The Spatial Predicting of COVID-19 Incidence and Its Mortality Based On OLS and GWR Models in Iran

Abstract

Background: Within six months of the COVID-19 outbreak, 350279 people were infected, and 20125 people died of COVID-19 in Iran. There is an urgent need to find the most accurate effective indicators on this disease's outbreak in order to control and predict. Methods: We examined the effect of 36 demographic, economic, environmental, health infrastructure, social, and topographic independent variables on the COVID-19 infection and mortality rates using the ordinary least squares (OLS) model in ArcGIS 10.5. Regarding adjusted R-squared>0/7, we selected 20 variables for COVID-19 infection rate and 16 variables for the mortality rate. The collinearity problem between the selected variables resolved after using the variance inflation factor (VIF). Then, we performed the OLS and geographically weighted regression (GWR) models in ArcGIS 10.5.Results: Having a large number of men, having a large population, lack of specialist doctors, lack of hospital, having a large urban population, having a large number of people aged 65 and over or older individuals, and high natural mortality rate had the most prominent impact on the COVID-19 infection increasing rate. Also, lack of ICU beds, low number of insured people, lack of subspecialist physicians, and lack of hospital beds had the most prominent impact on increasing of COVID-19 mortality. Then the variables with VIF above 7.5 were removed and finally, high incoming immigrants rate and lack of nurses were identified as two independent variables to predict COVID-19 infection rate. In addition, high incoming immigrants rate and high number of doctor consultation were recognized as two variables to predict mortality rate due to COVID-19. The results of the Akaike information criterion (AIC) and adj.R2 showed that both models were appropriate for these analyses.Conclusions: Based on our results, there would be a considerable increase in COVID-19 infection in Kerman, Esfahan, and Kermanshah provinces. In addition, there would be a remarkable decrease in COVID-19 infection in Khuzestan, Lorestan, Azarbayjan Shargi, and Tehran provinces. Regarding COVID-19 mortality, there would be a substantial rise in Fars and Khorasan Razavi provinces. Moreover, our analyses predicted a considerable diminish in COVID-19 mortality in Tehran, Ardebil, Zanjan, Gilan, Golestan, Lorestan, Khuzestan, Bushehr, and Hormozgan provinces.