Spatial analysis of covid-19 disease based on demographic and geographic indicators in dry areas, a case study of Qom metropolis

Aim: The aim of this research is to analyze the COVID-19 virus spatially based on demographic and geographic indicators in dry areas (in Qom metropolis). Material & Method: The data for this research was obtained through the available data from Qom University of Medical Sciences during the years 2018-1400. This information is based on the location of each person in the GIS software environment, and the methods of nearest neighbor index (NNI), global Moran's test, and general G statistic were used to measure spatial autocorrelation statistics. Findings: This research showed that the spread and pandemic of COVID-19 in some dry areas (Shahreqom) have more acute conditions than other localities. Conclusion: Based on the research findings, it can be said that the distribution pattern of this disease in the neighborhoods of Qom city is clustered and cluster type with high intensity. This relationship is stronger and with the highest frequency in the localities of Bajak Ik, Khakfaraj, Nirogah, and Shahrpardisan and in the localities of Hozovi and University and Fatemieh towns, which are the watery localities with the lowest frequency in terms of demographic and geographical indicators. Innovation: Among the most important innovative and practical aspects of research, we can mention the use of GIS in the distribution and spread of COVID-19 in different urban areas of dry regions. In fact, among the applications of this research, it is possible to mention the field of behavior and spatiotemporal function of viruses similar to the type of COVID-19 virus, which provides a coherent intellectual framework for controlling and preventing its epidemic.