Social Development and Health Promotion Research Center, Health Institute, Kermanshah University of Medical Sciences, Kermanshah, Iran.
School of Nursing and Midwifery, Dezful University of Medical Sciences, Dezful, Iran.
Front Public Health. 2024 Oct 4;12:1400629. doi: 10.3389/fpubh.2024.1400629. eCollection 2024.
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.
n 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 .
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.
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.
呈现正在发生的疫情及其向附近社区和社会阶层扩散的可能性，可能会提供更深入的了解，使我们能够更有效地应对疫情，并全面了解战略应对规划的复杂细节。因此，本研究探讨了克尔曼沙阿大都市 COVID-19 疫情的时空传播，并对不同社会阶层的风险区域进行了优先级排序。
在这项横断面研究中，对 58951 名 COVID-19 感染患者的数据进行了分析。2020 年，在 24849 名感染患者中，有 10423 名女性，14426 名男性；2021 年，有 15714 名女性，18388 名男性。为了对社会阶层（工人、中产阶级和上层阶级）进行分类，我们利用了经济、社会、文化和物理指标。我们的分析利用了 Arc/GIS 10.6 软件以及统计测试，包括标准距离（SD）、平均中心（MC）、标准偏差椭圆（SDE）和 Moran's I。
结果表明，疾病的平均震中从 2020 年至 2021 年从市中心转移到了城市的东部。与疾病 SD 相关的结果表明，超过 70%的患者集中在该城市区域。与 2021 年相比，2020 年 COVID-19 的 SD 也表明疾病在整个城市的传播有所增加。Moran's I 测试和热点测试结果表明，疾病呈集群模式出现。在克尔曼沙阿大都市，记录了 58951 例 COVID-19 病例，其中 55.76%为男性，44.24%为女性。社会阶层分布显示，上层阶级占 28.86%，中产阶级占 55.95%，工人阶级占 15.19%。与其他阶层相比，男性和女性中上层阶级的疾病发病率更高。
我们的研究设计了一种针对人口密集城市的时空疾病传播模型，该模型能够观察 COVID-19 在不同社区和城市社会阶层中的空间和时间传播方式，从而更深入地了解疫情动态。
