A description of spatial-temporal patterns of the novel COVID-19 outbreak in the neighbourhoods' scale in Tehran, Iran.

Autor:	Lak A; Faculty of Architecture and Urban Planning, Shahid Beheshti University, Tehran, Iran., Maher A; School of Management and Medical Education, Shahid Beheshti University of Medical Sciences, Tehran, Iran., Zali A; Functional Neurosurgery Research Center, Shohada Tajrish Neurosurgical Center of Excellence, Shahid Beheshti University of Medical Sciences, Tehran, Iran., Badr S; Faculty of Architecture and Urban Planning, Shahid Beheshti University, Tehran, Iran., Mostafavi E; Department of Epidemiology and Biostatistics, Research Centre for Emerging and Reemerging infectious diseases, Pasteur Institute of Iran, Tehran, Iran., Baradaran HR; Department of Epidemiology, School of Public Health, Iran University of Medical Sciences, Tehran, Iran., Hanani K; Statistics & Information Technology Managment, Shahid Beheshti University of Medical Sciences, Tehran, Iran., Toomanian A; Department of GIS and Remote Sensing, Faculty of Geography, University of Tehran, Tehran, Iran., Khalili D; Prevention of Metabolic Disorders Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Jazyk:	angličtina
Zdroj:	Medical journal of the Islamic Republic of Iran [Med J Islam Repub Iran] 2021 Oct 04; Vol. 35, pp. 128. Date of Electronic Publication: 2021 Oct 04 (Print Publication: 2021).
DOI:	10.47176/mjiri.35.128
Abstrakt:	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. Competing Interests: Conflicts of Interest: None declared (© 2021 Iran University of Medical Sciences.)
Databáze:	MEDLINE
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