EarlyWarning System (EWS) for Dengue in Indonesia and Thailand

ABSTRACT Mohammad Juffrie, Dana A. Focks - Early Warning Systems (EWS) for Dengue in Indonesia and Thailand Background: Dengue virus infection is an acute febrile disease caused by 4 sero-type viruses. The transmission via mosquito vector Ae. Aegypti. The morbidity of dengue virus infection is quite high and the mortality below 5%. The most dangerous form is dengue shock syndrome, the mortality is very high. The effort to reduce morbidity and mortality is improvement of the clinical management and control of vector. Today, most dengue control efforts are based on suppression of Aedes aegypti (L.) and not eradication. EWS would provide significant utility where mitigation methods were available. EWSs were possible for three reasons, an extensive time series on the disease incidence the available, dengue being a vector-borne disease, is significantly influenced by weather, in many sub-regions of SE Asia, weather anomalies are significantly influenced by and lag behind several months, sea surface temperature (SST) anomalies. Methods: Analytic cross sectional study was conducted. The dependant variable in this analysis, Epi.yr. is dichotomous and indicates whether an epidemic occurred during a particular year. The two independent (predictor) variables are sea surface temperature anomalies as reported by the Japanese Meteorological Association (JMA) and previous cases. The monthly number of cases were dengue and DHF in Yogyakarta, Indonesia and the metropolitan area of Bangkok, Thailand. Results: Yogyakarta, many years were very near the epidemic cutoff of 278 cases, yet only one year, 1992 with 237 cases, was incorrectly labeled. The false positive in 1992, had a probability of 0.64 of epidemic and 0.36 of no epidemic. Bangkok, the best three-month prediction gave 6 false indication in 35 years, 5 false negatives, 1 false positive. For two month prediction, 3 errors in 35 years were made, 2 false negatives, 1 false positive. Conclusion: The results presented in this study is very use full for predicting the incidence of dengue virus infection using weather data. This method would only require a simple calculator, or preferably a PC using the derived equation. Key words: dengue -incidence -early warning -weather - probabilit

Skeeter Buster: A Stochastic, Spatially Explicit Modeling Tool for Studying Aedes aegypti Population Replacement and Population Suppression Strategies

Dengue is a viral disease that affects approximately 50 million people annually, and is estimated to result in 12,500 fatalities. Dengue viruses are vectored by mosquitoes, predominantly by the species Aedes aegypti. Because there is currently no vaccine or specific treatment, the only available strategy to reduce dengue transmission is to control the populations of these mosquitoes. This can be achieved by traditional approaches such as insecticides, or by recently developed genetic methods that propose the release of mosquitoes genetically engineered to be unable to transmit dengue viruses. The expected outcome of different control strategies can be compared by simulating the population dynamics and genetics of mosquitoes at a given location. Development of optimal control strategies can then be guided by the modeling approach. To that end, we introduce a new modeling tool called Skeeter Buster. This model describes the dynamics and the genetics of Ae. aegypti populations at a very fine scale, simulating the contents of individual houses, and even the individual water-holding containers in which mosquito larvae reside. Skeeter Buster can be used to compare the predicted outcomes of multiple control strategies, traditional or genetic, making it an important tool in the fight against dengue

Epidemiology of Dengue Virus in Iquitos, Peru 1999 to 2005: Interepidemic and Epidemic Patterns of Transmission

To develop prevention (including vaccines) and control programs for dengue fever, a significant mosquito-borne disease in the tropics, there is an urgent need for comprehensive long term field epidemiological studies. We report results from a study that monitored ∼2,400 school children and some adult family members for dengue infection at 6 month intervals from 1999 to 2005, in the Amazonian city of Iquitos, Peru. At enrollment, ∼80% of the participants had a previous infection with DENV serotypes 1 and 2 or both. During the first 15 months, about 3 new infections for every 100 participants were observed among the study participants. In 2001, DENV-3, a serotype not previously observed in the region, invaded Iquitos in a process characterized by 3 distinct periods: amplification over at least a 5–6 month period, replacement of previously circulating serotypes, and epidemic transmission when incidence peaked. Incidence patterns of new infections were geographically distinct from baseline prevalence rates prior to arrival of DENV-3, but closely mirrored them during the invasion. DENV transmission varied geographically corresponding to elevated mosquito densities. The invasion of a novel serotype is often characterized by 5–6 months of silent transmission before traditional surveillance programs detect the virus. This article sets the stage for subsequent publications on dengue epidemiology

EarlyWarning System (EWS) for Dengue in Indonesia and Thailand

Background: Dengue virus infection is an acute febrile disease caused by 4 sero-type viruses. The transmission via mosquito vector Ae. Aegypti. The morbidity of dengue virus infection is quite high and the mortality below 5%. The most dangerous form is dengue shock syndrome, the mortality is very high. The effort to reduce morbidity and mortality is improvement of the clinical management and control of vector. Today, most dengue control efforts are based on suppression of Aedes aegypti (L.) and not eradication. EWS would provide significant utility where mitigation methods were available. EWSs were possible for three reasons, an extensive time series on the disease incidence the available, dengue being a vector-borne disease, is significantly influenced by weather, in many sub-regions of SE Asia, weather anomalies are significantly influenced by and lag behind several months, sea surface temperature (SST) anomalies. Methods: Analytic cross sectional study was conducted. The dependant variable in this analysis, Epi.yr. is dichotomous and indicates whether an epidemic occurred during a particular year. The two independent (predictor) variables are sea surface temperature anomalies as reported by the Japanese Meteorological Association (JMA) and previous cases. The monthly number of cases were dengue and DHF in Yogyakarta, Indonesia and the metropolitan area of Bangkok, Thailand. Results: Yogyakarta, many years were very near the epidemic cutoff of 278 cases, yet only one year, 1992 with 237 cases, was incorrectly labeled. The false positive in 1992, had a probability of 0.64 of epidemic and 0.36 of no epidemic. Bangkok, the best three-month prediction gave 6 false indication in 35 years, 5 false negatives, 1 false positive. For two month prediction, 3 errors in 35 years were made, 2 false negatives, 1 false positive. Conclusion: The results presented in this study is very use full for predicting the incidence of dengue virus infection using weather data. This method would only require a simple calculator, or preferably a PC using the derived equation. Key words: dengue -incidence -early warning -weather - probabilit

Deterministic model for simulating the predation of Toxorhynchites rutilus rutilus on Aedes aegypti /

no.S-17