Socioeconomic and Climatic determinants of COVID-19 in the health regions of Eastern Northeast Brazil

Abstract

The COVID-19 pandemic significantly impacted Brazil, amplifying existing socioeconomic disparities and social vulnerabilities, particularly in the State of Alagoas, located in Eastern Northeast Brazil (ENEB). This study evaluated the climatic, environmental, and socioeconomic effects attributed to COVID-19 across the Health Regions (HR) of Alagoas. Daily data on COVID-19 cases and deaths from the 10 h were sourced from DATASUS through the Unified Health System (SUS) for the period from March 2020 to January 2023. Both datasets underwent descriptive statistical analysis, with the Spline method, Principal Component Analysis (PCA), and Case Fatality Rate (CFR %) calculations employed for deeper insights. The resulting data were visualized on Maps using QGIS version 3.16. Climatic data included air temperature (T), wind speed (Ws), water vapor pressure (e), rainfall (Pcp), and reference evapotranspiration (ETo), obtained from the TerraClimate platform on a monthly scale. Socioeconomic and demographic data consisted of population density; municipal Human Development Index (HDI); Lack of Bathroom Facilities (or toilet); illiteracy rate; Low-Income; coverage of the Family Health Strategy, Gini index, SUS establishments, urbanized area, and monthly income per capita of up to 1/2 minimum wage from IBGE (2010 census) and the Basic Guide of SUS for Alagoas (2017). All data were subjected to a correlation matrix, adopting the Spearman correlation coefficient (ρ) with a significance level (p-value < 0.05) for analysis and implemented using the Python language. The results show differences in COVID-19 among the HR. There is a direct and highly significant relationship between social, economic, and demographic determinants and the COVID-19 pandemic, unlike climatic variables, which showed specific correlations in some HR. Regarding socioeconomic and demographic relational patterns, lack of bathrooms, HDI, SUS facilities, population density, and urban area stand out, with high positive and monotonic Spearman correlations. Regarding climatic relational patterns, T, ETo, and e stand out, particularly in the 4th and 7th HR, with the exception of the 3rd HR (Ws). The study's results indicate that improvements in terms of governance and public management are necessary post-pandemic.

Keywords: COVID-19; Climate; Health; Social indicators; Social vulnerability.