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An in-depth statistical analysis of the COVID-19 pandemic's initial spread in the WHO African region
Ananthu James; Jyoti Dalal; Timokleia Kousi; Daniela Vivacqua; Daniel Cardoso Portela Camara; Izabel Cristina dos Reis; Sara Botero-Mesa; Wingston Ng'ambi; Papy Ansobi; Beat Stoll; Cleophas Chimbetete; Franck Mboussou; Benido Impouma; Cristina Barroso Hofer; Flavio Codeco Coelho; Olivia Keiser; Jessica L Abbate.
Afiliação
  • Ananthu James; Indian Institute of Science, Bangalore; The Global Research and Analysis for Public Health (GRAPH) Network (https://thegraphnetwork.org), Association Actions en
  • Jyoti Dalal; The Global Research and Analysis for Public Health (GRAPH) Network (https://thegraphnetwork.org), Association Actions en Sante, Geneve, Switzerland
  • Timokleia Kousi; Institute of Global Health, Faculty of Medicine, University of Geneva, Geneva, Switzerland; The Global Research and Analysis for Public Health (GRAPH) Network (
  • Daniela Vivacqua; Department of Pediatric Infectious Diseases, UFRJ, Rio de Janeiro, Brazil; The Global Research and Analysis for Public Health (GRAPH) Network (https://thegraphn
  • Daniel Cardoso Portela Camara; Nucleo Operacional Sentinela de Mosquitos Vetores - NOSMOVE, Fundacao Oswaldo Cruz, Rio de Janeiro, Brazil; The Global Research and Analysis for Public Health (
  • Izabel Cristina dos Reis; Nucleo Operacional Sentinela de Mosquitos Vetores - NOSMOVE, Fundacao Oswaldo Cruz, Rio de Janeiro, Brazil; The Global Research and Analysis for Public Health (
  • Sara Botero-Mesa; Institute of Global Health, Faculty of Medicine, University of Geneva, Geneva, Switzerland; The Global Research and Analysis for Public Health (GRAPH) Network (
  • Wingston Ng'ambi; Health Economics Policy Unit, Department of Health Systems and Policy, College of Medicine, University of Malawi, Lilongwe, Malawi
  • Papy Ansobi; Research and Training Unit in Ecology and Control of Infectious Diseases (URF-ECMI), Faculty of Medicine, University of Kinshasa, Kinshasa, Republic Democratic
  • Beat Stoll; Institute of Global Health, Faculty of Medicine, University of Geneva, Geneva, Switzerland
  • Cleophas Chimbetete; Newlands Clinic, Harare, Zimbabwe
  • Franck Mboussou; World Health Organization, Regional Office for Africa, Brazzaville, Congo
  • Benido Impouma; World Health Organization, Regional Office for Africa, Brazzaville, Congo
  • Cristina Barroso Hofer; Department of Pediatric Infectious Diseases, UFRJ, Rio de Janeiro, Brazil; The Global Research and Analysis for Public Health (GRAPH) Network (https://thegraphn
  • Flavio Codeco Coelho; School of Applied Mathematics, Getulio Vargas Foundation, Rio de Janeiro, Brazil; The Global Research and Analysis for Public Health (GRAPH) Network (https://th
  • Olivia Keiser; Institute of Global Health, Faculty of Medicine, University of Geneva, Geneva, Switzerland; The Global Research and Analysis for Public Health (GRAPH) Network (
  • Jessica L Abbate; UMI TransVIHMI (Institut de Recherche pour le Developpement, Institut National de la Sante et de la Recherche Medicale, Universite de Montpellier), Montpellier,
Preprint em En | PREPRINT-MEDRXIV | ID: ppmedrxiv-21262401
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 World Health Organization 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 urbanized 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 prioritize 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. Summary BoxO_ST_ABSWhat is already known on this topic?C_ST_ABSO_LICOVID-19 trajectories varied widely across the world, and within the African continent. C_LIO_LIThere is significant heterogeneity in the surveillance and response capacities among WHO African region member states. C_LI What are the new findings?O_LICumulative and peak attack rates during the first wave of COVID-19 were higher in WHO African region member states with higher per-capita GDP, larger tourism industries, older and more urbanized populations, and higher pandemic preparedness scores. C_LIO_LIAlthough better-resourced African countries documented higher attack rates, they succeeded in limiting rapid early spread and mortalities due to COVID-19 infection. C_LIO_LIAfrican countries that had more stringent early COVID-19 response policies managed to delay the onset of the outbreak at the national level. However, this phenomenon is partially explained by a lack of detection capacity, captured in low pandemic preparedness scores, and subsequent initial epidemic growth rates were slower in relatively well-resourced countries. C_LI What do the new findings imply?Careful implementation of strict government policies can aid in delaying an epidemic, but investments in public health infrastructure and pandemic preparedness are needed to better mitigate its impact on the population as a whole.
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Texto completo: 1 Coleções: 09-preprints Base de dados: PREPRINT-MEDRXIV Tipo de estudo: Observational_studies / Prognostic_studies / Rct Idioma: En Ano de publicação: 2021 Tipo de documento: Preprint
Texto completo: 1 Coleções: 09-preprints Base de dados: PREPRINT-MEDRXIV Tipo de estudo: Observational_studies / Prognostic_studies / Rct Idioma: En Ano de publicação: 2021 Tipo de documento: Preprint