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

Abstract

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 R² of 0.67. Furthermore, the mortality rate was found to be associated with air quality (e.g., NO₂, PM₁₀, and O₃); 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.

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

Figure 1

Map of Tehran, Iran, showing the spatial distribution of COVID-19 mortality 2019–2021; EBS = empirical Bayes smoothed mortality rates per 100,000 population at the neighbourhood level. Numbers indicate the administrative district division of the city. Each district includes some neighbourhoods.

Figure 2

Spatial distributions for selected explanatory variables in Tehran, Iran. Dark blue shades show low ranges and dark red shades show high range values for each variable (numbers as given in Table 1).

Figure 3

Methodology flowchart of the study of COVID-19 mortality in Tehran.

Figure 4

(a): Monthly distribution chart of the mortality rates (per 100,000 population) by number and sex; (b): percentage of COVID-19 related deaths by number, sex, and age group.

Figure 5

Purely temporal significant clusters of COVID-19 deaths during 2019 to 2021 in the study area.

Figure 6

Detected purely spatial clusters of COVID-19 deaths in Tehran, Iran.

Figure 7

Detected space-time clusters of COVID-19 deaths in Tehran, Iran.

Figure 8

Spatial distribution of local R² values for GWR and MGWR models. (A): Map of the GWR local R² values, (B): Map of the MGWR local R² values, (C): Histogram chart depicting the distribution of GWR R² values; and (D): Histogram chart depicting the distribution of MGWR R² values in the study area.

Figure 9

Surface map of local estimates pseudo t-values of MGWR model results for Tehran’s COVID-19 mortality rate dataset. Dark blue shades show areas with high t-values. All maps were generated in ArcGIS Pro 3.0.2 (ESRI, Redlands, CA, USA, 2022).

Figure 10

Spatial distribution bivariate map of local estimates (Beta) and covariates original values of MGWR model results for Tehran’s COVID-19 mortality rates. All the maps were generated in ArcGIS Pro 3.0.2 (ESRI, Redlands, CA, USA, 2022).