Modeling Dynamic System for Prediction of Dengue Hemorrhagic Fever in Maros District

Abstract

BACKGROUND: Efforts to control the incidence of dengue hemorrhagic fever (DHF) have been carried out intensively, however, there is no significant reduction in the number of DHF sufferers. Meanwhile, the predictive model is expected to be an early warning to anticipate the incidence of DHF. AIM: Therefore, this study aims to determine the dynamic model for predicting dengue fever incidence in Maros Regency from 2020 to 2040. METHODS: This study used the research and development (R and D) method with a dynamic systems approach. The study was conducted in Maros Regency and the data on dengue cases in Maros Regency from 2014 to 2018 were used as samples. Meanwhile, interpretive structural modeling (ISM) was used to determine policy scenarios in reducing dengue cases while the analysis of the dynamic model of dengue fever was conducted using the Powersim program. RESULTS: The critical elements of DHF prevention in the Maros Regency include the Jumantik program, 3M Plus, early warning systems, and outreach. Furthermore, the prediction of the average incidence of dengue fever from 2020 to 2040 has decreased based on dynamic model simulations by applying the Jumantik scenario (46.8%), 3M Plus (61.17%), early warning systems (74.4%), counseling (52.12%), and the combined scenario (97.87%). CONCLUSIONS: The incidence of dengue fever in the Maros Regency is prevented and controlled by the combination of the Jumantik program, 3M Plus, early warning systems, and counseling.

Mathematical Models of Dengue Transmission Dynamics With Vaccination and Wolbachia Parameters and Seasonal Aspects

“…Mathematical models can be used to simulate various vector control strategies and analyze their impact on disease transmission. DHF tends to show seasonal variability in its distribution [11]. Aedes mosquitoes tend to reproduce and become more active during particular seasons [8].…”