Fine-scale predictive modeling of Aedes mosquito abundance and dengue risk indicators using machine learning algorithms with microclimatic variables

Abstract Effective prediction of Aedes mosquito abundance and dengue risk indicators such as the Aedes Index (AI) and Dengue Positive Trap Index (DPTI) is essential for early intervention and targeted vector control. However, current models often rely on coarse regional data and fail to account for...

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Detalhes bibliográficos

Principais autores:	Nazri Che Dom, Nur Athen Mohd Hardy Abdullah, Rahmat Dapari, Siti Aekbal Salleh
Formato:	Artigo
Idioma:	Inglês
Publicado em:	Nature Portfolio 2025-10-01
coleção:	Scientific Reports
Assuntos:	Dengue Aedes mosquito Predictive modeling Machine learning Microclimate Risk mapping
Acesso em linha:	https://doi.org/10.1038/s41598-025-17191-y
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