The final, formatted version of the article will be published soon.
ORIGINAL RESEARCH article
Front. Public Health
Sec. Infectious Diseases: Epidemiology and Prevention
Volume 12 - 2024 |
doi: 10.3389/fpubh.2024.1400629
Spatiotemporal modelling of covid-19 spread: unveiling socioeconomic disparities and patterns, across social classes in the urban population of Kermanshah, Iran
Provisionally accepted- 1 Kermanshah University of Medical Sciences, Kermanshah, Kerman, Iran
- 2 Dezful University of Medical Sciences (DUMS), Dezful, Khuzestan, Iran
- 3 Birjand University of Medical Sciences, Birjand, South Khorasan, Iran
- 4 Cardiovascular Research Center, Kermanshah University of Medical Sciences, Kermanshah, Iran
- 5 The University of Manchester, Manchester, England, United Kingdom
- 6 Amir Kabir Hospital, Arak, Iran
- 7 University of South Australia, Adelaide, Australia
Presenting ongoing outbreaks and the potential for their spread to nearby neighborhoods and social classes may offer a deeper understanding, enable a more efficient reaction to outbreaks, and enable a comprehensive understanding of intricate details for strategic response planning. Hence, this study explored the spatiotemporal spread of COVID-19 outbreaks and prioritization of the risk areas among social classes in the Kermanshah metropolis. Methods: In this cross-sectional study, the data of 58.951 COVID-19-infected patients were analyzed. In 2020, out of 24.849 infected patients, 10.423 were females, 14,426 were males, and in 2021, 15.714 were females, and 18,388 were males. To categorize social classes (working, middle, and upper), we utilized economic, social, cultural, and physical indicators. Our analysis utilized Arc/GIS 10.6 software along with statistical tests, including standard distance (SD), mean center (MC), standard deviational ellipse (SDE), and Moran's I.The results revealed that the average epicenter of the disease shifted from the city center in 2020-2021 to the eastern part of the city in 2021. The results related to the SD of the disease showed that more than 70% of the patients were concentrated in this area of the city. The SD of COVID-19 in 2020 compared to 2021 also indicated an increased spread throughout the city. Moran's I test and the hotspot test results showed the emergence of a clustered pattern of the disease. In the Kermanshah metropolis, 58,951 COVID-19 cases were recorded, with 55.76% males and 44.24% females. Social class distribution showed 28.86% upper class, 55.95% middle class, and 15.19% working class. A higher disease prevalence among both males and females in the upper class compared to others. Discussion: Our study designed a spatiotemporal disease spread model, specifically tailored for a densely populated urban area. This model allows for the observation of how COVID-19 propagates both spatially and temporally, offering a deeper understanding of outbreak dynamics in different neighborhoods and social classes of the city.
Keywords: COVID-19, Crisis response strategies, Socioeconomic status, GIS, Disease transmission, Epidemic management
Received: 26 Mar 2024; Accepted: 29 Aug 2024.
Copyright: © 2024 Zangeneh, Hamidipour, Khazir, Ziapour, Molavi, Kiaee, Teimouri and Khosravi. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Arash Ziapour, Cardiovascular Research Center, Kermanshah University of Medical Sciences, Kermanshah, Iran
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.