Evidence map›Paper›PMID 33106726›Full record

ArticleWorld development2021

Why is the number of COVID-19 cases lower than expected in Sub-Saharan Africa? A cross-sectional analysis of the role of demographic and geographic factors.

Pierre Nguimkeu, Sosson Tadadjeu

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In one paragraph

Article in World development, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
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43citing papers in PubMed, 1 pooled it
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1 · What the graph read from it

What it found

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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.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

43 citing papers in PubMed, 1 synthesis or guideline pooled it.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

2 authors.

Pierre NguimkeuDepartment of Economics, Andrew Young School of Policy Studies, Georgia State University, 55 Park Place, Atlanta, GA 30303, USA.
Sosson TadadjeuFaculty of Economics and Management, University of Dschang, P.O. Box 96, Dschang, Cameroon.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Unlike initially predicted by WHO, the severity of the novel coronavirus pandemic has remained relatively low in Sub-Saharan Africa, more than two months after the first confirmed cases were identified. In this paper, we analyze the extent to which demographic and geographic factors associated to the disease explain this phenomenon. We use publicly available data from a cross-section of 182 countries worldwide, and we employ a regression analysis that accounts for possible misreporting of COVID-19 cases, as well as a Ramsey-type specification that preserves degree of freedom. We found that proportion of population aged 65+, population density, and urbanization are significantly positively associated with high numbers of active infected cases, while mean temperature around the first quarter (January-March) is negatively associated to this COVID-19 outcome. These factors are those for which Africa has a comparative advantage. In contrast, factors for which Africa has a relative disadvantage, such as income and quality of health care infrastructure, are found to be insignificant predictors of the spread of the pandemic. These results hold even when accounting for possible underreporting, as well as differences in the duration of the epidemic in each country, as measured by the time elapsed since the first confirmed case occurred. We conclude that differences in demographic and geographic characteristics help understand the relatively low progression of the pandemic in sub-Saharan Africa as well as the gap in the number of active cases between this region and the rest of the World. We also found, however, that this gap is insignificant beyond these factors, and is expected to narrow over time as the pandemic evolves. These results provide insights for relevant urban policies and kinds of development planning to consider in the fight against disease spreads of the coronavirus type.

Indexed as

AfricaCOVID-19PandemicRegression analysis

Identifiers

PMID33106726
PMCPMC7577660

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.