Analysis of spatial-temporal patterns of corona virus epidemic in Iran

One of the most contagious and infectious diseases of the 21st century is the coronavirus (Covid-19), which has been spreading worldwide since the end of December 2019 as a pneumonia outbreak from China. Analysis of spatial-temporal patterns of Coronavirus using GIS is important in understanding the geographical distribution of this epidemic as well as epidemiological and community health studies in the country. Therefore, it is necessary to study the geography of this disease in order to control and prevent it; Therefore, in the present applied and descriptive-analytical research, using spatial statistics, it has performed spatial-temporal analysis as well as spatial modeling of coronavirus epidemiology in the country. The statistical population of the present study is 31 provinces of the country. The data of Corona virus patients were analyzed in the period from March 24, 2017 to April 24, 2012 (21638 people) using ArcGIS software. The results of spatial correlation show that the provinces of Tehran, Alborz, Qom, Mazandaran, Gilan, Qazvin, Isfahan, Semnan, Markazi and Yazd are in the HH cluster, which means that the number of people infected with coronavirus in these provinces is higher than average. 32.26% of the country's provinces. Also, the analysis of hot spots on the number of people infected with Coronavirus showed that the provinces (Qom, Tehran, Golestan, Semnan, Isfahan, Mazandaran and Alborz) in the hot clusters and the provinces (Bushehr, Ilam and Kermanshah) in the cold clusters. Are located. The results of the study indicate that the most important geographical factor in the spread of coronavirus in the country is the distance and proximity of the provinces affected by the disease, which follows the pattern of compatible spatial distribution.