{"title":"Spatial epidemiology based on the analysis of COVID-19 in Africa","authors":"Joyce Akhalakwa Mukolwe , John Kamwele Mutinda , Amos Kipkorir Langat","doi":"10.1016/j.sciaf.2025.e02557","DOIUrl":null,"url":null,"abstract":"<div><div>The COVID-19 pandemic has posed significant challenges to global public health, with varying impacts across different regions. In Africa, the disease’s spread and vaccination efforts have been influenced by multiple factors, including geography, socioeconomic status, demographic characteristics, and healthcare infrastructure. This study aims to investigate the spatial epidemiology of COVID-19 across African countries, with a specific focus on understanding the relationship between the geographic distribution of cases, vaccination coverage, and underlying socioeconomic, demographic, and health-related factors. The study utilizes secondary data from the World Health Organization (WHO) and Our World in Data, covering the period from 2020 to 2022. The study employs advanced spatial econometric models — spatial lag model (SLM), spatial lagged X (SLX), and spatial error model (SEM) — to analyze the role of spatial dependence and the influence of neighboring countries on the transmission and vaccination trends across Africa.</div><div>The results reveal significant spatial clustering of COVID-19 cases, with hotspots identified in the Northern and Southern regions of Africa. Specifically, the highest case rates were observed in South Africa, Egypt, and Morocco, while vaccination coverage varied widely, with countries like Seychelles achieving over 70% vaccination coverage, while others like South Sudan showed much lower rates (below 10%) in 2022. The analysis indicates that demographic factors such as the proportion of the population aged 65 and older, and health-related factors such as diabetes prevalence, have a substantial impact on the distribution of cases. Socioeconomic factors, including the human development index (HDI), GDP, and population density, also significantly affect both case rates and vaccination coverage. Furthermore, vaccination uptake in 2021 and 2022 was influenced by varying socioeconomic conditions across countries, with some regions exhibiting lower coverage despite higher availability of vaccines.</div><div>This study highlights the importance of considering spatial factors in understanding disease transmission and vaccination efforts in Africa. It provides key insights for policymakers to develop targeted interventions that account for the unique geographic and socioeconomic contexts of African countries. Understanding these spatial dynamics is crucial for strengthening public health strategies and ensuring equitable vaccine distribution across the continent. The findings underscore the need for tailored interventions based on geographic and socio-economic conditions, which could lead to more efficient responses to future health crises.</div></div>","PeriodicalId":21690,"journal":{"name":"Scientific African","volume":"27 ","pages":"Article e02557"},"PeriodicalIF":2.7000,"publicationDate":"2025-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Scientific African","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2468227625000286","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
The COVID-19 pandemic has posed significant challenges to global public health, with varying impacts across different regions. In Africa, the disease’s spread and vaccination efforts have been influenced by multiple factors, including geography, socioeconomic status, demographic characteristics, and healthcare infrastructure. This study aims to investigate the spatial epidemiology of COVID-19 across African countries, with a specific focus on understanding the relationship between the geographic distribution of cases, vaccination coverage, and underlying socioeconomic, demographic, and health-related factors. The study utilizes secondary data from the World Health Organization (WHO) and Our World in Data, covering the period from 2020 to 2022. The study employs advanced spatial econometric models — spatial lag model (SLM), spatial lagged X (SLX), and spatial error model (SEM) — to analyze the role of spatial dependence and the influence of neighboring countries on the transmission and vaccination trends across Africa.
The results reveal significant spatial clustering of COVID-19 cases, with hotspots identified in the Northern and Southern regions of Africa. Specifically, the highest case rates were observed in South Africa, Egypt, and Morocco, while vaccination coverage varied widely, with countries like Seychelles achieving over 70% vaccination coverage, while others like South Sudan showed much lower rates (below 10%) in 2022. The analysis indicates that demographic factors such as the proportion of the population aged 65 and older, and health-related factors such as diabetes prevalence, have a substantial impact on the distribution of cases. Socioeconomic factors, including the human development index (HDI), GDP, and population density, also significantly affect both case rates and vaccination coverage. Furthermore, vaccination uptake in 2021 and 2022 was influenced by varying socioeconomic conditions across countries, with some regions exhibiting lower coverage despite higher availability of vaccines.
This study highlights the importance of considering spatial factors in understanding disease transmission and vaccination efforts in Africa. It provides key insights for policymakers to develop targeted interventions that account for the unique geographic and socioeconomic contexts of African countries. Understanding these spatial dynamics is crucial for strengthening public health strategies and ensuring equitable vaccine distribution across the continent. The findings underscore the need for tailored interventions based on geographic and socio-economic conditions, which could lead to more efficient responses to future health crises.