Medical Journal of The Islamic Republic of Iran (MJIRI)
Iran University of Medical Sciences
Tue, Nov 12, 2024
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Volume 35, Issue 1 (1-2021)
Med J Islam Repub Iran 2021 |
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Lak A, Maher A, Zali A, Badr S, Mostafavi E, Baradaran H R, et al . A description of spatial-temporal patterns of the novel COVID-19 outbreak in the neighbourhoods’ scale in Tehran, Iran. Med J Islam Repub Iran 2021; 35 (1) :954-961
URL: http://mjiri.iums.ac.ir/article-1-7521-en.html
URL: http://mjiri.iums.ac.ir/article-1-7521-en.html
Azadeh Lak 
, Ali Maher , Alireza Zali , Siamak Badr , Ehsan Mostafavi , Hamid R Baradaran , Khatereh Hanani , Ara Toomanian , Davood Khalili
, Ali Maher , Alireza Zali , Siamak Badr , Ehsan Mostafavi , Hamid R Baradaran , Khatereh Hanani , Ara Toomanian , Davood Khalili
School of Management and Medical Education, Shahid Beheshti University of Medical Sciences, Tehran, Iran , dralimaher@Sbmu.ac.ir
Abstract: (1876 Views)
Background: Analyzing and monitoring the spatial-temporal patterns of the new coronavirus disease (COVID-19) pandemic can assist local authorities and researchers in detecting disease outbreaks in the early stages. Because of different socioeconomic profiles in Tehran's areas, we will provide a clear picture of the pandemic distribution in Tehran's neighbourhoods during the first months of its spread from February to July 2020, employing a spatial-temporal analysis applying the geographical information system (GIS). Disease rates were estimated by location during the 5 months, and hot spots and cold spots were highlighted.
Methods: This study was performed using the COVID-19 incident cases and deaths recorded in the Medical Care Monitoring Centre from February 20, to July 20, 2020. The local Getis-Ord Gi* method was applied to identify the hotspots where the infectious disease distribution had significantly clustered spatially. A statistical analysis for incidence and mortality rates and hot spots was conducted using ArcGIS 10.7 software.
Results: The addresses of 43,000 Tehrani patients (15,514 confirmed COVID-19 cases and 27,486 diagnosed as probable cases) were changed in its Geo-codes in the GIS. The highest incidence rate from February to July 2020 was 48 per 10,000 and the highest 5-month incidence rate belonged to central and eastern neighbourhoods. According to the Cumulative Population density of patients, the higher number is estimated by more than 2500 people in the area; however, the lower number is highlighted by about 500 people in the neighborhood. Also, the results from the local Getis-Ord Gi* method indicate that COVID-19 has formed a hotspot in the eastern, southeast, and central districts in Tehran since February. We also observed a death rate hot spot in eastern areas.
Conclusion: Because of the spread of COVID-19 disease throughout Tehran's neighborhoods with different socioeconomic status, it seems essential to pay attention to health behaviors to prevent the next waves of the disease. The findings suggest that disease distribution has formed a hot spot in Tehran's eastern and central regions.
Methods: This study was performed using the COVID-19 incident cases and deaths recorded in the Medical Care Monitoring Centre from February 20, to July 20, 2020. The local Getis-Ord Gi* method was applied to identify the hotspots where the infectious disease distribution had significantly clustered spatially. A statistical analysis for incidence and mortality rates and hot spots was conducted using ArcGIS 10.7 software.
Results: The addresses of 43,000 Tehrani patients (15,514 confirmed COVID-19 cases and 27,486 diagnosed as probable cases) were changed in its Geo-codes in the GIS. The highest incidence rate from February to July 2020 was 48 per 10,000 and the highest 5-month incidence rate belonged to central and eastern neighbourhoods. According to the Cumulative Population density of patients, the higher number is estimated by more than 2500 people in the area; however, the lower number is highlighted by about 500 people in the neighborhood. Also, the results from the local Getis-Ord Gi* method indicate that COVID-19 has formed a hotspot in the eastern, southeast, and central districts in Tehran since February. We also observed a death rate hot spot in eastern areas.
Conclusion: Because of the spread of COVID-19 disease throughout Tehran's neighborhoods with different socioeconomic status, it seems essential to pay attention to health behaviors to prevent the next waves of the disease. The findings suggest that disease distribution has formed a hot spot in Tehran's eastern and central regions.
Type of Study: Original Research |
Subject:
Epidemiology
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