Fine Scale Modeling for Potential Distribution of Dengue Fever in Tampan District, Indonesia

Abstract

Larvisiding is one common way used to reduce mosquito density in breeding areas before metamorphosizing into adults. Despite numerous eradication efforts, the outcomes have not met expectations, leading to additional issues such as environmental pollution in urban areas. In the context of dengue hemorrhagic fever (DHF), addressing the challenge of mitigating the endemic outbreak entails formulating an effective strategy through a vector eradication approach. Therefore, this study explored the spatial pattern of DHF and estimated the potential spread of outbreaks. A geographic information system approach, with nearest neighbor analysis and kernel density estimation (KDE), was used to generate information regarding the pattern and potential for transmission of Aedes aegypti mosquitoes. The results showed that in 2019, a random pattern was observed, while in 2020, a clustered pattern of virus spread occurred. Furthermore, in terms of the potential transmission, an exposed zone of 9.73 km² was identified in 2019, and this increased to 15.72 km² in 2020. In this study, several important actions were implemented with a spatial approach, enabling the detection and polarization of events. However, the limitations included not being comprehensive in addressing the hygiene, sanitation, drainage, and population density aspects.

Keywords

• epidemic
• kernel-density estimation
• neighboring algorithm
• surveillance
• tampan district