872004 22 818 87 529 1 223 597 8 127 6182005 32 500 160 569 2 126 541 11 891 583Total 104 587 360 572 4 778 570 31 559 607


1997 11 364 142 458 341 487 285 6951998 24 542 218 514 479 501 249 6671999 27 593 219 447 469 557 417 6382000 45 511 320 500 856 481 1 134 6162001 28 607 248 460 687 476 1 590 6182002 38 579 209 459 665 448 2 011 5912003 16 375 106 585 356 478 1 119 6362004 33 606 236 475 878 495 2 623 6182005 28 500 115 496 235 502 654 627Total 256 539 2 004 481 5 472 484 10 480 618











male cases all ages



Philippinesb


Sri Lankabc






Singapore


Sri Lanka




Malaysia


Cambodia


DISCUSSION




1997 19 429 5441998 27 381 5561999 10 146 5962000 7 103 5922001 16 368 5622002 32 767 5472003 31 545 5612004 33 895 6142005 39 686 5812006 38 556 5812007 48 846 5932008 49 335 615

















None declared

Funding


Acknowledgements


References





























Original Research






METHODS






Notifi cation


Vector control




Data analysis







Ethics


RESULTS











Age group (years)

2005 2007



Total 14 032 (1000) 3289 8 287 (1000) 1806


3000

2500

2000

1500

1000

500


Months

Num

ber o

f cas

es 2007 2005












DISCUSSION





Year 2005 Year 2007









0

10

20

30

40

50

60

70

80

90

100Ja

n-05 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec

Jan-

06 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec

Jan-

07 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec


Month-Year

Dist

ribut

ion

of s

erot

ype







None declared

Funding

None

References




























Original Research





















RESULTS












Frequency ()




SexMale 568 (459)Female 669 (541)





Yes 561 (667)No 281 (333)










Pregnantdagger

Yes 61 17 213 11 (04ndash26)No 442 85 127 1










DISCUSSION







OR (95 CI)

Age (years)


10ndash17 1



65+ 57 (18ndash182)


Yesdagger 1

No 21 (134ndash33)


Nodagger 1

Yes 27 (13ndash57)

Morbid obesity

Nodagger 1

Yes 19 (14ndash36)



10

08

06

04

02

0000 02 04 06 08 10


Sens

itivi

ty

ROC Curve












None declared

Funding

None













References






















Frequency









bull le5 references





































Original Research









References





Peer Review Process


Authorship


Abull Study design


bull Data analysis









Licence












Corrections































Regional Analysis







METHODS





RESULTS




Asia Subregion

Cambodia




Malaysia




400

350

300

250

200

150

100

50

0

140

120

100

080

060

040

020

000

1991

1992

1993

1194

1195

1196

1197

1198

1199

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

CFR

all c

ases

()

Num

ber o

f cas

es (x

100

0)

Year







No of deaths





TOTAL 353 907 1952 1 073 030 1 812 863



Country

2006 2007 2008 2009 2010

No of cases

No of deaths

CFR ()

No of cases

No of deaths

CFR ()

No of cases

No of deaths

CFR ()

No of cases

No of deaths

CFR ()

No of cases

No of deaths

CFR ()

Cambodia 16 669 158 095 39 851 407 102 9 542 65 068 11 699 38 032 12 500 38 030


6 356 6 009 4 943 4 008 4 149 21 051 7 214 12 017 22 929 46 020

Malaysia 38 556 89 023 48 846 98 020 49 335 112 023 41 486 88 021 46 171 134 029

Philippines 37 101 378 102 55 639 533 096 39 620 373 094 57 819 548 095 135 355 793 059

Singapore 3 127 10 032 8 826 24 027 7 032 10 014 4 497 8 018 5 364 4 007

Viet Nam 68 532 53 008 104 393 88 008 96 451 97 010 105 370 87 008 128 831 55 004

Australia 189 0 000 316 0 0 563 0 0 1 401 0 0 1 171 0 0

Total 170 530 694 041 262 814 1 154 044 206 692 678 033 229 486 781 034 352 321 1 070 030





The Philippines


Singapore


Viet Nam


Pacifi c subregion

Australia


DISCUSSION












None declared

Funding


Acknowledgements


References



















Regional Analysis

BACKGROUND



























Cambodia






monitoring




Hong Kong (China)








Not regular

Malaysia






Routine






Singapore





Routine





Not regular









CountryareasSpace

spraying (outbreak)


Biological control


(source reduction)




collaboration





based) - +

China + - - + + - +




research)+ ++ - +

Fiji + + - + + - -

Malaysia + + - + + ++ +


research)+ + - +


Singapore + + - + + ++ ++

Vanuatu + + - + + - +




































FUTURE PERSPECTIVE











CONCLUSIONS



None declared

Funding


References





































Regional Analysis









METHODS








RESULTS








The Philippines






2003 1 052 520 3 876 530 4 491 464 8 224 6352004 200 550 502 560 1 278 518 1 434 462 2005 551 488 1 051 481 1 847 520 2 022 485 2006 712 531 1 133 539 1 777 519 2 846 506 Total 3 342 513 8 326 541 13 486 498 22 360 579


1999 242 574 1 785 508 5 021 509 2 358 5892001 607 521 3 814 507 13 399 504 7 132 5842002 361 535 3 055 505 8 645 506 4 428 5822003 650 534 4 866 509 15 749 505 8 260 5622004 561 504 3 583 497 12 426 499 6 470 5842005 806 553 4 915 510 17 202 505 10 472 578Total 4 200 545 28 469 507 92 260 503 47 526 572


2000 5 400 17 529 96 583 555 6632001 5 800 27 667 243 580 2 097 6192002 12 333 23 652 429 632 3 481 6482003 22 591 30 567 532 560 4 204 5872004 22 818 87 529 1 223 597 8 127 6182005 32 500 160 569 2 126 541 11 891 583Total 104 587 360 572 4 778 570 31 559 607


1997 11 364 142 458 341 487 285 6951998 24 542 218 514 479 501 249 6671999 27 593 219 447 469 557 417 6382000 45 511 320 500 856 481 1 134 6162001 28 607 248 460 687 476 1 590 6182002 38 579 209 459 665 448 2 011 5912003 16 375 106 585 356 478 1 119 6362004 33 606 236 475 878 495 2 623 6182005 28 500 115 496 235 502 654 627Total 256 539 2 004 481 5 472 484 10 480 618











male cases all ages



Philippinesb


Sri Lankabc






Singapore


Sri Lanka




Malaysia


Cambodia


DISCUSSION




1997 19 429 5441998 27 381 5561999 10 146 5962000 7 103 5922001 16 368 5622002 32 767 5472003 31 545 5612004 33 895 6142005 39 686 5812006 38 556 5812007 48 846 5932008 49 335 615

















None declared

Funding


Acknowledgements


References





























Original Research






METHODS






Notifi cation


Vector control




Data analysis







Ethics


RESULTS











Age group (years)

2005 2007



Total 14 032 (1000) 3289 8 287 (1000) 1806


3000

2500

2000

1500

1000

500


Months

Num

ber o

f cas

es 2007 2005












DISCUSSION





Year 2005 Year 2007









0

10

20

30

40

50

60

70

80

90

100Ja

n-05 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec

Jan-

06 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec

Jan-

07 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec


Month-Year

Dist

ribut

ion

of s

erot

ype







None declared

Funding

None

References




























Original Research





















RESULTS












Frequency ()




SexMale 568 (459)Female 669 (541)





Yes 561 (667)No 281 (333)










Pregnantdagger

Yes 61 17 213 11 (04ndash26)No 442 85 127 1










DISCUSSION







OR (95 CI)

Age (years)


10ndash17 1



65+ 57 (18ndash182)


Yesdagger 1

No 21 (134ndash33)


Nodagger 1

Yes 27 (13ndash57)

Morbid obesity

Nodagger 1

Yes 19 (14ndash36)



10

08

06

04

02

0000 02 04 06 08 10


Sens

itivi

ty

ROC Curve












None declared

Funding

None













References






















Frequency









bull le5 references





































Original Research









References





Peer Review Process


Authorship


Abull Study design


bull Data analysis









Licence












Corrections







Regional Analysis







METHODS





RESULTS




Asia Subregion

Cambodia




Malaysia




400

350

300

250

200

150

100

50

0

140

120

100

080

060

040

020

000

1991

1992

1993

1194

1195

1196

1197

1198

1199

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

CFR

all c

ases

()

Num

ber o

f cas

es (x

100

0)

Year







No of deaths





TOTAL 353 907 1952 1 073 030 1 812 863



Country

2006 2007 2008 2009 2010

No of cases

No of deaths

CFR ()

No of cases

No of deaths

CFR ()

No of cases

No of deaths

CFR ()

No of cases

No of deaths

CFR ()

No of cases

No of deaths

CFR ()

Cambodia 16 669 158 095 39 851 407 102 9 542 65 068 11 699 38 032 12 500 38 030


6 356 6 009 4 943 4 008 4 149 21 051 7 214 12 017 22 929 46 020

Malaysia 38 556 89 023 48 846 98 020 49 335 112 023 41 486 88 021 46 171 134 029

Philippines 37 101 378 102 55 639 533 096 39 620 373 094 57 819 548 095 135 355 793 059

Singapore 3 127 10 032 8 826 24 027 7 032 10 014 4 497 8 018 5 364 4 007

Viet Nam 68 532 53 008 104 393 88 008 96 451 97 010 105 370 87 008 128 831 55 004

Australia 189 0 000 316 0 0 563 0 0 1 401 0 0 1 171 0 0

Total 170 530 694 041 262 814 1 154 044 206 692 678 033 229 486 781 034 352 321 1 070 030





The Philippines


Singapore


Viet Nam


Pacifi c subregion

Australia


DISCUSSION












None declared

Funding


Acknowledgements


References



















Regional Analysis

BACKGROUND



























Cambodia






monitoring




Hong Kong (China)








Not regular

Malaysia






Routine






Singapore





Routine





Not regular









CountryareasSpace

spraying (outbreak)


Biological control


(source reduction)




collaboration





based) - +

China + - - + + - +




research)+ ++ - +

Fiji + + - + + - -

Malaysia + + - + + ++ +


research)+ + - +


Singapore + + - + + ++ ++

Vanuatu + + - + + - +




































FUTURE PERSPECTIVE











CONCLUSIONS



None declared

Funding


References





































Regional Analysis









METHODS








RESULTS








The Philippines






2003 1 052 520 3 876 530 4 491 464 8 224 6352004 200 550 502 560 1 278 518 1 434 462 2005 551 488 1 051 481 1 847 520 2 022 485 2006 712 531 1 133 539 1 777 519 2 846 506 Total 3 342 513 8 326 541 13 486 498 22 360 579


1999 242 574 1 785 508 5 021 509 2 358 5892001 607 521 3 814 507 13 399 504 7 132 5842002 361 535 3 055 505 8 645 506 4 428 5822003 650 534 4 866 509 15 749 505 8 260 5622004 561 504 3 583 497 12 426 499 6 470 5842005 806 553 4 915 510 17 202 505 10 472 578Total 4 200 545 28 469 507 92 260 503 47 526 572


2000 5 400 17 529 96 583 555 6632001 5 800 27 667 243 580 2 097 6192002 12 333 23 652 429 632 3 481 6482003 22 591 30 567 532 560 4 204 5872004 22 818 87 529 1 223 597 8 127 6182005 32 500 160 569 2 126 541 11 891 583Total 104 587 360 572 4 778 570 31 559 607


1997 11 364 142 458 341 487 285 6951998 24 542 218 514 479 501 249 6671999 27 593 219 447 469 557 417 6382000 45 511 320 500 856 481 1 134 6162001 28 607 248 460 687 476 1 590 6182002 38 579 209 459 665 448 2 011 5912003 16 375 106 585 356 478 1 119 6362004 33 606 236 475 878 495 2 623 6182005 28 500 115 496 235 502 654 627Total 256 539 2 004 481 5 472 484 10 480 618











male cases all ages



Philippinesb


Sri Lankabc






Singapore


Sri Lanka




Malaysia


Cambodia


DISCUSSION




1997 19 429 5441998 27 381 5561999 10 146 5962000 7 103 5922001 16 368 5622002 32 767 5472003 31 545 5612004 33 895 6142005 39 686 5812006 38 556 5812007 48 846 5932008 49 335 615

















None declared

Funding


Acknowledgements


References





























Original Research






METHODS






Notifi cation


Vector control




Data analysis







Ethics


RESULTS











Age group (years)

2005 2007



Total 14 032 (1000) 3289 8 287 (1000) 1806


3000

2500

2000

1500

1000

500


Months

Num

ber o

f cas

es 2007 2005












DISCUSSION





Year 2005 Year 2007









0

10

20

30

40

50

60

70

80

90

100Ja

n-05 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec

Jan-

06 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec

Jan-

07 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec


Month-Year

Dist

ribut

ion

of s

erot

ype







None declared

Funding

None

References




























Original Research





















RESULTS












Frequency ()




SexMale 568 (459)Female 669 (541)





Yes 561 (667)No 281 (333)










Pregnantdagger

Yes 61 17 213 11 (04ndash26)No 442 85 127 1










DISCUSSION







OR (95 CI)

Age (years)


10ndash17 1



65+ 57 (18ndash182)


Yesdagger 1

No 21 (134ndash33)


Nodagger 1

Yes 27 (13ndash57)

Morbid obesity

Nodagger 1

Yes 19 (14ndash36)



10

08

06

04

02

0000 02 04 06 08 10


Sens

itivi

ty

ROC Curve












None declared

Funding

None













References






















Frequency









bull le5 references





































Original Research









References





Peer Review Process


Authorship


Abull Study design


bull Data analysis









Licence












Corrections






RESULTS




Asia Subregion

Cambodia




Malaysia




400

350

300

250

200

150

100

50

0

140

120

100

080

060

040

020

000

1991

1992

1993

1194

1195

1196

1197

1198

1199

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

CFR

all c

ases

()

Num

ber o

f cas

es (x

100

0)

Year







No of deaths





TOTAL 353 907 1952 1 073 030 1 812 863



Country

2006 2007 2008 2009 2010

No of cases

No of deaths

CFR ()

No of cases

No of deaths

CFR ()

No of cases

No of deaths

CFR ()

No of cases

No of deaths

CFR ()

No of cases

No of deaths

CFR ()

Cambodia 16 669 158 095 39 851 407 102 9 542 65 068 11 699 38 032 12 500 38 030


6 356 6 009 4 943 4 008 4 149 21 051 7 214 12 017 22 929 46 020

Malaysia 38 556 89 023 48 846 98 020 49 335 112 023 41 486 88 021 46 171 134 029

Philippines 37 101 378 102 55 639 533 096 39 620 373 094 57 819 548 095 135 355 793 059

Singapore 3 127 10 032 8 826 24 027 7 032 10 014 4 497 8 018 5 364 4 007

Viet Nam 68 532 53 008 104 393 88 008 96 451 97 010 105 370 87 008 128 831 55 004

Australia 189 0 000 316 0 0 563 0 0 1 401 0 0 1 171 0 0

Total 170 530 694 041 262 814 1 154 044 206 692 678 033 229 486 781 034 352 321 1 070 030





The Philippines


Singapore


Viet Nam


Pacifi c subregion

Australia


DISCUSSION












None declared

Funding


Acknowledgements


References



















Regional Analysis

BACKGROUND



























Cambodia






monitoring




Hong Kong (China)








Not regular

Malaysia






Routine






Singapore





Routine





Not regular









CountryareasSpace

spraying (outbreak)


Biological control


(source reduction)




collaboration





based) - +

China + - - + + - +




research)+ ++ - +

Fiji + + - + + - -

Malaysia + + - + + ++ +


research)+ + - +


Singapore + + - + + ++ ++

Vanuatu + + - + + - +




































FUTURE PERSPECTIVE











CONCLUSIONS



None declared

Funding


References





































Regional Analysis









METHODS








RESULTS








The Philippines






2003 1 052 520 3 876 530 4 491 464 8 224 6352004 200 550 502 560 1 278 518 1 434 462 2005 551 488 1 051 481 1 847 520 2 022 485 2006 712 531 1 133 539 1 777 519 2 846 506 Total 3 342 513 8 326 541 13 486 498 22 360 579


1999 242 574 1 785 508 5 021 509 2 358 5892001 607 521 3 814 507 13 399 504 7 132 5842002 361 535 3 055 505 8 645 506 4 428 5822003 650 534 4 866 509 15 749 505 8 260 5622004 561 504 3 583 497 12 426 499 6 470 5842005 806 553 4 915 510 17 202 505 10 472 578Total 4 200 545 28 469 507 92 260 503 47 526 572


2000 5 400 17 529 96 583 555 6632001 5 800 27 667 243 580 2 097 6192002 12 333 23 652 429 632 3 481 6482003 22 591 30 567 532 560 4 204 5872004 22 818 87 529 1 223 597 8 127 6182005 32 500 160 569 2 126 541 11 891 583Total 104 587 360 572 4 778 570 31 559 607


1997 11 364 142 458 341 487 285 6951998 24 542 218 514 479 501 249 6671999 27 593 219 447 469 557 417 6382000 45 511 320 500 856 481 1 134 6162001 28 607 248 460 687 476 1 590 6182002 38 579 209 459 665 448 2 011 5912003 16 375 106 585 356 478 1 119 6362004 33 606 236 475 878 495 2 623 6182005 28 500 115 496 235 502 654 627Total 256 539 2 004 481 5 472 484 10 480 618











male cases all ages



Philippinesb


Sri Lankabc






Singapore


Sri Lanka




Malaysia


Cambodia


DISCUSSION




1997 19 429 5441998 27 381 5561999 10 146 5962000 7 103 5922001 16 368 5622002 32 767 5472003 31 545 5612004 33 895 6142005 39 686 5812006 38 556 5812007 48 846 5932008 49 335 615

















None declared

Funding


Acknowledgements


References





























Original Research






METHODS






Notifi cation


Vector control




Data analysis







Ethics


RESULTS











Age group (years)

2005 2007



Total 14 032 (1000) 3289 8 287 (1000) 1806


3000

2500

2000

1500

1000

500


Months

Num

ber o

f cas

es 2007 2005












DISCUSSION





Year 2005 Year 2007









0

10

20

30

40

50

60

70

80

90

100Ja

n-05 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec

Jan-

06 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec

Jan-

07 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec


Month-Year

Dist

ribut

ion

of s

erot

ype







None declared

Funding

None

References




























Original Research





















RESULTS












Frequency ()




SexMale 568 (459)Female 669 (541)





Yes 561 (667)No 281 (333)










Pregnantdagger

Yes 61 17 213 11 (04ndash26)No 442 85 127 1










DISCUSSION







OR (95 CI)

Age (years)


10ndash17 1



65+ 57 (18ndash182)


Yesdagger 1

No 21 (134ndash33)


Nodagger 1

Yes 27 (13ndash57)

Morbid obesity

Nodagger 1

Yes 19 (14ndash36)



10

08

06

04

02

0000 02 04 06 08 10


Sens

itivi

ty

ROC Curve












None declared

Funding

None













References






















Frequency









bull le5 references





































Original Research









References





Peer Review Process


Authorship


Abull Study design


bull Data analysis









Licence












Corrections








No of deaths





TOTAL 353 907 1952 1 073 030 1 812 863



Country

2006 2007 2008 2009 2010

No of cases

No of deaths

CFR ()

No of cases

No of deaths

CFR ()

No of cases

No of deaths

CFR ()

No of cases

No of deaths

CFR ()

No of cases

No of deaths

CFR ()

Cambodia 16 669 158 095 39 851 407 102 9 542 65 068 11 699 38 032 12 500 38 030


6 356 6 009 4 943 4 008 4 149 21 051 7 214 12 017 22 929 46 020

Malaysia 38 556 89 023 48 846 98 020 49 335 112 023 41 486 88 021 46 171 134 029

Philippines 37 101 378 102 55 639 533 096 39 620 373 094 57 819 548 095 135 355 793 059

Singapore 3 127 10 032 8 826 24 027 7 032 10 014 4 497 8 018 5 364 4 007

Viet Nam 68 532 53 008 104 393 88 008 96 451 97 010 105 370 87 008 128 831 55 004

Australia 189 0 000 316 0 0 563 0 0 1 401 0 0 1 171 0 0

Total 170 530 694 041 262 814 1 154 044 206 692 678 033 229 486 781 034 352 321 1 070 030





The Philippines


Singapore


Viet Nam


Pacifi c subregion

Australia


DISCUSSION












None declared

Funding


Acknowledgements


References



















Regional Analysis

BACKGROUND



























Cambodia






monitoring




Hong Kong (China)








Not regular

Malaysia






Routine






Singapore





Routine





Not regular









CountryareasSpace

spraying (outbreak)


Biological control


(source reduction)




collaboration





based) - +

China + - - + + - +




research)+ ++ - +

Fiji + + - + + - -

Malaysia + + - + + ++ +


research)+ + - +


Singapore + + - + + ++ ++

Vanuatu + + - + + - +




































FUTURE PERSPECTIVE











CONCLUSIONS



None declared

Funding


References





































Regional Analysis









METHODS








RESULTS








The Philippines






2003 1 052 520 3 876 530 4 491 464 8 224 6352004 200 550 502 560 1 278 518 1 434 462 2005 551 488 1 051 481 1 847 520 2 022 485 2006 712 531 1 133 539 1 777 519 2 846 506 Total 3 342 513 8 326 541 13 486 498 22 360 579


1999 242 574 1 785 508 5 021 509 2 358 5892001 607 521 3 814 507 13 399 504 7 132 5842002 361 535 3 055 505 8 645 506 4 428 5822003 650 534 4 866 509 15 749 505 8 260 5622004 561 504 3 583 497 12 426 499 6 470 5842005 806 553 4 915 510 17 202 505 10 472 578Total 4 200 545 28 469 507 92 260 503 47 526 572


2000 5 400 17 529 96 583 555 6632001 5 800 27 667 243 580 2 097 6192002 12 333 23 652 429 632 3 481 6482003 22 591 30 567 532 560 4 204 5872004 22 818 87 529 1 223 597 8 127 6182005 32 500 160 569 2 126 541 11 891 583Total 104 587 360 572 4 778 570 31 559 607


1997 11 364 142 458 341 487 285 6951998 24 542 218 514 479 501 249 6671999 27 593 219 447 469 557 417 6382000 45 511 320 500 856 481 1 134 6162001 28 607 248 460 687 476 1 590 6182002 38 579 209 459 665 448 2 011 5912003 16 375 106 585 356 478 1 119 6362004 33 606 236 475 878 495 2 623 6182005 28 500 115 496 235 502 654 627Total 256 539 2 004 481 5 472 484 10 480 618











male cases all ages



Philippinesb


Sri Lankabc






Singapore


Sri Lanka




Malaysia


Cambodia


DISCUSSION




1997 19 429 5441998 27 381 5561999 10 146 5962000 7 103 5922001 16 368 5622002 32 767 5472003 31 545 5612004 33 895 6142005 39 686 5812006 38 556 5812007 48 846 5932008 49 335 615

















None declared

Funding


Acknowledgements


References





























Original Research






METHODS






Notifi cation


Vector control




Data analysis







Ethics


RESULTS











Age group (years)

2005 2007



Total 14 032 (1000) 3289 8 287 (1000) 1806


3000

2500

2000

1500

1000

500


Months

Num

ber o

f cas

es 2007 2005












DISCUSSION





Year 2005 Year 2007









0

10

20

30

40

50

60

70

80

90

100Ja

n-05 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec

Jan-

06 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec

Jan-

07 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec


Month-Year

Dist

ribut

ion

of s

erot

ype







None declared

Funding

None

References




























Original Research





















RESULTS












Frequency ()




SexMale 568 (459)Female 669 (541)





Yes 561 (667)No 281 (333)










Pregnantdagger

Yes 61 17 213 11 (04ndash26)No 442 85 127 1










DISCUSSION







OR (95 CI)

Age (years)


10ndash17 1



65+ 57 (18ndash182)


Yesdagger 1

No 21 (134ndash33)


Nodagger 1

Yes 27 (13ndash57)

Morbid obesity

Nodagger 1

Yes 19 (14ndash36)



10

08

06

04

02

0000 02 04 06 08 10


Sens

itivi

ty

ROC Curve












None declared

Funding

None













References






















Frequency









bull le5 references





































Original Research









References





Peer Review Process


Authorship


Abull Study design


bull Data analysis









Licence












Corrections






The Philippines


Singapore


Viet Nam


Pacifi c subregion

Australia


DISCUSSION












None declared

Funding


Acknowledgements


References



















Regional Analysis

BACKGROUND



























Cambodia






monitoring




Hong Kong (China)








Not regular

Malaysia






Routine






Singapore





Routine





Not regular









CountryareasSpace

spraying (outbreak)


Biological control


(source reduction)




collaboration





based) - +

China + - - + + - +




research)+ ++ - +

Fiji + + - + + - -

Malaysia + + - + + ++ +


research)+ + - +


Singapore + + - + + ++ ++

Vanuatu + + - + + - +




































FUTURE PERSPECTIVE











CONCLUSIONS



None declared

Funding


References





































Regional Analysis









METHODS








RESULTS








The Philippines






2003 1 052 520 3 876 530 4 491 464 8 224 6352004 200 550 502 560 1 278 518 1 434 462 2005 551 488 1 051 481 1 847 520 2 022 485 2006 712 531 1 133 539 1 777 519 2 846 506 Total 3 342 513 8 326 541 13 486 498 22 360 579


1999 242 574 1 785 508 5 021 509 2 358 5892001 607 521 3 814 507 13 399 504 7 132 5842002 361 535 3 055 505 8 645 506 4 428 5822003 650 534 4 866 509 15 749 505 8 260 5622004 561 504 3 583 497 12 426 499 6 470 5842005 806 553 4 915 510 17 202 505 10 472 578Total 4 200 545 28 469 507 92 260 503 47 526 572


2000 5 400 17 529 96 583 555 6632001 5 800 27 667 243 580 2 097 6192002 12 333 23 652 429 632 3 481 6482003 22 591 30 567 532 560 4 204 5872004 22 818 87 529 1 223 597 8 127 6182005 32 500 160 569 2 126 541 11 891 583Total 104 587 360 572 4 778 570 31 559 607


1997 11 364 142 458 341 487 285 6951998 24 542 218 514 479 501 249 6671999 27 593 219 447 469 557 417 6382000 45 511 320 500 856 481 1 134 6162001 28 607 248 460 687 476 1 590 6182002 38 579 209 459 665 448 2 011 5912003 16 375 106 585 356 478 1 119 6362004 33 606 236 475 878 495 2 623 6182005 28 500 115 496 235 502 654 627Total 256 539 2 004 481 5 472 484 10 480 618











male cases all ages



Philippinesb


Sri Lankabc






Singapore


Sri Lanka




Malaysia


Cambodia


DISCUSSION




1997 19 429 5441998 27 381 5561999 10 146 5962000 7 103 5922001 16 368 5622002 32 767 5472003 31 545 5612004 33 895 6142005 39 686 5812006 38 556 5812007 48 846 5932008 49 335 615

















None declared

Funding


Acknowledgements


References





























Original Research






METHODS






Notifi cation


Vector control




Data analysis







Ethics


RESULTS











Age group (years)

2005 2007



Total 14 032 (1000) 3289 8 287 (1000) 1806


3000

2500

2000

1500

1000

500


Months

Num

ber o

f cas

es 2007 2005












DISCUSSION





Year 2005 Year 2007









0

10

20

30

40

50

60

70

80

90

100Ja

n-05 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec

Jan-

06 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec

Jan-

07 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec


Month-Year

Dist

ribut

ion

of s

erot

ype







None declared

Funding

None

References




























Original Research





















RESULTS












Frequency ()




SexMale 568 (459)Female 669 (541)





Yes 561 (667)No 281 (333)










Pregnantdagger

Yes 61 17 213 11 (04ndash26)No 442 85 127 1










DISCUSSION







OR (95 CI)

Age (years)


10ndash17 1



65+ 57 (18ndash182)


Yesdagger 1

No 21 (134ndash33)


Nodagger 1

Yes 27 (13ndash57)

Morbid obesity

Nodagger 1

Yes 19 (14ndash36)



10

08

06

04

02

0000 02 04 06 08 10


Sens

itivi

ty

ROC Curve












None declared

Funding

None













References






















Frequency









bull le5 references





































Original Research









References





Peer Review Process


Authorship


Abull Study design


bull Data analysis









Licence












Corrections










None declared

Funding


Acknowledgements


References



















Regional Analysis

BACKGROUND



























Cambodia






monitoring




Hong Kong (China)








Not regular

Malaysia






Routine






Singapore





Routine





Not regular









CountryareasSpace

spraying (outbreak)


Biological control


(source reduction)




collaboration





based) - +

China + - - + + - +




research)+ ++ - +

Fiji + + - + + - -

Malaysia + + - + + ++ +


research)+ + - +


Singapore + + - + + ++ ++

Vanuatu + + - + + - +




































FUTURE PERSPECTIVE











CONCLUSIONS



None declared

Funding


References





































Regional Analysis









METHODS








RESULTS








The Philippines






2003 1 052 520 3 876 530 4 491 464 8 224 6352004 200 550 502 560 1 278 518 1 434 462 2005 551 488 1 051 481 1 847 520 2 022 485 2006 712 531 1 133 539 1 777 519 2 846 506 Total 3 342 513 8 326 541 13 486 498 22 360 579


1999 242 574 1 785 508 5 021 509 2 358 5892001 607 521 3 814 507 13 399 504 7 132 5842002 361 535 3 055 505 8 645 506 4 428 5822003 650 534 4 866 509 15 749 505 8 260 5622004 561 504 3 583 497 12 426 499 6 470 5842005 806 553 4 915 510 17 202 505 10 472 578Total 4 200 545 28 469 507 92 260 503 47 526 572


2000 5 400 17 529 96 583 555 6632001 5 800 27 667 243 580 2 097 6192002 12 333 23 652 429 632 3 481 6482003 22 591 30 567 532 560 4 204 5872004 22 818 87 529 1 223 597 8 127 6182005 32 500 160 569 2 126 541 11 891 583Total 104 587 360 572 4 778 570 31 559 607


1997 11 364 142 458 341 487 285 6951998 24 542 218 514 479 501 249 6671999 27 593 219 447 469 557 417 6382000 45 511 320 500 856 481 1 134 6162001 28 607 248 460 687 476 1 590 6182002 38 579 209 459 665 448 2 011 5912003 16 375 106 585 356 478 1 119 6362004 33 606 236 475 878 495 2 623 6182005 28 500 115 496 235 502 654 627Total 256 539 2 004 481 5 472 484 10 480 618











male cases all ages



Philippinesb


Sri Lankabc






Singapore


Sri Lanka




Malaysia


Cambodia


DISCUSSION




1997 19 429 5441998 27 381 5561999 10 146 5962000 7 103 5922001 16 368 5622002 32 767 5472003 31 545 5612004 33 895 6142005 39 686 5812006 38 556 5812007 48 846 5932008 49 335 615

















None declared

Funding


Acknowledgements


References





























Original Research






METHODS






Notifi cation


Vector control




Data analysis







Ethics


RESULTS











Age group (years)

2005 2007



Total 14 032 (1000) 3289 8 287 (1000) 1806


3000

2500

2000

1500

1000

500


Months

Num

ber o

f cas

es 2007 2005












DISCUSSION





Year 2005 Year 2007









0

10

20

30

40

50

60

70

80

90

100Ja

n-05 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec

Jan-

06 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec

Jan-

07 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec


Month-Year

Dist

ribut

ion

of s

erot

ype







None declared

Funding

None

References




























Original Research





















RESULTS












Frequency ()




SexMale 568 (459)Female 669 (541)





Yes 561 (667)No 281 (333)










Pregnantdagger

Yes 61 17 213 11 (04ndash26)No 442 85 127 1










DISCUSSION







OR (95 CI)

Age (years)


10ndash17 1



65+ 57 (18ndash182)


Yesdagger 1

No 21 (134ndash33)


Nodagger 1

Yes 27 (13ndash57)

Morbid obesity

Nodagger 1

Yes 19 (14ndash36)



10

08

06

04

02

0000 02 04 06 08 10


Sens

itivi

ty

ROC Curve












None declared

Funding

None













References






















Frequency









bull le5 references





































Original Research









References





Peer Review Process


Authorship


Abull Study design


bull Data analysis









Licence












Corrections











Regional Analysis

BACKGROUND



























Cambodia






monitoring




Hong Kong (China)








Not regular

Malaysia






Routine






Singapore





Routine





Not regular









CountryareasSpace

spraying (outbreak)


Biological control


(source reduction)




collaboration





based) - +

China + - - + + - +




research)+ ++ - +

Fiji + + - + + - -

Malaysia + + - + + ++ +


research)+ + - +


Singapore + + - + + ++ ++

Vanuatu + + - + + - +




































FUTURE PERSPECTIVE











CONCLUSIONS



None declared

Funding


References





































Regional Analysis









METHODS








RESULTS








The Philippines






2003 1 052 520 3 876 530 4 491 464 8 224 6352004 200 550 502 560 1 278 518 1 434 462 2005 551 488 1 051 481 1 847 520 2 022 485 2006 712 531 1 133 539 1 777 519 2 846 506 Total 3 342 513 8 326 541 13 486 498 22 360 579


1999 242 574 1 785 508 5 021 509 2 358 5892001 607 521 3 814 507 13 399 504 7 132 5842002 361 535 3 055 505 8 645 506 4 428 5822003 650 534 4 866 509 15 749 505 8 260 5622004 561 504 3 583 497 12 426 499 6 470 5842005 806 553 4 915 510 17 202 505 10 472 578Total 4 200 545 28 469 507 92 260 503 47 526 572


2000 5 400 17 529 96 583 555 6632001 5 800 27 667 243 580 2 097 6192002 12 333 23 652 429 632 3 481 6482003 22 591 30 567 532 560 4 204 5872004 22 818 87 529 1 223 597 8 127 6182005 32 500 160 569 2 126 541 11 891 583Total 104 587 360 572 4 778 570 31 559 607


1997 11 364 142 458 341 487 285 6951998 24 542 218 514 479 501 249 6671999 27 593 219 447 469 557 417 6382000 45 511 320 500 856 481 1 134 6162001 28 607 248 460 687 476 1 590 6182002 38 579 209 459 665 448 2 011 5912003 16 375 106 585 356 478 1 119 6362004 33 606 236 475 878 495 2 623 6182005 28 500 115 496 235 502 654 627Total 256 539 2 004 481 5 472 484 10 480 618











male cases all ages



Philippinesb


Sri Lankabc






Singapore


Sri Lanka




Malaysia


Cambodia


DISCUSSION




1997 19 429 5441998 27 381 5561999 10 146 5962000 7 103 5922001 16 368 5622002 32 767 5472003 31 545 5612004 33 895 6142005 39 686 5812006 38 556 5812007 48 846 5932008 49 335 615

















None declared

Funding


Acknowledgements


References





























Original Research






METHODS






Notifi cation


Vector control




Data analysis







Ethics


RESULTS











Age group (years)

2005 2007



Total 14 032 (1000) 3289 8 287 (1000) 1806


3000

2500

2000

1500

1000

500


Months

Num

ber o

f cas

es 2007 2005












DISCUSSION





Year 2005 Year 2007









0

10

20

30

40

50

60

70

80

90

100Ja

n-05 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec

Jan-

06 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec

Jan-

07 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec


Month-Year

Dist

ribut

ion

of s

erot

ype







None declared

Funding

None

References




























Original Research





















RESULTS












Frequency ()




SexMale 568 (459)Female 669 (541)





Yes 561 (667)No 281 (333)










Pregnantdagger

Yes 61 17 213 11 (04ndash26)No 442 85 127 1










DISCUSSION







OR (95 CI)

Age (years)


10ndash17 1



65+ 57 (18ndash182)


Yesdagger 1

No 21 (134ndash33)


Nodagger 1

Yes 27 (13ndash57)

Morbid obesity

Nodagger 1

Yes 19 (14ndash36)



10

08

06

04

02

0000 02 04 06 08 10


Sens

itivi

ty

ROC Curve












None declared

Funding

None













References






















Frequency









bull le5 references





































Original Research









References





Peer Review Process


Authorship


Abull Study design


bull Data analysis









Licence












Corrections























Cambodia






monitoring




Hong Kong (China)








Not regular

Malaysia






Routine






Singapore





Routine





Not regular









CountryareasSpace

spraying (outbreak)


Biological control


(source reduction)




collaboration





based) - +

China + - - + + - +




research)+ ++ - +

Fiji + + - + + - -

Malaysia + + - + + ++ +


research)+ + - +


Singapore + + - + + ++ ++

Vanuatu + + - + + - +




































FUTURE PERSPECTIVE











CONCLUSIONS



None declared

Funding


References





































Regional Analysis









METHODS








RESULTS








The Philippines






2003 1 052 520 3 876 530 4 491 464 8 224 6352004 200 550 502 560 1 278 518 1 434 462 2005 551 488 1 051 481 1 847 520 2 022 485 2006 712 531 1 133 539 1 777 519 2 846 506 Total 3 342 513 8 326 541 13 486 498 22 360 579


1999 242 574 1 785 508 5 021 509 2 358 5892001 607 521 3 814 507 13 399 504 7 132 5842002 361 535 3 055 505 8 645 506 4 428 5822003 650 534 4 866 509 15 749 505 8 260 5622004 561 504 3 583 497 12 426 499 6 470 5842005 806 553 4 915 510 17 202 505 10 472 578Total 4 200 545 28 469 507 92 260 503 47 526 572


2000 5 400 17 529 96 583 555 6632001 5 800 27 667 243 580 2 097 6192002 12 333 23 652 429 632 3 481 6482003 22 591 30 567 532 560 4 204 5872004 22 818 87 529 1 223 597 8 127 6182005 32 500 160 569 2 126 541 11 891 583Total 104 587 360 572 4 778 570 31 559 607


1997 11 364 142 458 341 487 285 6951998 24 542 218 514 479 501 249 6671999 27 593 219 447 469 557 417 6382000 45 511 320 500 856 481 1 134 6162001 28 607 248 460 687 476 1 590 6182002 38 579 209 459 665 448 2 011 5912003 16 375 106 585 356 478 1 119 6362004 33 606 236 475 878 495 2 623 6182005 28 500 115 496 235 502 654 627Total 256 539 2 004 481 5 472 484 10 480 618











male cases all ages



Philippinesb


Sri Lankabc






Singapore


Sri Lanka




Malaysia


Cambodia


DISCUSSION




1997 19 429 5441998 27 381 5561999 10 146 5962000 7 103 5922001 16 368 5622002 32 767 5472003 31 545 5612004 33 895 6142005 39 686 5812006 38 556 5812007 48 846 5932008 49 335 615

















None declared

Funding


Acknowledgements


References





























Original Research






METHODS






Notifi cation


Vector control




Data analysis







Ethics


RESULTS











Age group (years)

2005 2007



Total 14 032 (1000) 3289 8 287 (1000) 1806


3000

2500

2000

1500

1000

500


Months

Num

ber o

f cas

es 2007 2005












DISCUSSION





Year 2005 Year 2007









0

10

20

30

40

50

60

70

80

90

100Ja

n-05 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec

Jan-

06 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec

Jan-

07 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec


Month-Year

Dist

ribut

ion

of s

erot

ype







None declared

Funding

None

References




























Original Research





















RESULTS












Frequency ()




SexMale 568 (459)Female 669 (541)





Yes 561 (667)No 281 (333)










Pregnantdagger

Yes 61 17 213 11 (04ndash26)No 442 85 127 1










DISCUSSION







OR (95 CI)

Age (years)


10ndash17 1



65+ 57 (18ndash182)


Yesdagger 1

No 21 (134ndash33)


Nodagger 1

Yes 27 (13ndash57)

Morbid obesity

Nodagger 1

Yes 19 (14ndash36)



10

08

06

04

02

0000 02 04 06 08 10


Sens

itivi

ty

ROC Curve












None declared

Funding

None













References






















Frequency









bull le5 references





































Original Research









References





Peer Review Process


Authorship


Abull Study design


bull Data analysis









Licence












Corrections











CountryareasSpace

spraying (outbreak)


Biological control


(source reduction)




collaboration





based) - +

China + - - + + - +




research)+ ++ - +

Fiji + + - + + - -

Malaysia + + - + + ++ +


research)+ + - +


Singapore + + - + + ++ ++

Vanuatu + + - + + - +




































FUTURE PERSPECTIVE











CONCLUSIONS



None declared

Funding


References





































Regional Analysis









METHODS








RESULTS








The Philippines






2003 1 052 520 3 876 530 4 491 464 8 224 6352004 200 550 502 560 1 278 518 1 434 462 2005 551 488 1 051 481 1 847 520 2 022 485 2006 712 531 1 133 539 1 777 519 2 846 506 Total 3 342 513 8 326 541 13 486 498 22 360 579


1999 242 574 1 785 508 5 021 509 2 358 5892001 607 521 3 814 507 13 399 504 7 132 5842002 361 535 3 055 505 8 645 506 4 428 5822003 650 534 4 866 509 15 749 505 8 260 5622004 561 504 3 583 497 12 426 499 6 470 5842005 806 553 4 915 510 17 202 505 10 472 578Total 4 200 545 28 469 507 92 260 503 47 526 572


2000 5 400 17 529 96 583 555 6632001 5 800 27 667 243 580 2 097 6192002 12 333 23 652 429 632 3 481 6482003 22 591 30 567 532 560 4 204 5872004 22 818 87 529 1 223 597 8 127 6182005 32 500 160 569 2 126 541 11 891 583Total 104 587 360 572 4 778 570 31 559 607


1997 11 364 142 458 341 487 285 6951998 24 542 218 514 479 501 249 6671999 27 593 219 447 469 557 417 6382000 45 511 320 500 856 481 1 134 6162001 28 607 248 460 687 476 1 590 6182002 38 579 209 459 665 448 2 011 5912003 16 375 106 585 356 478 1 119 6362004 33 606 236 475 878 495 2 623 6182005 28 500 115 496 235 502 654 627Total 256 539 2 004 481 5 472 484 10 480 618











male cases all ages



Philippinesb


Sri Lankabc






Singapore


Sri Lanka




Malaysia


Cambodia


DISCUSSION




1997 19 429 5441998 27 381 5561999 10 146 5962000 7 103 5922001 16 368 5622002 32 767 5472003 31 545 5612004 33 895 6142005 39 686 5812006 38 556 5812007 48 846 5932008 49 335 615

















None declared

Funding


Acknowledgements


References





























Original Research






METHODS






Notifi cation


Vector control




Data analysis







Ethics


RESULTS











Age group (years)

2005 2007



Total 14 032 (1000) 3289 8 287 (1000) 1806


3000

2500

2000

1500

1000

500


Months

Num

ber o

f cas

es 2007 2005












DISCUSSION





Year 2005 Year 2007









0

10

20

30

40

50

60

70

80

90

100Ja

n-05 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec

Jan-

06 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec

Jan-

07 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec


Month-Year

Dist

ribut

ion

of s

erot

ype







None declared

Funding

None

References




























Original Research





















RESULTS












Frequency ()




SexMale 568 (459)Female 669 (541)





Yes 561 (667)No 281 (333)










Pregnantdagger

Yes 61 17 213 11 (04ndash26)No 442 85 127 1










DISCUSSION







OR (95 CI)

Age (years)


10ndash17 1



65+ 57 (18ndash182)


Yesdagger 1

No 21 (134ndash33)


Nodagger 1

Yes 27 (13ndash57)

Morbid obesity

Nodagger 1

Yes 19 (14ndash36)



10

08

06

04

02

0000 02 04 06 08 10


Sens

itivi

ty

ROC Curve












None declared

Funding

None













References






















Frequency









bull le5 references





































Original Research









References





Peer Review Process


Authorship


Abull Study design


bull Data analysis









Licence












Corrections




































FUTURE PERSPECTIVE











CONCLUSIONS



None declared

Funding


References





































Regional Analysis









METHODS








RESULTS








The Philippines






2003 1 052 520 3 876 530 4 491 464 8 224 6352004 200 550 502 560 1 278 518 1 434 462 2005 551 488 1 051 481 1 847 520 2 022 485 2006 712 531 1 133 539 1 777 519 2 846 506 Total 3 342 513 8 326 541 13 486 498 22 360 579


1999 242 574 1 785 508 5 021 509 2 358 5892001 607 521 3 814 507 13 399 504 7 132 5842002 361 535 3 055 505 8 645 506 4 428 5822003 650 534 4 866 509 15 749 505 8 260 5622004 561 504 3 583 497 12 426 499 6 470 5842005 806 553 4 915 510 17 202 505 10 472 578Total 4 200 545 28 469 507 92 260 503 47 526 572


2000 5 400 17 529 96 583 555 6632001 5 800 27 667 243 580 2 097 6192002 12 333 23 652 429 632 3 481 6482003 22 591 30 567 532 560 4 204 5872004 22 818 87 529 1 223 597 8 127 6182005 32 500 160 569 2 126 541 11 891 583Total 104 587 360 572 4 778 570 31 559 607


1997 11 364 142 458 341 487 285 6951998 24 542 218 514 479 501 249 6671999 27 593 219 447 469 557 417 6382000 45 511 320 500 856 481 1 134 6162001 28 607 248 460 687 476 1 590 6182002 38 579 209 459 665 448 2 011 5912003 16 375 106 585 356 478 1 119 6362004 33 606 236 475 878 495 2 623 6182005 28 500 115 496 235 502 654 627Total 256 539 2 004 481 5 472 484 10 480 618











male cases all ages



Philippinesb


Sri Lankabc






Singapore


Sri Lanka




Malaysia


Cambodia


DISCUSSION




1997 19 429 5441998 27 381 5561999 10 146 5962000 7 103 5922001 16 368 5622002 32 767 5472003 31 545 5612004 33 895 6142005 39 686 5812006 38 556 5812007 48 846 5932008 49 335 615

















None declared

Funding


Acknowledgements


References





























Original Research






METHODS






Notifi cation


Vector control




Data analysis







Ethics


RESULTS











Age group (years)

2005 2007



Total 14 032 (1000) 3289 8 287 (1000) 1806


3000

2500

2000

1500

1000

500


Months

Num

ber o

f cas

es 2007 2005












DISCUSSION





Year 2005 Year 2007









0

10

20

30

40

50

60

70

80

90

100Ja

n-05 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec

Jan-

06 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec

Jan-

07 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec


Month-Year

Dist

ribut

ion

of s

erot

ype







None declared

Funding

None

References




























Original Research





















RESULTS












Frequency ()




SexMale 568 (459)Female 669 (541)





Yes 561 (667)No 281 (333)










Pregnantdagger

Yes 61 17 213 11 (04ndash26)No 442 85 127 1










DISCUSSION







OR (95 CI)

Age (years)


10ndash17 1



65+ 57 (18ndash182)


Yesdagger 1

No 21 (134ndash33)


Nodagger 1

Yes 27 (13ndash57)

Morbid obesity

Nodagger 1

Yes 19 (14ndash36)



10

08

06

04

02

0000 02 04 06 08 10


Sens

itivi

ty

ROC Curve












None declared

Funding

None













References






















Frequency









bull le5 references





































Original Research









References





Peer Review Process


Authorship


Abull Study design


bull Data analysis









Licence












Corrections






















FUTURE PERSPECTIVE











CONCLUSIONS



None declared

Funding


References





































Regional Analysis









METHODS








RESULTS








The Philippines






2003 1 052 520 3 876 530 4 491 464 8 224 6352004 200 550 502 560 1 278 518 1 434 462 2005 551 488 1 051 481 1 847 520 2 022 485 2006 712 531 1 133 539 1 777 519 2 846 506 Total 3 342 513 8 326 541 13 486 498 22 360 579


1999 242 574 1 785 508 5 021 509 2 358 5892001 607 521 3 814 507 13 399 504 7 132 5842002 361 535 3 055 505 8 645 506 4 428 5822003 650 534 4 866 509 15 749 505 8 260 5622004 561 504 3 583 497 12 426 499 6 470 5842005 806 553 4 915 510 17 202 505 10 472 578Total 4 200 545 28 469 507 92 260 503 47 526 572


2000 5 400 17 529 96 583 555 6632001 5 800 27 667 243 580 2 097 6192002 12 333 23 652 429 632 3 481 6482003 22 591 30 567 532 560 4 204 5872004 22 818 87 529 1 223 597 8 127 6182005 32 500 160 569 2 126 541 11 891 583Total 104 587 360 572 4 778 570 31 559 607


1997 11 364 142 458 341 487 285 6951998 24 542 218 514 479 501 249 6671999 27 593 219 447 469 557 417 6382000 45 511 320 500 856 481 1 134 6162001 28 607 248 460 687 476 1 590 6182002 38 579 209 459 665 448 2 011 5912003 16 375 106 585 356 478 1 119 6362004 33 606 236 475 878 495 2 623 6182005 28 500 115 496 235 502 654 627Total 256 539 2 004 481 5 472 484 10 480 618











male cases all ages



Philippinesb


Sri Lankabc






Singapore


Sri Lanka




Malaysia


Cambodia


DISCUSSION




1997 19 429 5441998 27 381 5561999 10 146 5962000 7 103 5922001 16 368 5622002 32 767 5472003 31 545 5612004 33 895 6142005 39 686 5812006 38 556 5812007 48 846 5932008 49 335 615

















None declared

Funding


Acknowledgements


References





























Original Research






METHODS






Notifi cation


Vector control




Data analysis







Ethics


RESULTS











Age group (years)

2005 2007



Total 14 032 (1000) 3289 8 287 (1000) 1806


3000

2500

2000

1500

1000

500


Months

Num

ber o

f cas

es 2007 2005












DISCUSSION





Year 2005 Year 2007









0

10

20

30

40

50

60

70

80

90

100Ja

n-05 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec

Jan-

06 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec

Jan-

07 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec


Month-Year

Dist

ribut

ion

of s

erot

ype







None declared

Funding

None

References




























Original Research





















RESULTS












Frequency ()




SexMale 568 (459)Female 669 (541)





Yes 561 (667)No 281 (333)










Pregnantdagger

Yes 61 17 213 11 (04ndash26)No 442 85 127 1










DISCUSSION







OR (95 CI)

Age (years)


10ndash17 1



65+ 57 (18ndash182)


Yesdagger 1

No 21 (134ndash33)


Nodagger 1

Yes 27 (13ndash57)

Morbid obesity

Nodagger 1

Yes 19 (14ndash36)



10

08

06

04

02

0000 02 04 06 08 10


Sens

itivi

ty

ROC Curve












None declared

Funding

None













References






















Frequency









bull le5 references





































Original Research









References





Peer Review Process


Authorship


Abull Study design


bull Data analysis









Licence












Corrections










FUTURE PERSPECTIVE











CONCLUSIONS



None declared

Funding


References





































Regional Analysis









METHODS








RESULTS








The Philippines






2003 1 052 520 3 876 530 4 491 464 8 224 6352004 200 550 502 560 1 278 518 1 434 462 2005 551 488 1 051 481 1 847 520 2 022 485 2006 712 531 1 133 539 1 777 519 2 846 506 Total 3 342 513 8 326 541 13 486 498 22 360 579


1999 242 574 1 785 508 5 021 509 2 358 5892001 607 521 3 814 507 13 399 504 7 132 5842002 361 535 3 055 505 8 645 506 4 428 5822003 650 534 4 866 509 15 749 505 8 260 5622004 561 504 3 583 497 12 426 499 6 470 5842005 806 553 4 915 510 17 202 505 10 472 578Total 4 200 545 28 469 507 92 260 503 47 526 572


2000 5 400 17 529 96 583 555 6632001 5 800 27 667 243 580 2 097 6192002 12 333 23 652 429 632 3 481 6482003 22 591 30 567 532 560 4 204 5872004 22 818 87 529 1 223 597 8 127 6182005 32 500 160 569 2 126 541 11 891 583Total 104 587 360 572 4 778 570 31 559 607


1997 11 364 142 458 341 487 285 6951998 24 542 218 514 479 501 249 6671999 27 593 219 447 469 557 417 6382000 45 511 320 500 856 481 1 134 6162001 28 607 248 460 687 476 1 590 6182002 38 579 209 459 665 448 2 011 5912003 16 375 106 585 356 478 1 119 6362004 33 606 236 475 878 495 2 623 6182005 28 500 115 496 235 502 654 627Total 256 539 2 004 481 5 472 484 10 480 618











male cases all ages



Philippinesb


Sri Lankabc






Singapore


Sri Lanka




Malaysia


Cambodia


DISCUSSION




1997 19 429 5441998 27 381 5561999 10 146 5962000 7 103 5922001 16 368 5622002 32 767 5472003 31 545 5612004 33 895 6142005 39 686 5812006 38 556 5812007 48 846 5932008 49 335 615

















None declared

Funding


Acknowledgements


References





























Original Research






METHODS






Notifi cation


Vector control




Data analysis







Ethics


RESULTS











Age group (years)

2005 2007



Total 14 032 (1000) 3289 8 287 (1000) 1806


3000

2500

2000

1500

1000

500


Months

Num

ber o

f cas

es 2007 2005












DISCUSSION





Year 2005 Year 2007









0

10

20

30

40

50

60

70

80

90

100Ja

n-05 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec

Jan-

06 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec

Jan-

07 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec


Month-Year

Dist

ribut

ion

of s

erot

ype







None declared

Funding

None

References




























Original Research





















RESULTS












Frequency ()




SexMale 568 (459)Female 669 (541)





Yes 561 (667)No 281 (333)










Pregnantdagger

Yes 61 17 213 11 (04ndash26)No 442 85 127 1










DISCUSSION







OR (95 CI)

Age (years)


10ndash17 1



65+ 57 (18ndash182)


Yesdagger 1

No 21 (134ndash33)


Nodagger 1

Yes 27 (13ndash57)

Morbid obesity

Nodagger 1

Yes 19 (14ndash36)



10

08

06

04

02

0000 02 04 06 08 10


Sens

itivi

ty

ROC Curve












None declared

Funding

None













References






















Frequency









bull le5 references





































Original Research









References





Peer Review Process


Authorship


Abull Study design


bull Data analysis









Licence












Corrections










CONCLUSIONS



None declared

Funding


References





































Regional Analysis









METHODS








RESULTS








The Philippines






2003 1 052 520 3 876 530 4 491 464 8 224 6352004 200 550 502 560 1 278 518 1 434 462 2005 551 488 1 051 481 1 847 520 2 022 485 2006 712 531 1 133 539 1 777 519 2 846 506 Total 3 342 513 8 326 541 13 486 498 22 360 579


1999 242 574 1 785 508 5 021 509 2 358 5892001 607 521 3 814 507 13 399 504 7 132 5842002 361 535 3 055 505 8 645 506 4 428 5822003 650 534 4 866 509 15 749 505 8 260 5622004 561 504 3 583 497 12 426 499 6 470 5842005 806 553 4 915 510 17 202 505 10 472 578Total 4 200 545 28 469 507 92 260 503 47 526 572


2000 5 400 17 529 96 583 555 6632001 5 800 27 667 243 580 2 097 6192002 12 333 23 652 429 632 3 481 6482003 22 591 30 567 532 560 4 204 5872004 22 818 87 529 1 223 597 8 127 6182005 32 500 160 569 2 126 541 11 891 583Total 104 587 360 572 4 778 570 31 559 607


1997 11 364 142 458 341 487 285 6951998 24 542 218 514 479 501 249 6671999 27 593 219 447 469 557 417 6382000 45 511 320 500 856 481 1 134 6162001 28 607 248 460 687 476 1 590 6182002 38 579 209 459 665 448 2 011 5912003 16 375 106 585 356 478 1 119 6362004 33 606 236 475 878 495 2 623 6182005 28 500 115 496 235 502 654 627Total 256 539 2 004 481 5 472 484 10 480 618











male cases all ages



Philippinesb


Sri Lankabc






Singapore


Sri Lanka




Malaysia


Cambodia


DISCUSSION




1997 19 429 5441998 27 381 5561999 10 146 5962000 7 103 5922001 16 368 5622002 32 767 5472003 31 545 5612004 33 895 6142005 39 686 5812006 38 556 5812007 48 846 5932008 49 335 615

















None declared

Funding


Acknowledgements


References





























Original Research






METHODS






Notifi cation


Vector control




Data analysis







Ethics


RESULTS











Age group (years)

2005 2007



Total 14 032 (1000) 3289 8 287 (1000) 1806


3000

2500

2000

1500

1000

500


Months

Num

ber o

f cas

es 2007 2005












DISCUSSION





Year 2005 Year 2007









0

10

20

30

40

50

60

70

80

90

100Ja

n-05 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec

Jan-

06 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec

Jan-

07 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec


Month-Year

Dist

ribut

ion

of s

erot

ype







None declared

Funding

None

References




























Original Research





















RESULTS












Frequency ()




SexMale 568 (459)Female 669 (541)





Yes 561 (667)No 281 (333)










Pregnantdagger

Yes 61 17 213 11 (04ndash26)No 442 85 127 1










DISCUSSION







OR (95 CI)

Age (years)


10ndash17 1



65+ 57 (18ndash182)


Yesdagger 1

No 21 (134ndash33)


Nodagger 1

Yes 27 (13ndash57)

Morbid obesity

Nodagger 1

Yes 19 (14ndash36)



10

08

06

04

02

0000 02 04 06 08 10


Sens

itivi

ty

ROC Curve












None declared

Funding

None













References






















Frequency









bull le5 references





































Original Research









References





Peer Review Process


Authorship


Abull Study design


bull Data analysis









Licence












Corrections






































Regional Analysis









METHODS








RESULTS








The Philippines






2003 1 052 520 3 876 530 4 491 464 8 224 6352004 200 550 502 560 1 278 518 1 434 462 2005 551 488 1 051 481 1 847 520 2 022 485 2006 712 531 1 133 539 1 777 519 2 846 506 Total 3 342 513 8 326 541 13 486 498 22 360 579


1999 242 574 1 785 508 5 021 509 2 358 5892001 607 521 3 814 507 13 399 504 7 132 5842002 361 535 3 055 505 8 645 506 4 428 5822003 650 534 4 866 509 15 749 505 8 260 5622004 561 504 3 583 497 12 426 499 6 470 5842005 806 553 4 915 510 17 202 505 10 472 578Total 4 200 545 28 469 507 92 260 503 47 526 572


2000 5 400 17 529 96 583 555 6632001 5 800 27 667 243 580 2 097 6192002 12 333 23 652 429 632 3 481 6482003 22 591 30 567 532 560 4 204 5872004 22 818 87 529 1 223 597 8 127 6182005 32 500 160 569 2 126 541 11 891 583Total 104 587 360 572 4 778 570 31 559 607


1997 11 364 142 458 341 487 285 6951998 24 542 218 514 479 501 249 6671999 27 593 219 447 469 557 417 6382000 45 511 320 500 856 481 1 134 6162001 28 607 248 460 687 476 1 590 6182002 38 579 209 459 665 448 2 011 5912003 16 375 106 585 356 478 1 119 6362004 33 606 236 475 878 495 2 623 6182005 28 500 115 496 235 502 654 627Total 256 539 2 004 481 5 472 484 10 480 618











male cases all ages



Philippinesb


Sri Lankabc






Singapore


Sri Lanka




Malaysia


Cambodia


DISCUSSION




1997 19 429 5441998 27 381 5561999 10 146 5962000 7 103 5922001 16 368 5622002 32 767 5472003 31 545 5612004 33 895 6142005 39 686 5812006 38 556 5812007 48 846 5932008 49 335 615

















None declared

Funding


Acknowledgements


References





























Original Research






METHODS






Notifi cation


Vector control




Data analysis







Ethics


RESULTS











Age group (years)

2005 2007



Total 14 032 (1000) 3289 8 287 (1000) 1806


3000

2500

2000

1500

1000

500


Months

Num

ber o

f cas

es 2007 2005












DISCUSSION





Year 2005 Year 2007









0

10

20

30

40

50

60

70

80

90

100Ja

n-05 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec

Jan-

06 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec

Jan-

07 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec


Month-Year

Dist

ribut

ion

of s

erot

ype







None declared

Funding

None

References




























Original Research





















RESULTS












Frequency ()




SexMale 568 (459)Female 669 (541)





Yes 561 (667)No 281 (333)










Pregnantdagger

Yes 61 17 213 11 (04ndash26)No 442 85 127 1










DISCUSSION







OR (95 CI)

Age (years)


10ndash17 1



65+ 57 (18ndash182)


Yesdagger 1

No 21 (134ndash33)


Nodagger 1

Yes 27 (13ndash57)

Morbid obesity

Nodagger 1

Yes 19 (14ndash36)



10

08

06

04

02

0000 02 04 06 08 10


Sens

itivi

ty

ROC Curve












None declared

Funding

None













References






















Frequency









bull le5 references





































Original Research









References





Peer Review Process


Authorship


Abull Study design


bull Data analysis









Licence












Corrections







Regional Analysis









METHODS








RESULTS








The Philippines






2003 1 052 520 3 876 530 4 491 464 8 224 6352004 200 550 502 560 1 278 518 1 434 462 2005 551 488 1 051 481 1 847 520 2 022 485 2006 712 531 1 133 539 1 777 519 2 846 506 Total 3 342 513 8 326 541 13 486 498 22 360 579


1999 242 574 1 785 508 5 021 509 2 358 5892001 607 521 3 814 507 13 399 504 7 132 5842002 361 535 3 055 505 8 645 506 4 428 5822003 650 534 4 866 509 15 749 505 8 260 5622004 561 504 3 583 497 12 426 499 6 470 5842005 806 553 4 915 510 17 202 505 10 472 578Total 4 200 545 28 469 507 92 260 503 47 526 572


2000 5 400 17 529 96 583 555 6632001 5 800 27 667 243 580 2 097 6192002 12 333 23 652 429 632 3 481 6482003 22 591 30 567 532 560 4 204 5872004 22 818 87 529 1 223 597 8 127 6182005 32 500 160 569 2 126 541 11 891 583Total 104 587 360 572 4 778 570 31 559 607


1997 11 364 142 458 341 487 285 6951998 24 542 218 514 479 501 249 6671999 27 593 219 447 469 557 417 6382000 45 511 320 500 856 481 1 134 6162001 28 607 248 460 687 476 1 590 6182002 38 579 209 459 665 448 2 011 5912003 16 375 106 585 356 478 1 119 6362004 33 606 236 475 878 495 2 623 6182005 28 500 115 496 235 502 654 627Total 256 539 2 004 481 5 472 484 10 480 618











male cases all ages



Philippinesb


Sri Lankabc






Singapore


Sri Lanka




Malaysia


Cambodia


DISCUSSION




1997 19 429 5441998 27 381 5561999 10 146 5962000 7 103 5922001 16 368 5622002 32 767 5472003 31 545 5612004 33 895 6142005 39 686 5812006 38 556 5812007 48 846 5932008 49 335 615

















None declared

Funding


Acknowledgements


References





























Original Research






METHODS






Notifi cation


Vector control




Data analysis







Ethics


RESULTS











Age group (years)

2005 2007



Total 14 032 (1000) 3289 8 287 (1000) 1806


3000

2500

2000

1500

1000

500


Months

Num

ber o

f cas

es 2007 2005












DISCUSSION





Year 2005 Year 2007









0

10

20

30

40

50

60

70

80

90

100Ja

n-05 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec

Jan-

06 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec

Jan-

07 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec


Month-Year

Dist

ribut

ion

of s

erot

ype







None declared

Funding

None

References




























Original Research





















RESULTS












Frequency ()




SexMale 568 (459)Female 669 (541)





Yes 561 (667)No 281 (333)










Pregnantdagger

Yes 61 17 213 11 (04ndash26)No 442 85 127 1










DISCUSSION







OR (95 CI)

Age (years)


10ndash17 1



65+ 57 (18ndash182)


Yesdagger 1

No 21 (134ndash33)


Nodagger 1

Yes 27 (13ndash57)

Morbid obesity

Nodagger 1

Yes 19 (14ndash36)



10

08

06

04

02

0000 02 04 06 08 10


Sens

itivi

ty

ROC Curve












None declared

Funding

None













References






















Frequency









bull le5 references





































Original Research









References





Peer Review Process


Authorship


Abull Study design


bull Data analysis









Licence












Corrections









RESULTS








The Philippines






2003 1 052 520 3 876 530 4 491 464 8 224 6352004 200 550 502 560 1 278 518 1 434 462 2005 551 488 1 051 481 1 847 520 2 022 485 2006 712 531 1 133 539 1 777 519 2 846 506 Total 3 342 513 8 326 541 13 486 498 22 360 579


1999 242 574 1 785 508 5 021 509 2 358 5892001 607 521 3 814 507 13 399 504 7 132 5842002 361 535 3 055 505 8 645 506 4 428 5822003 650 534 4 866 509 15 749 505 8 260 5622004 561 504 3 583 497 12 426 499 6 470 5842005 806 553 4 915 510 17 202 505 10 472 578Total 4 200 545 28 469 507 92 260 503 47 526 572


2000 5 400 17 529 96 583 555 6632001 5 800 27 667 243 580 2 097 6192002 12 333 23 652 429 632 3 481 6482003 22 591 30 567 532 560 4 204 5872004 22 818 87 529 1 223 597 8 127 6182005 32 500 160 569 2 126 541 11 891 583Total 104 587 360 572 4 778 570 31 559 607


1997 11 364 142 458 341 487 285 6951998 24 542 218 514 479 501 249 6671999 27 593 219 447 469 557 417 6382000 45 511 320 500 856 481 1 134 6162001 28 607 248 460 687 476 1 590 6182002 38 579 209 459 665 448 2 011 5912003 16 375 106 585 356 478 1 119 6362004 33 606 236 475 878 495 2 623 6182005 28 500 115 496 235 502 654 627Total 256 539 2 004 481 5 472 484 10 480 618











male cases all ages



Philippinesb


Sri Lankabc






Singapore


Sri Lanka




Malaysia


Cambodia


DISCUSSION




1997 19 429 5441998 27 381 5561999 10 146 5962000 7 103 5922001 16 368 5622002 32 767 5472003 31 545 5612004 33 895 6142005 39 686 5812006 38 556 5812007 48 846 5932008 49 335 615

















None declared

Funding


Acknowledgements


References





























Original Research






METHODS






Notifi cation


Vector control




Data analysis







Ethics


RESULTS











Age group (years)

2005 2007



Total 14 032 (1000) 3289 8 287 (1000) 1806


3000

2500

2000

1500

1000

500


Months

Num

ber o

f cas

es 2007 2005












DISCUSSION





Year 2005 Year 2007









0

10

20

30

40

50

60

70

80

90

100Ja

n-05 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec

Jan-

06 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec

Jan-

07 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec


Month-Year

Dist

ribut

ion

of s

erot

ype







None declared

Funding

None

References




























Original Research





















RESULTS












Frequency ()




SexMale 568 (459)Female 669 (541)





Yes 561 (667)No 281 (333)










Pregnantdagger

Yes 61 17 213 11 (04ndash26)No 442 85 127 1










DISCUSSION







OR (95 CI)

Age (years)


10ndash17 1



65+ 57 (18ndash182)


Yesdagger 1

No 21 (134ndash33)


Nodagger 1

Yes 27 (13ndash57)

Morbid obesity

Nodagger 1

Yes 19 (14ndash36)



10

08

06

04

02

0000 02 04 06 08 10


Sens

itivi

ty

ROC Curve












None declared

Funding

None













References






















Frequency









bull le5 references





































Original Research









References





Peer Review Process


Authorship


Abull Study design


bull Data analysis









Licence












Corrections







The Philippines






2003 1 052 520 3 876 530 4 491 464 8 224 6352004 200 550 502 560 1 278 518 1 434 462 2005 551 488 1 051 481 1 847 520 2 022 485 2006 712 531 1 133 539 1 777 519 2 846 506 Total 3 342 513 8 326 541 13 486 498 22 360 579


1999 242 574 1 785 508 5 021 509 2 358 5892001 607 521 3 814 507 13 399 504 7 132 5842002 361 535 3 055 505 8 645 506 4 428 5822003 650 534 4 866 509 15 749 505 8 260 5622004 561 504 3 583 497 12 426 499 6 470 5842005 806 553 4 915 510 17 202 505 10 472 578Total 4 200 545 28 469 507 92 260 503 47 526 572


2000 5 400 17 529 96 583 555 6632001 5 800 27 667 243 580 2 097 6192002 12 333 23 652 429 632 3 481 6482003 22 591 30 567 532 560 4 204 5872004 22 818 87 529 1 223 597 8 127 6182005 32 500 160 569 2 126 541 11 891 583Total 104 587 360 572 4 778 570 31 559 607


1997 11 364 142 458 341 487 285 6951998 24 542 218 514 479 501 249 6671999 27 593 219 447 469 557 417 6382000 45 511 320 500 856 481 1 134 6162001 28 607 248 460 687 476 1 590 6182002 38 579 209 459 665 448 2 011 5912003 16 375 106 585 356 478 1 119 6362004 33 606 236 475 878 495 2 623 6182005 28 500 115 496 235 502 654 627Total 256 539 2 004 481 5 472 484 10 480 618











male cases all ages



Philippinesb


Sri Lankabc






Singapore


Sri Lanka




Malaysia


Cambodia


DISCUSSION




1997 19 429 5441998 27 381 5561999 10 146 5962000 7 103 5922001 16 368 5622002 32 767 5472003 31 545 5612004 33 895 6142005 39 686 5812006 38 556 5812007 48 846 5932008 49 335 615

















None declared

Funding


Acknowledgements


References





























Original Research






METHODS






Notifi cation


Vector control




Data analysis







Ethics


RESULTS











Age group (years)

2005 2007



Total 14 032 (1000) 3289 8 287 (1000) 1806


3000

2500

2000

1500

1000

500


Months

Num

ber o

f cas

es 2007 2005












DISCUSSION





Year 2005 Year 2007









0

10

20

30

40

50

60

70

80

90

100Ja

n-05 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec

Jan-

06 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec

Jan-

07 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec


Month-Year

Dist

ribut

ion

of s

erot

ype







None declared

Funding

None

References




























Original Research





















RESULTS












Frequency ()




SexMale 568 (459)Female 669 (541)





Yes 561 (667)No 281 (333)










Pregnantdagger

Yes 61 17 213 11 (04ndash26)No 442 85 127 1










DISCUSSION







OR (95 CI)

Age (years)


10ndash17 1



65+ 57 (18ndash182)


Yesdagger 1

No 21 (134ndash33)


Nodagger 1

Yes 27 (13ndash57)

Morbid obesity

Nodagger 1

Yes 19 (14ndash36)



10

08

06

04

02

0000 02 04 06 08 10


Sens

itivi

ty

ROC Curve












None declared

Funding

None













References






















Frequency









bull le5 references





































Original Research









References





Peer Review Process


Authorship


Abull Study design


bull Data analysis









Licence












Corrections











male cases all ages



Philippinesb


Sri Lankabc






Singapore


Sri Lanka




Malaysia


Cambodia


DISCUSSION




1997 19 429 5441998 27 381 5561999 10 146 5962000 7 103 5922001 16 368 5622002 32 767 5472003 31 545 5612004 33 895 6142005 39 686 5812006 38 556 5812007 48 846 5932008 49 335 615

















None declared

Funding


Acknowledgements


References





























Original Research






METHODS






Notifi cation


Vector control




Data analysis







Ethics


RESULTS











Age group (years)

2005 2007



Total 14 032 (1000) 3289 8 287 (1000) 1806


3000

2500

2000

1500

1000

500


Months

Num

ber o

f cas

es 2007 2005












DISCUSSION





Year 2005 Year 2007









0

10

20

30

40

50

60

70

80

90

100Ja

n-05 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec

Jan-

06 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec

Jan-

07 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec


Month-Year

Dist

ribut

ion

of s

erot

ype







None declared

Funding

None

References




























Original Research





















RESULTS












Frequency ()




SexMale 568 (459)Female 669 (541)





Yes 561 (667)No 281 (333)










Pregnantdagger

Yes 61 17 213 11 (04ndash26)No 442 85 127 1










DISCUSSION







OR (95 CI)

Age (years)


10ndash17 1



65+ 57 (18ndash182)


Yesdagger 1

No 21 (134ndash33)


Nodagger 1

Yes 27 (13ndash57)

Morbid obesity

Nodagger 1

Yes 19 (14ndash36)



10

08

06

04

02

0000 02 04 06 08 10


Sens

itivi

ty

ROC Curve












None declared

Funding

None













References






















Frequency









bull le5 references





































Original Research









References





Peer Review Process


Authorship


Abull Study design


bull Data analysis









Licence












Corrections






Singapore


Sri Lanka




Malaysia


Cambodia


DISCUSSION




1997 19 429 5441998 27 381 5561999 10 146 5962000 7 103 5922001 16 368 5622002 32 767 5472003 31 545 5612004 33 895 6142005 39 686 5812006 38 556 5812007 48 846 5932008 49 335 615

















None declared

Funding


Acknowledgements


References





























Original Research






METHODS






Notifi cation


Vector control




Data analysis







Ethics


RESULTS











Age group (years)

2005 2007



Total 14 032 (1000) 3289 8 287 (1000) 1806


3000

2500

2000

1500

1000

500


Months

Num

ber o

f cas

es 2007 2005












DISCUSSION





Year 2005 Year 2007









0

10

20

30

40

50

60

70

80

90

100Ja

n-05 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec

Jan-

06 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec

Jan-

07 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec


Month-Year

Dist

ribut

ion

of s

erot

ype







None declared

Funding

None

References




























Original Research





















RESULTS












Frequency ()




SexMale 568 (459)Female 669 (541)





Yes 561 (667)No 281 (333)










Pregnantdagger

Yes 61 17 213 11 (04ndash26)No 442 85 127 1










DISCUSSION







OR (95 CI)

Age (years)


10ndash17 1



65+ 57 (18ndash182)


Yesdagger 1

No 21 (134ndash33)


Nodagger 1

Yes 27 (13ndash57)

Morbid obesity

Nodagger 1

Yes 19 (14ndash36)



10

08

06

04

02

0000 02 04 06 08 10


Sens

itivi

ty

ROC Curve












None declared

Funding

None













References






















Frequency









bull le5 references





































Original Research









References





Peer Review Process


Authorship


Abull Study design


bull Data analysis









Licence












Corrections
















None declared

Funding


Acknowledgements


References





























Original Research






METHODS






Notifi cation


Vector control




Data analysis







Ethics


RESULTS











Age group (years)

2005 2007



Total 14 032 (1000) 3289 8 287 (1000) 1806


3000

2500

2000

1500

1000

500


Months

Num

ber o

f cas

es 2007 2005












DISCUSSION





Year 2005 Year 2007









0

10

20

30

40

50

60

70

80

90

100Ja

n-05 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec

Jan-

06 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec

Jan-

07 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec


Month-Year

Dist

ribut

ion

of s

erot

ype







None declared

Funding

None

References




























Original Research





















RESULTS












Frequency ()




SexMale 568 (459)Female 669 (541)





Yes 561 (667)No 281 (333)










Pregnantdagger

Yes 61 17 213 11 (04ndash26)No 442 85 127 1










DISCUSSION







OR (95 CI)

Age (years)


10ndash17 1



65+ 57 (18ndash182)


Yesdagger 1

No 21 (134ndash33)


Nodagger 1

Yes 27 (13ndash57)

Morbid obesity

Nodagger 1

Yes 19 (14ndash36)



10

08

06

04

02

0000 02 04 06 08 10


Sens

itivi

ty

ROC Curve












None declared

Funding

None













References






















Frequency









bull le5 references





































Original Research









References





Peer Review Process


Authorship


Abull Study design


bull Data analysis









Licence












Corrections








None declared

Funding


Acknowledgements


References





























Original Research






METHODS






Notifi cation


Vector control




Data analysis







Ethics


RESULTS











Age group (years)

2005 2007



Total 14 032 (1000) 3289 8 287 (1000) 1806


3000

2500

2000

1500

1000

500


Months

Num

ber o

f cas

es 2007 2005












DISCUSSION





Year 2005 Year 2007









0

10

20

30

40

50

60

70

80

90

100Ja

n-05 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec

Jan-

06 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec

Jan-

07 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec


Month-Year

Dist

ribut

ion

of s

erot

ype







None declared

Funding

None

References




























Original Research





















RESULTS












Frequency ()




SexMale 568 (459)Female 669 (541)





Yes 561 (667)No 281 (333)










Pregnantdagger

Yes 61 17 213 11 (04ndash26)No 442 85 127 1










DISCUSSION







OR (95 CI)

Age (years)


10ndash17 1



65+ 57 (18ndash182)


Yesdagger 1

No 21 (134ndash33)


Nodagger 1

Yes 27 (13ndash57)

Morbid obesity

Nodagger 1

Yes 19 (14ndash36)



10

08

06

04

02

0000 02 04 06 08 10


Sens

itivi

ty

ROC Curve












None declared

Funding

None













References






















Frequency









bull le5 references





































Original Research









References





Peer Review Process


Authorship


Abull Study design


bull Data analysis









Licence












Corrections












Original Research






METHODS






Notifi cation


Vector control




Data analysis







Ethics


RESULTS











Age group (years)

2005 2007



Total 14 032 (1000) 3289 8 287 (1000) 1806


3000

2500

2000

1500

1000

500


Months

Num

ber o

f cas

es 2007 2005












DISCUSSION





Year 2005 Year 2007









0

10

20

30

40

50

60

70

80

90

100Ja

n-05 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec

Jan-

06 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec

Jan-

07 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec


Month-Year

Dist

ribut

ion

of s

erot

ype







None declared

Funding

None

References




























Original Research





















RESULTS












Frequency ()




SexMale 568 (459)Female 669 (541)





Yes 561 (667)No 281 (333)










Pregnantdagger

Yes 61 17 213 11 (04ndash26)No 442 85 127 1










DISCUSSION







OR (95 CI)

Age (years)


10ndash17 1



65+ 57 (18ndash182)


Yesdagger 1

No 21 (134ndash33)


Nodagger 1

Yes 27 (13ndash57)

Morbid obesity

Nodagger 1

Yes 19 (14ndash36)



10

08

06

04

02

0000 02 04 06 08 10


Sens

itivi

ty

ROC Curve












None declared

Funding

None













References






















Frequency









bull le5 references





































Original Research









References





Peer Review Process


Authorship


Abull Study design


bull Data analysis









Licence












Corrections






Notifi cation


Vector control




Data analysis







Ethics


RESULTS











Age group (years)

2005 2007



Total 14 032 (1000) 3289 8 287 (1000) 1806


3000

2500

2000

1500

1000

500


Months

Num

ber o

f cas

es 2007 2005












DISCUSSION





Year 2005 Year 2007









0

10

20

30

40

50

60

70

80

90

100Ja

n-05 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec

Jan-

06 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec

Jan-

07 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec


Month-Year

Dist

ribut

ion

of s

erot

ype







None declared

Funding

None

References




























Original Research





















RESULTS












Frequency ()




SexMale 568 (459)Female 669 (541)





Yes 561 (667)No 281 (333)










Pregnantdagger

Yes 61 17 213 11 (04ndash26)No 442 85 127 1










DISCUSSION







OR (95 CI)

Age (years)


10ndash17 1



65+ 57 (18ndash182)


Yesdagger 1

No 21 (134ndash33)


Nodagger 1

Yes 27 (13ndash57)

Morbid obesity

Nodagger 1

Yes 19 (14ndash36)



10

08

06

04

02

0000 02 04 06 08 10


Sens

itivi

ty

ROC Curve












None declared

Funding

None













References






















Frequency









bull le5 references





































Original Research









References





Peer Review Process


Authorship


Abull Study design


bull Data analysis









Licence












Corrections











Age group (years)

2005 2007



Total 14 032 (1000) 3289 8 287 (1000) 1806


3000

2500

2000

1500

1000

500


Months

Num

ber o

f cas

es 2007 2005












DISCUSSION





Year 2005 Year 2007









0

10

20

30

40

50

60

70

80

90

100Ja

n-05 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec

Jan-

06 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec

Jan-

07 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec


Month-Year

Dist

ribut

ion

of s

erot

ype







None declared

Funding

None

References




























Original Research





















RESULTS












Frequency ()




SexMale 568 (459)Female 669 (541)





Yes 561 (667)No 281 (333)










Pregnantdagger

Yes 61 17 213 11 (04ndash26)No 442 85 127 1










DISCUSSION







OR (95 CI)

Age (years)


10ndash17 1



65+ 57 (18ndash182)


Yesdagger 1

No 21 (134ndash33)


Nodagger 1

Yes 27 (13ndash57)

Morbid obesity

Nodagger 1

Yes 19 (14ndash36)



10

08

06

04

02

0000 02 04 06 08 10


Sens

itivi

ty

ROC Curve












None declared

Funding

None













References






















Frequency









bull le5 references





































Original Research









References





Peer Review Process


Authorship


Abull Study design


bull Data analysis









Licence












Corrections














DISCUSSION





Year 2005 Year 2007









0

10

20

30

40

50

60

70

80

90

100Ja

n-05 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec

Jan-

06 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec

Jan-

07 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec


Month-Year

Dist

ribut

ion

of s

erot

ype







None declared

Funding

None

References




























Original Research





















RESULTS












Frequency ()




SexMale 568 (459)Female 669 (541)





Yes 561 (667)No 281 (333)










Pregnantdagger

Yes 61 17 213 11 (04ndash26)No 442 85 127 1










DISCUSSION







OR (95 CI)

Age (years)


10ndash17 1



65+ 57 (18ndash182)


Yesdagger 1

No 21 (134ndash33)


Nodagger 1

Yes 27 (13ndash57)

Morbid obesity

Nodagger 1

Yes 19 (14ndash36)



10

08

06

04

02

0000 02 04 06 08 10


Sens

itivi

ty

ROC Curve












None declared

Funding

None













References






















Frequency









bull le5 references





































Original Research









References





Peer Review Process


Authorship


Abull Study design


bull Data analysis









Licence












Corrections











0

10

20

30

40

50

60

70

80

90

100Ja

n-05 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec

Jan-

06 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec

Jan-

07 Feb

Mar

Apr

May Jun

Jul

Aug Se

p

Oct

Nov Dec


Month-Year

Dist

ribut

ion

of s

erot

ype







None declared

Funding

None

References




























Original Research





















RESULTS












Frequency ()




SexMale 568 (459)Female 669 (541)





Yes 561 (667)No 281 (333)










Pregnantdagger

Yes 61 17 213 11 (04ndash26)No 442 85 127 1










DISCUSSION







OR (95 CI)

Age (years)


10ndash17 1



65+ 57 (18ndash182)


Yesdagger 1

No 21 (134ndash33)


Nodagger 1

Yes 27 (13ndash57)

Morbid obesity

Nodagger 1

Yes 19 (14ndash36)



10

08

06

04

02

0000 02 04 06 08 10


Sens

itivi

ty

ROC Curve












None declared

Funding

None













References






















Frequency









bull le5 references





































Original Research









References





Peer Review Process


Authorship


Abull Study design


bull Data analysis









Licence












Corrections









None declared

Funding

None

References




























Original Research





















RESULTS












Frequency ()




SexMale 568 (459)Female 669 (541)





Yes 561 (667)No 281 (333)










Pregnantdagger

Yes 61 17 213 11 (04ndash26)No 442 85 127 1










DISCUSSION







OR (95 CI)

Age (years)


10ndash17 1



65+ 57 (18ndash182)


Yesdagger 1

No 21 (134ndash33)


Nodagger 1

Yes 27 (13ndash57)

Morbid obesity

Nodagger 1

Yes 19 (14ndash36)



10

08

06

04

02

0000 02 04 06 08 10


Sens

itivi

ty

ROC Curve












None declared

Funding

None













References






















Frequency









bull le5 references





































Original Research









References





Peer Review Process


Authorship


Abull Study design


bull Data analysis









Licence












Corrections








Original Research





















RESULTS












Frequency ()




SexMale 568 (459)Female 669 (541)





Yes 561 (667)No 281 (333)










Pregnantdagger

Yes 61 17 213 11 (04ndash26)No 442 85 127 1










DISCUSSION







OR (95 CI)

Age (years)


10ndash17 1



65+ 57 (18ndash182)


Yesdagger 1

No 21 (134ndash33)


Nodagger 1

Yes 27 (13ndash57)

Morbid obesity

Nodagger 1

Yes 19 (14ndash36)



10

08

06

04

02

0000 02 04 06 08 10


Sens

itivi

ty

ROC Curve












None declared

Funding

None













References






















Frequency









bull le5 references





































Original Research









References





Peer Review Process


Authorship


Abull Study design


bull Data analysis









Licence












Corrections














RESULTS












Frequency ()




SexMale 568 (459)Female 669 (541)





Yes 561 (667)No 281 (333)










Pregnantdagger

Yes 61 17 213 11 (04ndash26)No 442 85 127 1










DISCUSSION







OR (95 CI)

Age (years)


10ndash17 1



65+ 57 (18ndash182)


Yesdagger 1

No 21 (134ndash33)


Nodagger 1

Yes 27 (13ndash57)

Morbid obesity

Nodagger 1

Yes 19 (14ndash36)



10

08

06

04

02

0000 02 04 06 08 10


Sens

itivi

ty

ROC Curve












None declared

Funding

None













References






















Frequency









bull le5 references





































Original Research









References





Peer Review Process


Authorship


Abull Study design


bull Data analysis









Licence












Corrections









Frequency ()




SexMale 568 (459)Female 669 (541)





Yes 561 (667)No 281 (333)










Pregnantdagger

Yes 61 17 213 11 (04ndash26)No 442 85 127 1










DISCUSSION







OR (95 CI)

Age (years)


10ndash17 1



65+ 57 (18ndash182)


Yesdagger 1

No 21 (134ndash33)


Nodagger 1

Yes 27 (13ndash57)

Morbid obesity

Nodagger 1

Yes 19 (14ndash36)



10

08

06

04

02

0000 02 04 06 08 10


Sens

itivi

ty

ROC Curve












None declared

Funding

None













References






















Frequency









bull le5 references





































Original Research









References





Peer Review Process


Authorship


Abull Study design


bull Data analysis









Licence












Corrections






DISCUSSION







OR (95 CI)

Age (years)


10ndash17 1



65+ 57 (18ndash182)


Yesdagger 1

No 21 (134ndash33)


Nodagger 1

Yes 27 (13ndash57)

Morbid obesity

Nodagger 1

Yes 19 (14ndash36)



10

08

06

04

02

0000 02 04 06 08 10


Sens

itivi

ty

ROC Curve












None declared

Funding

None













References






















Frequency









bull le5 references





































Original Research









References





Peer Review Process


Authorship


Abull Study design


bull Data analysis









Licence












Corrections














None declared

Funding

None













References






















Frequency









bull le5 references





































Original Research









References





Peer Review Process


Authorship


Abull Study design


bull Data analysis









Licence












Corrections















References






















Frequency









bull le5 references





































Original Research









References





Peer Review Process


Authorship


Abull Study design


bull Data analysis









Licence












Corrections













Frequency









bull le5 references





































Original Research









References





Peer Review Process


Authorship


Abull Study design


bull Data analysis









Licence












Corrections





Original Research









References





Peer Review Process


Authorship


Abull Study design


bull Data analysis









Licence












Corrections


