![]() Geographically, significant robust relationships of these factors were found in the middle and southern parts of the city where the reported infection case was also higher. Social parameters like population density ( p<0.01 ), brickfield density ( p<0.02 ), and poverty level ( p<0.01 ) showed high coefficients as the key independent variables to COVID-19 infection rate. ![]() This study revealed that air pollution parameters like PM 2.5 ( p<0.02), AOT ( p<0.01), CO ( p<0.05), water vapor ( p<0.01) and O 3 ( p<0.01) were highly correlated with COVID-19 infection rate while geo-meteorological parameters like DEM ( p<0.01 ), wind pressure ( p<0.01 ), LST ( p<0.04 ), rainfall ( p<0.01 ) and wind speed ( p<0.03) were also similarly associated. Geographically Weighted Regression (GWR) model and GIS was used to understand the associations between COVID-19 infection rate as a dependent variable and 17 independent variables of air pollution, geo-meteorological and social parameters using a set of temporal data from 2010-2020 (May) in Dhaka, Bangladesh.
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