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Published in: BMC Public Health 1/2024

Open Access 01-12-2024 | COVID-19 | Research

SARS-CoV-2 incidence monitoring and statistical estimation of the basic and time-varying reproduction number at the early onset of the pandemic in 45 sub-Saharan African countries

Authors: Michael Safo Oduro, Seth Arhin-Donkor, Louis Asiedu, Damazo T. Kadengye, Samuel Iddi

Published in: BMC Public Health | Issue 1/2024

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Abstract

The world battled to defeat a novel coronavirus 2019 (SARS-CoV-2 or COVID-19), a respiratory illness that is transmitted from person to person through contacts with droplets from infected persons. Despite efforts to disseminate preventable messages and adoption of mitigation strategies by governments and the World Health Organization (WHO), transmission spread globally. An accurate assessment of the transmissibility of the coronavirus remained a public health priority for many countries across the world to fight this pandemic, especially at the early onset. In this paper, we estimated the transmission potential of COVID-19 across 45 countries in sub-Saharan Africa using three approaches, namely, \(R_{0}\) based on (i) an exponential growth model (ii) maximum likelihood (ML) estimation and (iii) a time-varying basic reproduction number at the early onset of the pandemic. Using data from March 14, 2020, to May 10, 2020, sub-Saharan African countries were still grappling with COVID-19 at that point in the pandemic. The region’s basic reproduction number (\(R_{0}\)) was 1.89 (95% CI: 1.767 to 2.026) using the growth model and 1.513 (95% CI: 1.491 to 1.535) with the maximum likelihood method, indicating that, on average, infected individuals transmitted the virus to less than two secondary persons. Several countries, including Sudan (\(R_{0}\): 2.03), Ghana (\(R_{0}\): 1.87), and Somalia (\(R_{0}\): 1.85), exhibited high transmission rates. These findings highlighted the need for continued vigilance and the implementation of effective control measures to combat the pandemic in the region. It is anticipated that the findings in this study would not only function as a historical record of reproduction numbers during the COVID-19 pandemic in African countries, but can serve as a blueprint for addressing future pandemics of a similar nature.
Literature
1.
go back to reference Anjorin AA. The coronavirus disease 2019 (COVID-19) pandemic: a review and an update on cases in Africa. Asian Pac J Trop Med. 2020;13(5):199–203.CrossRef Anjorin AA. The coronavirus disease 2019 (COVID-19) pandemic: a review and an update on cases in Africa. Asian Pac J Trop Med. 2020;13(5):199–203.CrossRef
4.
go back to reference Mehtar S, Preiser W, Lakhe NA, Bousso A, TamFum JJM, Kallay O, et al. Limiting the spread of COVID-19 in Africa: one size mitigation strategies do not fit all countries. Lancet Glob Health. 2020;8(7):e881–3.CrossRefPubMedPubMedCentral Mehtar S, Preiser W, Lakhe NA, Bousso A, TamFum JJM, Kallay O, et al. Limiting the spread of COVID-19 in Africa: one size mitigation strategies do not fit all countries. Lancet Glob Health. 2020;8(7):e881–3.CrossRefPubMedPubMedCentral
6.
7.
go back to reference Zhang S, Diao M, Yu W, Pei L, Lin Z, Chen D. Estimation of the reproductive number of novel coronavirus (COVID-19) and the probable outbreak size on the Diamond Princess cruise ship: A data-driven analysis. Int J Infect Dis. 2020;93:201–4.CrossRefPubMedPubMedCentral Zhang S, Diao M, Yu W, Pei L, Lin Z, Chen D. Estimation of the reproductive number of novel coronavirus (COVID-19) and the probable outbreak size on the Diamond Princess cruise ship: A data-driven analysis. Int J Infect Dis. 2020;93:201–4.CrossRefPubMedPubMedCentral
8.
10.
go back to reference Chowdhury R, Heng K, Shawon MSR, Goh G, Okonofua D, Ochoa-Rosales C, et al. Dynamic interventions to control COVID-19 pandemic: a multivariate prediction modelling study comparing 16 worldwide countries. Eur J Epidemiol. 2020;35:389–99.CrossRefPubMedPubMedCentral Chowdhury R, Heng K, Shawon MSR, Goh G, Okonofua D, Ochoa-Rosales C, et al. Dynamic interventions to control COVID-19 pandemic: a multivariate prediction modelling study comparing 16 worldwide countries. Eur J Epidemiol. 2020;35:389–99.CrossRefPubMedPubMedCentral
11.
go back to reference Hens N, Shkedy Z, Aerts M, Faes C, Van Damme P, Beutels P. Modeling infectious disease parameters based on serological and social contact data: a modern statistical perspective, vol. 63. Springer Science & Business Media; 2012. Hens N, Shkedy Z, Aerts M, Faes C, Van Damme P, Beutels P. Modeling infectious disease parameters based on serological and social contact data: a modern statistical perspective, vol. 63. Springer Science & Business Media; 2012.
12.
go back to reference Alimohamadi Y, Taghdir M, Sepandi M. Estimate of the basic reproduction number for COVID-19: a systematic review and meta-analysis. J Prev Med Public Health. 2020;53(3):151.CrossRefPubMedPubMedCentral Alimohamadi Y, Taghdir M, Sepandi M. Estimate of the basic reproduction number for COVID-19: a systematic review and meta-analysis. J Prev Med Public Health. 2020;53(3):151.CrossRefPubMedPubMedCentral
13.
go back to reference Liu Y, Gayle AA, Wilder-Smith A, Rocklöv J. The reproductive number of COVID-19 is higher compared to SARS coronavirus. J Travel Med. 2020. Liu Y, Gayle AA, Wilder-Smith A, Rocklöv J. The reproductive number of COVID-19 is higher compared to SARS coronavirus. J Travel Med. 2020.
14.
go back to reference Zhao S, Musa SS, Lin Q, Ran J, Yang G, Wang W, et al. Estimating the unreported number of novel coronavirus (2019-nCoV) cases in China in the first half of January 2020: a data-driven modelling analysis of the early outbreak. J Clin Med. 2020;9(2):388.CrossRefPubMedPubMedCentral Zhao S, Musa SS, Lin Q, Ran J, Yang G, Wang W, et al. Estimating the unreported number of novel coronavirus (2019-nCoV) cases in China in the first half of January 2020: a data-driven modelling analysis of the early outbreak. J Clin Med. 2020;9(2):388.CrossRefPubMedPubMedCentral
15.
17.
go back to reference Nishiura H. Correcting the actual reproduction number: a simple method to estimate R 0 from early epidemic growth data. Int J Environ Res Public Health. 2010;7(1):291–302.CrossRefPubMedPubMedCentral Nishiura H. Correcting the actual reproduction number: a simple method to estimate R 0 from early epidemic growth data. Int J Environ Res Public Health. 2010;7(1):291–302.CrossRefPubMedPubMedCentral
18.
go back to reference Wallinga J, Lipsitch M. How generation intervals shape the relationship between growth rates and reproductive numbers. Proc R Soc B Biol Sci. 2007;274(1609):599–604.CrossRef Wallinga J, Lipsitch M. How generation intervals shape the relationship between growth rates and reproductive numbers. Proc R Soc B Biol Sci. 2007;274(1609):599–604.CrossRef
20.
go back to reference Cori A, Ferguson NM, Fraser C, Cauchemez S. A new framework and software to estimate time-varying reproduction numbers during epidemics. Am J Epidemiol. 2013;178(9):1505–12.CrossRefPubMed Cori A, Ferguson NM, Fraser C, Cauchemez S. A new framework and software to estimate time-varying reproduction numbers during epidemics. Am J Epidemiol. 2013;178(9):1505–12.CrossRefPubMed
21.
go back to reference Fraser C, Cummings DA, Klinkenberg D, Burke DS, Ferguson NM. Influenza transmission in households during the 1918 pandemic. Am J Epidemiol. 2011;174(5):505–14.CrossRefPubMedPubMedCentral Fraser C, Cummings DA, Klinkenberg D, Burke DS, Ferguson NM. Influenza transmission in households during the 1918 pandemic. Am J Epidemiol. 2011;174(5):505–14.CrossRefPubMedPubMedCentral
22.
go back to reference Li Q, Guan X, Wu P, Wang X, Zhou L, Tong Y, et al. Early transmission dynamics in Wuhan, China, of novel coronavirus-infected pneumonia. N Engl J Med. 2020;382(13):1199–207.CrossRefPubMedPubMedCentral Li Q, Guan X, Wu P, Wang X, Zhou L, Tong Y, et al. Early transmission dynamics in Wuhan, China, of novel coronavirus-infected pneumonia. N Engl J Med. 2020;382(13):1199–207.CrossRefPubMedPubMedCentral
23.
go back to reference Han Q, Bragazzi N, Asgary A, Orbinski J, Wu J, Kong JD. Estimation of epidemiological parameters and ascertainment rate from early transmission of COVID-19 across Africa. R Soc Open Sci. 2023;10(9):230316.ADSCrossRefPubMedPubMedCentral Han Q, Bragazzi N, Asgary A, Orbinski J, Wu J, Kong JD. Estimation of epidemiological parameters and ascertainment rate from early transmission of COVID-19 across Africa. R Soc Open Sci. 2023;10(9):230316.ADSCrossRefPubMedPubMedCentral
24.
go back to reference Oshinubi K, Rachdi M, Demongeot J. Analysis of reproduction number R0 of COVID-19 using current health expenditure as gross domestic product percentage (CHE/GDP) across countries. In: Healthcare, vol. 9. MDPI; 2021. p. 1247. Oshinubi K, Rachdi M, Demongeot J. Analysis of reproduction number R0 of COVID-19 using current health expenditure as gross domestic product percentage (CHE/GDP) across countries. In: Healthcare, vol. 9. MDPI; 2021. p. 1247.
25.
go back to reference Demongeot J, Oshinubi K, Rachdi M, Seligmann H, Thuderoz F, Waku J. Estimation of daily reproduction numbers during the COVID-19 outbreak. Computation. 2021;9(10):109.CrossRef Demongeot J, Oshinubi K, Rachdi M, Seligmann H, Thuderoz F, Waku J. Estimation of daily reproduction numbers during the COVID-19 outbreak. Computation. 2021;9(10):109.CrossRef
26.
go back to reference Ofori SK, Schwind JS, Sullivan KL, Cowling BJ, Chowell G, Fung ICH. Transmission dynamics of COVID-19 in Ghana and the impact of public health interventions. Am J Trop Med Hyg. 2022;107(1):175.CrossRefPubMedPubMedCentral Ofori SK, Schwind JS, Sullivan KL, Cowling BJ, Chowell G, Fung ICH. Transmission dynamics of COVID-19 in Ghana and the impact of public health interventions. Am J Trop Med Hyg. 2022;107(1):175.CrossRefPubMedPubMedCentral
27.
go back to reference Youdom SW, Tonnang HE, Choukem SP. Modelling and projections of the COVID-19 epidemic and the potential impact of social distancing in Cameroon. J Public Health Afr. 2021;12(2). Youdom SW, Tonnang HE, Choukem SP. Modelling and projections of the COVID-19 epidemic and the potential impact of social distancing in Cameroon. J Public Health Afr. 2021;12(2).
28.
go back to reference Adekunle AI, Adegboye O, Gayawan E, McBryde E. Is Nigeria really on top of COVID-19? Message from effective reproduction number. Epidemiol Infect. 2020;148:e166.CrossRefPubMed Adekunle AI, Adegboye O, Gayawan E, McBryde E. Is Nigeria really on top of COVID-19? Message from effective reproduction number. Epidemiol Infect. 2020;148:e166.CrossRefPubMed
29.
go back to reference Jacobs ED, Okeke MI. A critical evaluation of Nigeria’s response to the first wave of COVID-19. Bull National Res Cent. 2022;46(1):44. Jacobs ED, Okeke MI. A critical evaluation of Nigeria’s response to the first wave of COVID-19. Bull National Res Cent. 2022;46(1):44.
Metadata
Title
SARS-CoV-2 incidence monitoring and statistical estimation of the basic and time-varying reproduction number at the early onset of the pandemic in 45 sub-Saharan African countries
Authors
Michael Safo Oduro
Seth Arhin-Donkor
Louis Asiedu
Damazo T. Kadengye
Samuel Iddi
Publication date
01-12-2024
Publisher
BioMed Central
Published in
BMC Public Health / Issue 1/2024
Electronic ISSN: 1471-2458
DOI
https://doi.org/10.1186/s12889-024-18184-8

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