Geography and Geographical Information Systems Department, College of Social Sciences, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, Saudi Arabia.
King Saud University, Center of Population Studies, Riyadh, Saudi Arabia.
Front Public Health. 2024 Jan 17;12:1281289. doi: 10.3389/fpubh.2024.1281289. eCollection 2024.
Saudi Arabia has 13 administrative areas, all of which have been seriously affected by the COVID-19 epidemic regardless of their features. Being the largest and a prominent Arab country, epidemic intensity and dynamics have importance, especially in the era of Vision 2030 where infrastructure development and growth to enhance quality of life has of prime focus.
This analysis aims to trace the differentials in COVID-19 infections, recoveries, and deaths across the country depending upon various demographic and developmental dimensions and interactions.
This analysis used Saudi Arabia Ministry of Health data from March 15th, 2020 to August 31st, 2022, by classifying administrative areas and locations to build a generalized linear model (3 × 3): three types of administrative areas (major, middle-sized, and others) and localities (major, medium-sized, and others). Apart from two-way ANOVA, an one-way ANOVA also carried out in addition to calculating mean values of infections, recoveries, and deaths.
A total of 205 localities were affected with varying severity, which are based on local demographics. Both the administrative areas and localities had a significant number of cases of infections, recoveries, and mortality, which are influenced by relationships and interactions, leading to differential mean values and proportional distributions across various types of administrative areas and localities.
There is dynamism that major administrative areas have lesser threats from the epidemics whereas medium-sized ones have serious threats. Moreover, an interaction of administrative areas and localities explains the dynamics of epidemic spread under varying levels of infrastructure preparedness. Thus, this study presents lessons learned to inform policies, programs, and development plans, especially for regional, urban, and infrastructure areas, considering grassroots level issues and diversity.
沙特阿拉伯有 13 个行政区域,无论其特征如何,都受到 COVID-19 疫情的严重影响。作为最大和突出的阿拉伯国家,疫情强度和动态具有重要意义,特别是在 2030 年愿景时代,基础设施发展和增长以提高生活质量是重中之重。
本分析旨在根据各种人口和发展维度以及相互作用,追踪全国范围内 COVID-19 感染、康复和死亡的差异。
本分析使用了沙特阿拉伯卫生部从 2020 年 3 月 15 日至 2022 年 8 月 31 日的数据,通过对行政区域和地点进行分类,构建了一个广义线性模型(3×3):三种类型的行政区域(主要、中等和其他)和地点(主要、中等和其他)。除了双向方差分析外,还进行了单向方差分析,以及计算感染、康复和死亡的平均值。
共有 205 个地点受到不同程度的影响,这是基于当地人口统计学。行政区域和地点都有大量的感染、康复和死亡病例,这些病例受到关系和相互作用的影响,导致各种类型的行政区域和地点的平均值和比例分布存在差异。
主要行政区域受到疫情威胁较小,而中等行政区域受到严重威胁,这种情况存在动态变化。此外,行政区域和地点的相互作用解释了在不同基础设施准备水平下疫情传播的动态。因此,本研究提供了经验教训,以告知政策、计划和发展计划,特别是针对区域、城市和基础设施领域,考虑到基层问题和多样性。