Improving dengue fever predictions in Taiwan based on feature selection and random forests.

ABSTRACT:

Background

Dengue fever is a well-studied vector-borne disease in tropical and subtropical areas of the world. Several methods for predicting the occurrence of dengue fever in Taiwan have been proposed. However, to the best of our knowledge, no study has investigated the relationship between air quality indices (AQIs) and dengue fever in Taiwan.

Results

This study aimed to develop a dengue fever prediction model in which meteorological factors, a vector index, and AQIs were incorporated into different machine learning algorithms. A total of 805 meteorological records from 2013 to 2015 were collected from government open-source data after preprocessing. In addition to well-known dengue-related factors, we investigated the effects of novel variables, including particulate matt

SUBMITTER: Kuo CY 

PROVIDER: S-EPMC10953060 | biostudies-literature | 2024 Mar

REPOSITORIES: biostudies-literature