Machine learning and spatio-temporal analysis of meteorological factors on waterborne diseases in Bangladesh

The findings from the study, incorporating the One Health perspective, provide insights for planning early warning, prevention, and control strategies to combat waterborne diseases in Bangladesh and similar endemic countries. Precautionary measures and intensified surveillance need to be implemented in certain high-risk districts for waterborne diseases across the country.

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Publication Details

Journal
PLoS neglected tropical diseases
Published
2025-01-16
DOI
https://doi.org/10.1371/journal.pntd.0012800
Citations
5
Primary Topic
COVID-19 epidemiological studies
Type
article
Field-Weighted Citation Impact
6.84
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article

Machine learning and spatio-temporal analysis of meteorological factors on waterborne diseases in Bangladesh

Arman Hossain Chowdhury, Md. Siddikur Rahman
5 citations
PLoS neglected tropical diseases
COVID-19 epidemiological studies
6.84
article

Machine learning and spatio-temporal analysis of meteorological factors on waterborne diseases in Bangladesh

Arman Hossain Chowdhury, Md. Siddikur Rahman
article en
5 citations

Abstract

The findings from the study, incorporating the One Health perspective, provide insights for planning early warning, prevention, and control strategies to combat waterborne diseases in Bangladesh and similar endemic countries. Precautionary measures and intensified surveillance need to be implemented in certain high-risk districts for waterborne diseases across the country.

PLoS neglected tropical diseasesVol. 19(1)
Begum Rokeya University (BD)
Openalex Percentile: Top 3%
COVID-19 epidemiological studies
6.84
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