Predicting potential areas at risk of the Dengue Hemorrhagic Fever in Jakarta, Indonesia—analyzing the accuracy of predictive hot spot analysis in the absence of small geographical area data

Predicting potential areas at risk of the Dengue Hemorrhagic Fever in Jakarta, Indonesia—analyzing the accuracy of predictive hot spot analysis in the absence of small geographical area data

ABSTRACTDengue Hemorrhagic Fever (DHF), a more severe form of dengue, is one of the most rapidly spreading mosquito-borne diseases in the world. This study is motivated by the rising DHF incidence in Jakarta, the capital city of Indonesia. We mainly utilized hot spot analysis, which employs spatial...

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Bibliographic Details
Main Authors: Valentino Prasetya, Valentino Vito, Ivan N. Tanawi, Dipo Aldila, Gatot F. Hertono
Format: Article
Language:English
Published: Taylor & Francis Group 2023-12-01
Series:Infection Ecology & Epidemiology
Subjects:
Getis-Ord Gi
hot spot analysis
machine learning
small area estimation
support vector regression
Online Access:https://www.tandfonline.com/doi/10.1080/20008686.2023.2218207

Internet

https://www.tandfonline.com/doi/10.1080/20008686.2023.2218207

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