Geospatial modeling and analysis of COVID-19 prevalence in Lagos state Nigeria

J. Igbokwe, A. Akinpelu, Andrew. Osagie Oliha, P. C. Anyadiegwu, Wille Augustine Ojanikele
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Abstract

The impact of COVID-19 pandemic has spatial dimensions which when properly interpreted could lead to better understanding of different characteristics of the pandemic. Thus, the impact of COVID-19 can be mapped for spatial analysis of its attributes. From health science, the research needs include the ability to cross variables of different kinds to interpret the COVID-19 phenomenon, its spatial analysis and spatiotemporal dimensions, its geographical impact on decision-making and everyday life, and predictive modelling of the evolution of the disease. For these reasons, this research aimed at geospatial modelling and analysis of COVID-19 prevalence in Lagos State Nigeria with a view to determine the spread and distribution pattern of COVID-19 as well as its hotspots in Lagos State Nigeria. Its objectives are to: identify and model the spatial distribution of COVID-19 in Lagos State and map the prevalence of COVID-19 in Lagos State. The methodology involved the analysis of the spatial distribution of COVID-19 between 2020 and 2022 and COVID-19 prevalence analysis. Results indicate a substantial surge in confirmed COVID-19 cases, rising from 21,717 to 56,596 during the study period. Alimosho and Eti-Osa LGAs emerged as the most affected regions, reporting the highest total confirmed cases. Additionally, confirmed deaths increased from 4,090 in 2020 to 9,874 in 2022, with Eti-Osa consistently reporting the highest number of fatalities, followed by Ikorodu and Surulere. Assessing the prevalence of confirmed cases and deaths across different LGAs, Eti-Osa consistently exhibited the highest prevalence, indicating a significant proportion of cases and deaths relative to its population.
尼日利亚拉各斯州 COVID-19 流行率的地理空间建模与分析
COVID-19 大流行病的影响具有空间维度,对其进行正确解读可更好地了解该流行病的不同特征。因此,可以绘制 COVID-19 的影响图,对其属性进行空间分析。从健康科学的角度来看,研究需求包括交叉不同类型变量的能力,以解释 COVID-19 现象、其空间分析和时空维度、其对决策和日常生活的地理影响,以及对疾病演变的预测建模。因此,本研究旨在对 COVID-19 在尼日利亚拉各斯州的流行情况进行地理空间建模和分析,以确定 COVID-19 在尼日利亚拉各斯州的传播和分布模式及其热点地区。其目标是:确定 COVID-19 在拉各斯州的空间分布并建立模型,绘制 COVID-19 在拉各斯州的流行地图。研究方法包括分析 2020 年至 2022 年 COVID-19 的空间分布以及 COVID-19 流行率分析。结果表明,在研究期间,COVID-19 确诊病例大幅增加,从 21,717 例增加到 56,596 例。阿利莫绍和埃蒂-奥萨地方自治政府是受影响最严重的地区,报告的确诊病例总数最高。此外,确诊死亡人数从 2020 年的 4,090 人增加到 2022 年的 9,874 人,其中埃蒂-奥萨的死亡人数一直最高,其次是伊科罗杜和苏卢雷。在评估不同地方选区的确诊病例和死亡人数时,埃蒂-奥萨的发病率一直最高,这表明病例和死亡人数在其人口中所占比例相当大。
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