In order to control epidemics, it is necessary to check the geographical distribution of the incidence and mortality rate and the factors affecting it. This review can influence public health policies aimed at controlling the virus. Since Covid-19 is an emerging and serious infectious disease, the analysis of the spatial distribution pattern of the epidemic is necessary, especially in rural and peri-urban areas, and it can help to prioritize places for targeted interventions, rapid testing and allocation of resources in facing the situation. Similar things will help in the future. The research method is descriptive, analytical and of the type of applied research. The statistical population is 66 villages with health care centers in the vicinity of Mashhad metropolis in the central part of Mashhad city. The period under investigation is from the beginning of the epidemic to October 1401, that is, the end of the seventh wave of the epidemic. During the study period, the rate of infection with Covid-19 for each village was entered into ArcGIS software, processed and the spatial distribution pattern of the epidemic was analyzed by point density analysis. Also, the ellipse techniques of standard distance and standard deviation were used to evaluate the density or dispersion of infected people and to determine the spatial distribution pattern of Covid-19. In order to identify the spatial distribution pattern of the epidemic, Moran's spatial autocorrelation analysis was performed. The results of the spatial analysis showed that by moving away from the metropolis of Mashhad, the density of people infected with Covid-19 in the rural areas decreased. Therefore, the most important factor in the spatial spread of the corona virus in the villages of the central part is the distance and proximity to the city of Mashhad, and it follows Hagerstrand's model of spatial diffusion. Also, with the increase in the density of the rural population and the increase in the number of workers in the service and industry sectors, the incidence of Covid-19 has increased. Moran's coefficient equal to 1.52, with Z-Score equal to 17.19 shows that the pattern of spatial distribution of patients with Covid-19 in the rural areas of the central part is clustered. The results of the study will enable government agencies, policy makers, and health care professionals to make informed decisions to control epidemics and address future infectious diseases. Qualitative data-based studies are needed to further clarify the role of social and economic determinants of health in the outbreak of Covid-19.The results of the spatial analysis show that the density of the number of patients decreases by moving away from the city of Mashhad. The highest density of covid-19 infection is observed in the southern areas of the central part and the neighboring villages of Mashhad metropolis. Also, with the increase in rural population density, the increase in service and industry workers, the number of people infected with Covid-19 will increase. Moran's coefficient equal to 1.52, z-score equal to 17.19 and P-value equal to 0.00 show that the spatial distribution pattern of covid-19 patients in the rural areas of the central part is clustered. It seems that gender affects the spatial distribution of covid-19 patients to some extent. The most important geographical factor of the spread of Covid-19 in the rural areas of the central part is the distance and proximity of the villages affected by this disease, and it follows the pattern of spatial diffusion.The results of the present research are similar to the results of the research of Sidiq Purwoko et al., 2023, which shows that the cases of Covid-19 in Central Java province follow a cluster pattern. Also, with the results of Rahnama and Bazargan's research, 1401, which shows that the spatial distribution of Covid-19 on March 3, 1998 follows a random pattern and on April 3, 1999, a cluster pattern, and the most important geographical factor of the spread of the corona virus in the country, The distance and spatial proximity of the provinces involved in this disease and it follows the pattern of spatial spread is similar.

In conclusion, considering that the spatial distribution of Covid-19 cases in rural areas is affected by the complex interaction of socio-spatial factors, including road networks, functional areas, socio-economic factors and urban facilities, it is suggested to those interested in research in this field to Pay more attention to these factors. Understanding these factors can provide valuable insights for policymakers and researchers working to combat the epidemic.