4.2 Article

The COVID-19 Mortality Rate Is Associated with Illiteracy, Age, and Air Pollution in Urban Neighborhoods: A Spatiotemporal Cross-Sectional Analysis

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MDPI
DOI: 10.3390/tropicalmed8020085

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spatiotemporal analysis; socio-economic; determinants; air quality; COVID-19 mortality; air pollution

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This research examines the COVID-19 mortality rates and their geographical association with various socioeconomic and ecological determinants in 350 neighborhoods in Tehran. The study finds that the downtown and northern areas of the city are significantly clustered in terms of high-risk areas for COVID-19 mortality. Factors such as air pollutant factors, socioeconomic status, built environment factors, and public transportation infrastructure are found to be correlated with the mortality rate.
There are different area-based factors affecting the COVID-19 mortality rate in urban areas. This research aims to examine COVID-19 mortality rates and their geographical association with various socioeconomic and ecological determinants in 350 of Tehran's neighborhoods as a big city. All deaths related to COVID-19 are included from December 2019 to July 2021. Spatial techniques, such as Kulldorff's SatScan, geographically weighted regression (GWR), and multi-scale GWR (MGWR), were used to investigate the spatially varying correlations between COVID-19 mortality rates and predictors, including air pollutant factors, socioeconomic status, built environment factors, and public transportation infrastructure. The city's downtown and northern areas were found to be significantly clustered in terms of spatial and temporal high-risk areas for COVID-19 mortality. The MGWR regression model outperformed the OLS and GWR regression models with an adjusted R-2 of 0.67. Furthermore, the mortality rate was found to be associated with air quality (e.g., NO2, PM10, and O-3); as air pollution increased, so did mortality. Additionally, the aging and illiteracy rates of urban neighborhoods were positively associated with COVID-19 mortality rates. Our approach in this study could be implemented to study potential associations of area-based factors with other emerging infectious diseases worldwide.

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