Present and Future Distribution Model using MaxEnt: A Risk Map for Dengue Haemorrhagic Fever based on Aedes aegypti Mosquitoes Distribution in Malang Region, East Java, Indonesia - Zulfaidah Penata Gama; Bagyo Yanuwiadi; Puji Rahayu; Rafi Jauhar Khalil; Miftah Farid Assiddiqy; Muhammad Asyraf Rijalullah; Nia Kurniawan (Journal of Tropical Biodiversity and Biotechnology, 2025)
The prevalence of Dengue Haemorrhagic Fever (DHF), a disease prevalent in countries with tropical and sub-tropical climates, including Indonesia, has exhibited a notable increase over the past two decades. A study case of a region experiencing this surge is Malang Region, which situated in East Java. The transmission of DHF within individual human is facilitated by the existence of Ae. aegypti, which serves as one of the intermediate vector mosquitoes. MaxEnt modelling was employed to analyse the niche and distribution of Ae. aegypti. The results of this study demonstrated that the integration of environmental and anthropogenic variables in a combination model provided  more comprehensive approach for comprehending the niche and distribution patterns of Ae. aegypti compared to relying only regarding a climatic model. Areas characterised by higher temperatures, high population density, and limited vegetation cover possess the inherent capacity to serve as suitable habitats for Ae. aegypti. According to the modelling results, the distribution of Ae. aegypti in Malang region currently encompasses approximately 14.5 % (545.5 km2) of the total area. It is projected that this distribution can potentially expand to 15.5 % (568.9 km2) by the year 2040. Several sub-districts, namely Klojen, Blimbing, Sukun, Lowokwaru, Kedungkandang, Pakisaji, and Kepanjen, have been classified as high-risk areas that require special concern. The combination model of environmental variables and anthropogenic variables provide more comprehensive approach to understand the niche and the distribution patterns of Ae. aegypti in Malang Region compared to relying solely on climate models.