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AN IN-DEPTH STATISTICAL ANALYSIS OF THE COVID-19 PANDEMIC’S INITIAL SPREAD IN THE WHO AFRICAN REGION
James, Ananthu et al. | Date Issued: 2022
Author
James, Ananthu
Dalal, Jyoti
Kousi, Timokleia
Vivacqua, Daniela
Câmara, Daniel Cardoso Portela
Reis, Izabel Cristina Dos
Mesa, Sara Botero
Ng’ambi, Wignston
Ansobi, Papy
Bianchi, Lucas M
Lee, Theresa M
Ogundiran, Opeayo
Stoll, Beat
Chimbetete, Cleophas
Mboussou, Franck
Impouma, Benido
Hofer, Cristina Barroso
Coelho, Flávio Codeço
Keiser, Olivia
Abbate, Jessica Lee
Affilliation
Department of Chemical Engineering, Indian Institute of Science, Bangalore, Karnataka, India /The Global Research and Analysis for Public Health (GRAPH) Network, Association Actions en Santé, Geneva, Switzerland.
The Global Research and Analysis for Public Health (GRAPH) Network, Association Actions en Santé, Geneva, Switzerland.
The Global Research and Analysis for Public Health (GRAPH) Network, Association Actions en Santé, Geneva, Switzerland / Institute of Global Health, Faculty of Medicine, University of Geneva, Geneva, Switzerland.
The Global Research and Analysis for Public Health (GRAPH) Network, Association Actions en Santé, Geneva, Switzerland / Universidade Federal do Rio de Janeiro. Instituto de Puericultura e Pediatria Martagão Gesteira. Rio de Janeiro, RJ, Brasil.
The Global Research and Analysis for Public Health (GRAPH) Network, Association Actions en Santé, Geneva, Switzerland / Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Mosquitos Transmissores de Hematozoários. Rio de Janeiro, RJ, Brasil / Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Núcleo Operacional Sentinela de Mosquitos Vetores (NOSMOVE). Rio de Janeiro, RJ, Brasil / World Health Organization Regional Office for Africa, Brazzaville, Congo.
The Global Research and Analysis for Public Health (GRAPH) Network, Association Actions en Santé, Geneva, Switzerland / Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laborat[orio de Mosquitos Transmissores de Hematozoários. Rio de Janeiro, RJ, Brasil. Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Núcleo Operacional Sentinela de Mosquitos Vetores (NOSMOVE). Rio de Janeiro, RJ, Brasil.
The Global Research and Analysis for Public Health (GRAPH) Network, Association Actions en Santé, Geneva, Switzerland / Institute of Global Health, Faculty of Medicine, University of Geneva, Geneva, Switzerland.
The Global Research and Analysis for Public Health (GRAPH) Network, Association Actions en Santé, Geneva, Switzerland / Institute of Global Health, Faculty of Medicine, University of Geneva, Geneva, Switzerland / Health Economics Policy Unit, Department of Health Systems and Policy, Kamuzu University of Health Sciences, Lilongwe, Malawi.
The Global Research and Analysis for Public Health (GRAPH) Network, Association Actions en Santé, Geneva, Switzerland / Research and Training Unit in Ecology and Control of Infectious Diseases (URF-ECMI), Faculty of Medicine, University of Kinshasa, Kinshasa, Democratic Republic of the Congo.
The Global Research and Analysis for Public Health (GRAPH) Network, Association Actions en Santé, Geneva, Switzerland / World Health Organization Regional Office for Africa, Brazzaville, Congo / Fundação Oswaldo Cruz. Escola Nacional de Saúde Pública Sergio Arouca. Rio de Janeiro, RJ, Brasil.
World Health Organization Regional Office for Africa, Brazzaville, Congo.
World Health Organization Regional Office for Africa, Brazzaville, Congo.
Institute of Global Health, Faculty of Medicine, University of Geneva, Geneva, Switzerland.
The Global Research and Analysis for Public Health (GRAPH) Network, Association Actions en Santé, Geneva, Switzerland / Newlands Clinic, Harare, Zimbabwe.
World Health Organization Regional Office for Africa, Brazzaville, Congo.
World Health Organization Regional Office for Africa, Brazzaville, Congo.
The Global Research and Analysis for Public Health (GRAPH) Network, Association Actions en Santé, Geneva, Switzerland / Universidade Federal do Rio de Janeiro. Instituto de Puericultura e Pediatria Martagão Gesteira. Rio de Janeiro, RJ, Brasil.
The Global Research and Analysis for Public Health (GRAPH) Network, Association Actions en Santé, Geneva, Switzerland / School of Applied Mathematics, Getulio Vargas Foundation, Rio de Janeiro, Brazil.
The Global Research and Analysis for Public Health (GRAPH) Network, Association Actions en Santé, Geneva, Switzerland / Institute of Global Health, Faculty of Medicine, University of Geneva, Geneva, Switzerland.
The Global Research and Analysis for Public Health (GRAPH) Network, Association Actions en Santé, Geneva, Switzerland / World Health Organization Regional Office for Africa, Brazzaville, Congo / UMI TransVIHMI (Institut de Recherche pour le Développement Institut National de la Santé et de la Recherche Médicale Université de Montpellier), Montpellier, France / Geomatys, Montpellier, France.
Abstract
During the first wave of the COVID-19 pandemic, sub-Saharan African countries experienced comparatively lower rates of SARS-CoV- 2 infections and related deaths than in other parts of the world, the reasons for which remain unclear. Yet, there was also considerable variation between countries. Here, we explored potential drivers of this variation among 46 of the 47 WHO African region Member States in a cross-sectional study. We described five indicators of early COVID-19 spread and severity for each country as of 29 November 2020: delay in detection of the first case, length of the early epidemic growth period, cumulative and peak attack rates and crude case fatality ratio (CFR). We tested the influence of 13 pre-pandemic and pandemic response predictor variables on the country-level variation in the spread and severity indicators using multivariate statistics and regression analysis. We found that wealthier African countries, with larger tourism industries and older populations, had higher peak (p<0.001) and cumulative (p<0.001) attack rates, and lower CFRs (p=0.021). More urbanised countries also had higher attack rates (p<0.001 for both indicators). Countries applying more stringent early control policies experienced greater delay in detection of the first case (p<0.001), but the initial propagation of the virus was slower in relatively wealthy, touristic African countries (p=0.023). Careful and early implementation of strict government policies were likely pivotal to delaying the initial phase of the pandemic, but did not have much impact on other indicators of spread and severity. An over-reliance on disruptive containment measures in more resource-limited contexts is neither effective nor sustainable. We thus urge decision-makers to prioritise the reduction of resource-based health disparities, and surveillance and response capacities in particular, to ensure global resilience against future threats to public health and economic stability.
Keywords in Portuguese
COVID-19
Análise estatística
Propagação inicial da pandemia
Região africana da OMS
 
Keywords
COVID-19
Statistical analysis
Pandemic’s initial spread
WHO African region
 
Publisher
BMJ Open
Citation
JAMES, Ananthu et al. An in-depth statistical analysis of the COVID-19 pandemic’s initial spread in the WHO African region. BMJ Global Health v. 7, e007295, p. 1-10, Feb. 2022.
DOI
10.1136/ bmjgh-2021-007295
ISSN
2059-7908