Environmental Management Hazards 2423-415X 7 2 2020 06 21 Analysis of spatio-temporal patterns of Covid-19 virus pandemic and its hazards in Iran Analysis of spatio-temporal patterns of Covid-19 virus pandemic and its hazards in Iran 113 127 77530 10.22059/jhsci.2020.304976.571 FA Mohammad Rahim Rahnama Professor of Geography and Urban Planning, Ferdowsi University of Mashhad, Mashhad, Iran Mahdi Bazargan PhD Student in Geography and Urban Planning, Ferdowsi University of Mashhad, Mashhad, Iran Journal Article 2020 06 23 Introduction In the present century, the prevalence of COVID-19 pneumonia as a contagious disease has posed major health threats to the world's public health. Despite significant advances in the fight against disease, infectious diseases are still of particular importance in epidemiology and community health. One of the main applications of epidemiological science is to facilitate the identification of geographical areas and vulnerable groups that are at higher risk for disease and risk factors for mortality. A geographic information system is a tool for collecting, storing, cohesive, managing, retrieving, analyzing, and displaying spatial information that can be used in epidemiological research and health policy. Therefore, this research has been conducted with the aim of geospatial study of Coronavirus to model the spatial emission of COVID-19 epidemiology in the country. Materials and Methods Based on the purpose of the present research, it is among the applied researches and according to the research method, it is descriptive-analytical. ArcGIS software has been used to analyze data. The statistical population of study includes the number of people infected with Coronavirus (21638 people) in the provinces of the country and in the time range of February 22, 2020 to March 22, 2020. Also, the study area in this research is 31 provinces of the country. Results and Discussion The present study has modeled the spread and spatial distribution of coronavirus epidemiology during the period of February 22, 2020 to March 22, 2020 in the country. The highest geographical distribution of coronary heart disease is observed in the northern and central regions of the country. The southern and southeastern regions of the country have the lowest prevalence of coronavirus. The results of spatial self-correlation showed that 32.26% of the country's provinces (Tehran, Alborz, Qom, Mazandaran, Gilan, Qazvin, Isfahan, Semnan, Markazi and Yazd) in the HH cluster, 9.68% of the provinces (Zanjan, Lorestan) And Ilam) in HL cluster, 41.94% of provinces (South Khorasan, East Azerbaijan, Kurdistan, Kohgiluyeh and Boyer-Ahmad, Hormozgan, Khuzestan, Fars, Bushehr, Sistan and Baluchestan, Chaharmahal and Bakhtiari, Kerman, Kermanshah and West Azerbaijan) in The LL cluster and 16.13% of the provinces (Golestan, Khorasan Razavi, North Khorasan, Ardabil and Hamedan) are also in the LH cluster. Conclusion The results of statistical-spatial analysis of hot spots show that Qom, Tehran, Golestan, Semnan, Isfahan, Mazandaran, and Alborz provinces (22.5% of the country's provinces) are in hot spots and Bushehr, Ilam and Kermanshah (9.67% of the country's provinces) were identified as cold spots. In addition, spatial clustering of the country's provinces showed that the spatio-temporal distance factor is the most important factor in spatial distribution of coronavirus from the center (Qom province) to other provinces, and follows the pattern of compatible spatial distribution. Introduction In the present century, the prevalence of COVID-19 pneumonia as a contagious disease has posed major health threats to the world's public health. Despite significant advances in the fight against disease, infectious diseases are still of particular importance in epidemiology and community health. One of the main applications of epidemiological science is to facilitate the identification of geographical areas and vulnerable groups that are at higher risk for disease and risk factors for mortality. A geographic information system is a tool for collecting, storing, cohesive, managing, retrieving, analyzing, and displaying spatial information that can be used in epidemiological research and health policy. Therefore, this research has been conducted with the aim of geospatial study of Coronavirus to model the spatial emission of COVID-19 epidemiology in the country. Materials and Methods Based on the purpose of the present research, it is among the applied researches and according to the research method, it is descriptive-analytical. ArcGIS software has been used to analyze data. The statistical population of study includes the number of people infected with Coronavirus (21638 people) in the provinces of the country and in the time range of February 22, 2020 to March 22, 2020. Also, the study area in this research is 31 provinces of the country. Results and Discussion The present study has modeled the spread and spatial distribution of coronavirus epidemiology during the period of February 22, 2020 to March 22, 2020 in the country. The highest geographical distribution of coronary heart disease is observed in the northern and central regions of the country. The southern and southeastern regions of the country have the lowest prevalence of coronavirus. The results of spatial self-correlation showed that 32.26% of the country's provinces (Tehran, Alborz, Qom, Mazandaran, Gilan, Qazvin, Isfahan, Semnan, Markazi and Yazd) in the HH cluster, 9.68% of the provinces (Zanjan, Lorestan) And Ilam) in HL cluster, 41.94% of provinces (South Khorasan, East Azerbaijan, Kurdistan, Kohgiluyeh and Boyer-Ahmad, Hormozgan, Khuzestan, Fars, Bushehr, Sistan and Baluchestan, Chaharmahal and Bakhtiari, Kerman, Kermanshah and West Azerbaijan) in The LL cluster and 16.13% of the provinces (Golestan, Khorasan Razavi, North Khorasan, Ardabil and Hamedan) are also in the LH cluster. Conclusion The results of statistical-spatial analysis of hot spots show that Qom, Tehran, Golestan, Semnan, Isfahan, Mazandaran, and Alborz provinces (22.5% of the country's provinces) are in hot spots and Bushehr, Ilam and Kermanshah (9.67% of the country's provinces) were identified as cold spots. In addition, spatial clustering of the country's provinces showed that the spatio-temporal distance factor is the most important factor in spatial distribution of coronavirus from the center (Qom province) to other provinces, and follows the pattern of compatible spatial distribution. https://jhsci.ut.ac.ir/article_77530_c6a5ae71190b09f8e7a9149d373177b7.pdf