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 OurWorld 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.
