Background: Using geographical analysis to identify geographical factors affecting the prevalence of COVID-19 infection can effect on public health policies to control of the virus. The aim of this study was to determine the spatial analysis of COVID-19 regions in Qom Province, using the local indicators of spatial association (LISA).
In a descriptive-analytical study, the total number of individuals infected with COVID-19 in Qom Province, from February 19, to September 2020, were included in the study. The spatial distribution in urban areas was determined using the Moran coefficient in GIS. in addition, the spatial autocorrelation of the coronavirus in the different urban districts of the province was calculated using LISA method.
Results: The prevalence of COVID -19 in Qom province was estimated to be 356.75 per 100,000 populations. The pattern of spatial distribution of the prevalence of COVID -19 in Qom was clustered. The District 3 (Imam Khomeini St.), and District 6 (Imamzadeh Ebrahim St.), were set in HH category of LISA as two foci of COVID-19 in Qom province.
Conclusions: Based on LISA, District 1 (Bajak) of urban districts was set in LH category. It means this district is located in a low value area surrounded by high values. One of the most important geographical factors affecting the incidence of coronavirus is based on spatial distribution model, distance and spatial proximity. So, health policy makers, should impose more restrictions on the observance of health protocols to control of the coronavirus.