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

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, $$R_{0}$$ 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 ($$R_{0}$$ 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 ($$R_{0}$$ R 0 : 2.03), Ghana ($$R_{0}$$ R 0 : 1.87), and Somalia ($$R_{0}$$ 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.

SARS-CoV-2 transmission dynamics in Mozambique and Zimbabwe during the First Three Years of the Pandemic

“…For example, the time-varying reproductive number characterizes virus transmissibility at a particular point in time; this quantity has been estimated using stochastic models coupled with Bayesian inference for France and Ireland [6], Switzerland [32], and Scandinavian countries [19]. Odurro et al [28] used a time varying reproduction estimation approach for sub-Saharan Africa and estimated the time-varying reproductive number while also accounting for depletion of the susceptible population. In addition, a model-inference approach was used to estimate the background population characteristics such as population susceptibility for South Africa [46], the United States at county resolution [34], and India [45].…”