Monthly meteorological and respiratory disease data for Santarém, Pará, Brazilian Amazon (2008–2024)
Description
This dataset contains 204 monthly observations collected for Santarém, Pará, Brazilian Amazon, covering the period from January 2008 to December 2024. It was compiled to support the investigation of associations between meteorological conditions and respiratory disease morbidity and mortality in a tropical South American region. The dataset includes the following variables: month, year, monthly precipitation (mm), maximum temperature (°C), minimum temperature (°C), relative humidity (%), in-hospital mortality rate from respiratory diseases (%), and number of hospitalizations from respiratory diseases. All variables are aggregated as monthly means or totals. Meteorological data were obtained from two sources: the Aeronautical Meteorology Network (REDEMET), station at Santarém International Airport, and the Meteorological Database for Teaching and Research (BDMEP) of the National Institute of Meteorology (INMET). Health data were extracted from the Hospital Information System (SIH) of Brazil's Unified Health System (SUS), maintained by the Ministry of Health. Records correspond to residents of Santarém and cover all respiratory disease categories under Chapter X of the International Classification of Diseases, 10th revision (ICD-10). This dataset may be used to reproduce the cross-correlation, principal component, and random forest analyses reported in the associated manuscript. It may also serve as a reference for future studies on climate-health relationships in the Brazilian Amazon.
Files
Steps to reproduce
Monthly meteorological data were obtained from two sources: the Aeronautical Meteorology Network (REDEMET), station at Santarém International Airport, and the Meteorological Database for Teaching and Research (BDMEP) of the National Institute of Meteorology (INMET). Variables include monthly precipitation (mm), maximum temperature (°C), minimum temperature (°C), and relative humidity (%). Hospitalization and mortality data were extracted from the Hospital Information System (SIH) of Brazil's Unified Health System (SUS), accessed via the DATASUS platform (http://tabnet.datasus.gov.br/). Records were filtered by place of residence (Santarém, Pará) and restricted to respiratory diseases under Chapter X of ICD-10. All variables were aggregated into monthly means or totals. Statistical analyses were performed in Python, applying cross-correlation analysis, principal component analysis with regression, and random forest modelling.
Institutions
- Universidade Federal de Santa MariaRio Grande do Sul, Santa Maria
- Instituto Nacional de Pesquisas EspaciaisSão Paulo, São José dos Campos