Published January 1, 2025 | Version 1.0

Tanzania Climate-Sensitive Waterborne Diseases Dataset for Predictive Machine Learning: A Comprehensive Five-Year Analysis of Health, Infrastructure, and Weather Data (2019–2023)

Description

This dataset presents comprehensive field and environmental data collected from five districts in Tanzania, referred to as District 1, District 2, District 3, District 4, and District 5, over a five-year period (2019–2023). The dataset includes information on critical public infrastructure such as water sources, toilet quality, health facility locations, and waste management facilities. Additionally, data on waterborne disease cases were recorded, covering Typhoid fever, Amoebiasis/dysentery, Diarrhea (categorized by severity: no dehydration, some dehydration, and severe dehydration), Schistosomiasis, and intestinal worms. Complementary weather data with monthly frequency for the same five-year period was sourced from Copernicus.

The dataset underwent rigorous preprocessing, cleaning, and formatting to ensure usability and consistency. Each data point, such as a water source, was expanded to include a minimum of 60 entries to align with weather conditions over the 60 months. Furthermore, all location-revealing data has been anonymized to maintain privacy. This dataset provides a valuable resource for public health analysis and research on the relationships between infrastructure, environmental conditions, and health outcomes in Tanzania.

Files

climate_data_embedde_District_1_Water_sources_data_MP_transformed.csv

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Additional details

Funding

Wellcome Trust
Lacuna Fund: Machine Learning Datasets for More Equitable Health Outcomes 228079

Dates

Available
2025-01-01