geographical distribution and underlying diseases of patients with covid-19 referred to afzalipour hospital in kerman city

Background: covid-19 is a novel disease that infected many people around the world. it is essential to find the potential high-risk locations and provide suitable healthcare interventions to control covid-19 distribution. using a geographic information system, this study aimed to investigate the distribution trends of patients with covid-19 in kerman, iran. methods: the information of registered patients of afzalipour hospital in kerman city who were admitted before july 22, 2020, was collected and used in this paper. the patients’ addresses were converted into geocodes. the trend of disease prevalence in connection with population density in different parts of kerman was investigated. after that, the average nearest neighbor analysis was performed to check the random distribution of disease cases. data were checked for randomness by high/low clustering analysis. results: : the spread of the covid-19 disease started in kerman city’s north, south, and west and then distributed to the center. the southern and western regions were in high-high clusters, and the central and northern regions were in low-low clusters in terms of covid-19 outbreak risk. regression showed a significant correlation between underlying diseases and patients' age with the incidence of covid-19 disease. conclusion: the prevalence of covid-19 had been higher in densely populated areas and also in areas with poorer economic conditions. therefore, paying attention to these areas as well as applying strict rules can help control the spread of covid-19. the result of this study could be useful for public health experts and healthcare managers to manage better this pandemic.