Title of article :
A description of spatial-temporal patter s of the novel COVID-19 outbreak in the neighbourhoods’ scale in Tehran, Iran
Author/Authors :
Lak, Azadeh Faculty of Architecture and Urban Planning - Shahid Beh shti University - Tehran, Iran , Maher, Ali School of Management and Medi al Education - Shahid Beheshti Uni ersity of Medical Sciences - Tehran, Iran , Zali, Alireza Shahid Beheshti University of Medical Scien es - Tehran, Iran , Badr, Siamak Faculty of Architecture and Urban Planning - Shahid Beh shti University - Tehran, Iran , Mostafavi, Ehsan Department of Epidemiology and Biostatistics - Resear h Centre for Emerging and Reemerging infectious diseases - Pasteur Institute of Iran - Tehran, Iran , R Baradaran, Hami Department of E idemiology - School of Public Health - Iran University of Medical Sciences - Tehran, Iran , Hanani, Khatereh Sh hid Beheshti University of Medical Sciences - Tehran, Iran , Toomanian, Ara Department of GI and Remote Sensing - Faculty of Geo raphy - University of Tehran - Tehran, Iran , Khalili, Davood Shahid Beheshti University of Medi al Sciences - Tehra , Iran
Abstract :
Background: Analyzing and monitoring the spatial-temporal patterns of the new co onavirus 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 spo s 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 J ly 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 nu
ber 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.
Keywords :
Spatial-temporal analysis , COVID-19 outbreak , Hotspot cases , GIS , Tehran , Iran
Journal title :
Medical Journal of the Islamic Republic of Iran