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Mapping and Spatial Pattern Analysis of Covid-19 in Central Iran Using the Local Indicators of Spatial Association (Lisa) Publisher Pubmed



Jesri N1 ; Saghafipour A2 ; Koohpaei A3 ; Farzinnia B4 ; Jooshin MK5 ; Abolkheirian S6 ; Sarvi M7
Authors
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Authors Affiliations
  1. 1. Remote Sensing & GIS Centre, Shahid Beheshti University, Tehran, Iran
  2. 2. Department of Public Health, Faculty of Health, Qom University of Medical Sciences, Qom, Iran
  3. 3. Occupational health & Safety Department, Faculty of Health, Qom University of Medical Sciences, Qom, Iran
  4. 4. Department of Environmental Health Engineering, Faculty of Health, Qom University of Medical Sciences, Qom, Iran
  5. 5. Department of Disease Control and Prevention, Qom Provincial Health Center, Qom University of Medical Sciences, Qom, Iran
  6. 6. Department of Health Education and Promotion, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
  7. 7. Student Research Committee, Qom University of Medical Sciences, Qom, Iran

Source: BMC Public Health Published:2021


Abstract

Background: Using geographical analysis to identify geographical factors related to the prevalence of COVID-19 infection can affect public health policies aiming at controlling the virus. This study aimed to determine the spatial analysis of COVID-19 in Qom Province, using the local indicators of spatial association (LISA). Methods: In a primary descriptive-analytical study, all individuals infected with COVID-19 in Qom Province from February 19th, 2020 to September 30th, 2020 were identified and included in the study. The spatial distribution in urban areas was determined using the Moran coefficient in geographic information systems (GIS); in addition, the spatial autocorrelation of the coronavirus in different urban districts of the province was calculated using the LISA method. Results: The prevalence of COVID-19 in Qom Province was estimated to be 356.75 per 100,000 populations. The pattern of spatial distribution of the prevalence of COVID-19 in Qom was clustered. District 3 (Imam Khomeini St.) and District 6 (Imamzadeh Ebrahim St.) were set in the High-High category of LISA: a high-value area surrounded by high-value areas as the two foci of COVID-19 in Qom Province. District 1 (Bajak) of urban districts was set in the Low-High category: a low-value area surrounded by high values. This district is located in a low-value area surrounded by high values. Conclusions: According to the results, district 3 (Imam Khomeini St.) and district 6 (Imamzadeh Ebrahim St.) areas are key areas for preventing and controlling interventional measures. In addition, considering the location of District 1 (Bajak) as an urban district in the Low-High category surrounded by high values, it seems that distance and spatial proximity play a major role in the spread of the disease. © 2021, The Author(s).
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