STOCHASTIC AND DETERMINISTIC DYNAMIC MODEL OF DENGUE TRANSMISSION BASED ON DENGUE INCIDENCE DATA AND CLIMATE FACTORS IN BANDUNG CITY - Pimpi, La
Indonesia is a country in the tropics, area of distribution and endemic area of dengue. The death rate caused by dengue is relatively high in Indonesia. Therefore, the health authority must prioritize preventing and controlling dengue disease for a long-term policy. This study proposes a method based on dynamic climate variables to estimate the proportion of infected humans and mosquitoes. This study integrates external factors (dynamic climate factors) with dynamic models of dengue transmission. The focus of this research is to investigate the incidence of dengue in Bandung City, one of the big cities in Indonesia that is classified as endemic dengue. In this study, the Poisson regression method is applied, which involves dynamic climate variables to estimate the average infected human population. Furthermore, using a deterministic and stochastic model approach, this estimation result is the basis for estimating the proportion of infected humans and the proportion of infected mosquitoes. Finally, using the QSS (quasay steady state) method to approximate the proportion of mosquitoes infected with dengue. The primary reproduction number and the adequate reproduction number are also found here. It was also found that the proportion of mosquitoes infected with dengue was smaller than that of infected humans. However, the population of infected mosquitoes was more significant than that of infected humans. The simulation results show that the stochastic approach is able to provide more information in modeling dengue incidence data than the deterministic approach, especially in providing confidence intervals for dengue occurrence per unit time. Therefore, dengue transmission can be reduced by controlling the abundance of mosquito populations, considering climate conditions and the historical number of infected humans.