EarlyWarning System (EWS) for Dengue in Indonesia and Thailand
Mohammad Juffrie, Dana A. Focks Dana A. Focks(1*)
(1) 
(*) Corresponding Author
Abstract
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 - probability
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 - probability
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Copyright (c) 2015 Mohammad Juffrie, Dana A. Focks Dana A. Focks
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