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Impouma B, Carr ALJ, Spina A, Mboussou F, Ogundiran O, Moussana F, Williams GS, Wolfe CM, Farham B, Flahault A, Codeco Tores C, Abbate JL, Coelho FC, Keiser O. Time to death and risk factors associated with mortality among COVID-19 cases in countries within the WHO African region in the early stages of the COVID-19 pandemic. Epidemiol Infect 2022; 150:1-29. [PMID: 35177157 PMCID: PMC9002149 DOI: 10.1017/s095026882100251x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2021] [Revised: 10/03/2021] [Accepted: 11/15/2021] [Indexed: 11/12/2022] Open
Abstract
This study describes risk factors associated with mortality among COVID-19 cases reported in the WHO African region between 21 March and 31 October 2020. Average hazard ratios of death were calculated using weighted Cox regression as well as median time to death for key risk factors. We included 46 870 confirmed cases reported by eight Member States in the region. The overall incidence was 20.06 per 100 000, with a total of 803 deaths and a total observation time of 3 959 874 person-days. Male sex (aHR 1.54 (95% CI 1.31–1.81); P < 0.001), older age (aHR 1.08 (95% CI 1.07–1.08); P < 0.001), persons who lived in a capital city (aHR 1.42 (95% CI 1.22–1.65); P < 0.001) and those with one or more comorbidity (aHR 36.37 (95% CI 20.26–65.27); P < 0.001) had a higher hazard of death. Being a healthcare worker reduced the average hazard of death by 40% (aHR 0.59 (95% CI 0.37–0.93); P = 0.024). Time to death was significantly less for persons ≥60 years (P = 0.038) and persons residing in capital cities (P < 0.001). The African region has COVID-19-related mortality similar to that of other regions, and is likely underestimated. Similar risk factors contribute to COVID-19-associated mortality as identified in other regions.
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Affiliation(s)
- Benido Impouma
- World Health Organization, Regional Office for Africa, Brazzaville, Congo
- Institute of Global Health, University of Geneva, Geneva, Switzerland
| | - Alice L. J. Carr
- Institute of Biomedical and Clinical Science, University of Exeter Medical School, Exeter, UK
| | - Alexander Spina
- University of Exeter Medical School, Heavitree Road, Exeter, UK
| | - Franck Mboussou
- World Health Organization, Regional Office for Africa, Brazzaville, Congo
| | - Opeayo Ogundiran
- World Health Organization, Regional Office for Africa, Brazzaville, Congo
| | - Fleury Moussana
- World Health Organization, Regional Office for Africa, Brazzaville, Congo
| | | | - Caitlin M. Wolfe
- World Health Organization, Regional Office for Africa, Brazzaville, Congo
- College of Public Health, University of South Florida, Tampa, Florida, USA
| | - Bridget Farham
- World Health Organization, Regional Office for Africa, Brazzaville, Congo
| | - Antoine Flahault
- Institute of Global Health, University of Geneva, Geneva, Switzerland
| | | | - Jessica L. Abbate
- UMI TransVIHMI (Institut de Recherche pour le Développement, Institut National de la Santé et de la Recherche Médicale, Université de Montpellier), Montpellier, France
- The GRAPH Network, Geneva, Switzerland
| | | | - Olivia Keiser
- Institute of Global Health, University of Geneva, Geneva, Switzerland
- The GRAPH Network, Geneva, Switzerland
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Impouma B, Roelens M, Williams GS, Flahault A, Codeço CT, Moussana F, Farham B, Hamblion EL, Mboussou F, Keiser O. Measuring Timeliness of Outbreak Response in the World Health Organization African Region, 2017-2019. Emerg Infect Dis 2021; 26:2555-2564. [PMID: 33079032 PMCID: PMC7588517 DOI: 10.3201/eid2611.191766] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
Large-scale protracted outbreaks can be prevented through early detection, notification, and rapid control. We assessed trends in timeliness of detecting and responding to outbreaks in the African Region reported to the World Health Organization during 2017–2019. We computed the median time to each outbreak milestone and assessed the rates of change over time using univariable and multivariable Cox proportional hazard regression analyses. We selected 296 outbreaks from 348 public reported health events and evaluated 184 for time to detection, 232 for time to notification, and 201 for time to end. Time to detection and end decreased over time, whereas time to notification increased. Multiple factors can account for these findings, including scaling up support to member states after the World Health Organization established its Health Emergencies Programme and support given to countries from donors and partners to strengthen their core capacities for meeting International Health Regulations.
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