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      A Spatial Analysis of COVID-19 in African Countries: Evaluating the Effects of Socio-Economic Vulnerabilities and Neighbouring.

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          Abstract

          The ongoing highly contagious coronavirus disease 2019 (COVID-19) pandemic, which started in Wuhan, China, in December 2019, has now become a global public health problem. Using publicly available data from the COVID-19 data repository of Our World in Data, we aimed to investigate the influences of spatial socio-economic vulnerabilities and neighbourliness on the COVID-19 burden in African countries. We analyzed the first wave (January-September 2020) and second wave (October 2020 to May 2021) of the COVID-19 pandemic using spatial statistics regression models. As of 31 May 2021, there was a total of 4,748,948 confirmed COVID-19 cases, with an average, median, and range per country of 101,041, 26,963, and 2191 to 1,665,617, respectively. We found that COVID-19 prevalence in an Africa country was highly dependent on those of neighbouring Africa countries as well as its economic wealth, transparency, and proportion of the population aged 65 or older (p-value < 0.05). Our finding regarding the high COVID-19 burden in countries with better transparency and higher economic wealth is surprising and counterintuitive. We believe this is a reflection on the differences in COVID-19 testing capacity, which is mostly higher in more developed countries, or data modification by less transparent governments. Country-wide integrated COVID suppression strategies such as limiting human mobility from more urbanized to less urbanized countries, as well as an understanding of a county's social-economic characteristics, could prepare a country to promptly and effectively respond to future outbreaks of highly contagious viral infections such as COVID-19.

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          Author and article information

          Journal
          Int J Environ Res Public Health
          International journal of environmental research and public health
          MDPI AG
          1660-4601
          1660-4601
          October 14 2021
          : 18
          : 20
          Affiliations
          [1 ] Biostatistics Research Unit, South Africa Medical Research Council, Pretoria 0001, South Africa.
          [2 ] Department of Statistics, University of Pretoria, Pretoria 0028, South Africa.
          [3 ] Department of Statistics and Operations Research, University of Limpopo, Sovenga 0727, South Africa.
          [4 ] Ingerod, SE-454 94 Brastad, Sweden.
          Article
          ijerph182010783
          10.3390/ijerph182010783
          8535688
          34682528
          91b43597-32f0-4353-bd3b-43576faae0a6
          History

          spatial regression analysis,country-level disparities,coronavirus (COVID-19) pandemic,Sub-Saharan Africa

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