Spatial analysis of dengue hemorrhagic fever in Talaud Islands regency

Abstract

Background: The number of dengue hemorrhagic fever (DHF) cases in Indonesia from January to February 2016 was 8,487 with 108 deaths. DHF is an infectious disease that continues to increase from 2014 until 2016 in Manado city. DHF cases in Talaud Islands Regency from 2014 to 2016 were 143 cases. Regional spatial analysis would simplify the distribution of DHF cases in high-risk areas. To be aware of the DHF outbreak cycle, it is necessary to model spatial risk factors based on geographic information systems (GIS) to tackle and eradicate DHF cases by region.Methods: This study aimed to analyze the spread of DHF in Talaud regency based on age, sex, population density and area height. The design of this research is qualitative analytic by using an ecological study approach. The research scope was 19 districts in Talaud regency. Secondary data are used which consists of case number, age, sex, population density, and area height taken from the Talaud district health office with 66 DHF cases in 2018-2019 and analyzed using the GIS approach through spatial analysis.Results: Based on the number of DHF cases that is most in the age group of 5-11 years. Male gender is more likely to suffer from DHF than female. Spatial description of the condition of the altitude in the Talaud Islands regency at risk of suffering from DHF is>50 meters above sea level. Spatial description of population density with most DHF cases is not densely populated area with less than 1,620 inhabitants per km.Conclusions: The health office of Talaud islands regency needs to actively promote health by providing information about eradicating mosquitoes.

Spatial Analysis of Dengue Hemorrhagic Fever in East Manggarai, Indonesia: A Case Study

“…Spatial analysis using regional risk factor modeling will facilitate the control and management of dengue cases, especially in the distribution of dengue cases in high-risk areas. Spatial analysis based on Geographic Information Systems (GIS) can be used to be aware of potential outbreaks per region (Mandagi, Kalesaran and Kolibu, 2021). A study in Nepal by Acharya et al using the SATsan application showed that the spread of DHF was not random but clustered in space and time in the Chitwan and Jhapa areas (Acharya et al, 2016).…”