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

Author

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  • Samuel O. M. Manda

    (Biostatistics Research Unit, South Africa Medical Research Council, Pretoria 0001, South Africa
    Department of Statistics, University of Pretoria, Pretoria 0028, South Africa)

  • Timotheus Darikwa

    (Department of Statistics and Operations Research, University of Limpopo, Sovenga 0727, South Africa)

  • Tshifhiwa Nkwenika

    (Biostatistics Research Unit, South Africa Medical Research Council, Pretoria 0001, South Africa)

  • Robert Bergquist

    (Ingerod, SE-454 94 Brastad, Sweden)

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.

Suggested Citation

  • Samuel O. M. Manda & Timotheus Darikwa & Tshifhiwa Nkwenika & Robert Bergquist, 2021. "A Spatial Analysis of COVID-19 in African Countries: Evaluating the Effects of Socio-Economic Vulnerabilities and Neighbouring," IJERPH, MDPI, vol. 18(20), pages 1-15, October.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:20:p:10783-:d:656100
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    References listed on IDEAS

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    1. Kolawole Valère Salako & Akoeugnigan Idelphonse Sode & Aliou Dicko & Eustache Ayédèguè Alaye & Martin Wolkewitz & Romain Glèlè Kakaï, 2024. "Cross-Country Assessment of Socio-Ecological Drivers of COVID-19 Dynamics in Africa: A Spatial Modelling Approach," Stats, MDPI, vol. 7(4), pages 1-15, October.
    2. Małgorzata Dudzińska & Marta Gwiaździńska-Goraj & Aleksandra Jezierska-Thöle, 2022. "Social Factors as Major Determinants of Rural Development Variation for Predicting Epidemic Vulnerability: A Lesson for the Future," IJERPH, MDPI, vol. 19(21), pages 1-24, October.

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