ArticleScientific African2022
Explainable features responsible for the high or low spread of SARS-CoV-2: Africa in view.
Article in Scientific African, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
4 authors.
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Abstract
The low spread of the global pandemic in Africa has raised concerns. Consequently, many commentators have misconstrued concerns suspecting weather, and immunity to be prime reasons. This study investigates the factors associated with the high and low spread of the SARS-CoV-2 (also known as COVID-19) and employs graphical Bayesian models to investigate feature interactions and causality. Through experimentation with the Bayesian framework, we propose that: (i) the proportion of people within the country population who test positive for SARS-CoV-2 and a country's test capacity cause the rate of spread of the virus [i.e., P(S|P) and P(S|T)] (ii) poverty gaps, welfare and freedom of the press directly cause the spread of the virus [i.e., P(S|E), P(S|W), and P(S|R)] (iii) Government effectiveness serves as a parent to poverty gaps and welfare [ i.e., P(E|G) and P(W|G)] and voice and accountability serve as a parent to freedom of the press [i.e., P(R|V)]. For the output, we "dichotomized" regions based on the "share of global infection rate" metric (SGIR) that implicitly accounts for a given region's population, and we find that - out of two hundred and nineteen countries investigated, one hundred and twenty-seven have SGIR ≥ 1%, and the majority (44 out 58 - 75.86%) of Africa countries (as of 12
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