The coronavirus disease 2019 (COVID-19) pandemic started with an outbreak of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Wuhan, Hubei province, China, in December 2019. Since its emergence, several models have been developed to study its transmission dynamics. There is a huge need to have a clear understanding of the evolution of the pandemic across countries.
Study: The basic reproduction number of COVID-19 across Africa. Image Credit: Staraldo/ Shutterstock
This news article was a review of a preliminary scientific report that had not undergone peer-review at the time of publication. Since its initial publication, the scientific report has now been peer reviewed and accepted for publication in a Scientific Journal. Links to the preliminary and peer-reviewed reports are available in the Sources section at the bottom of this article. View Sources
A new study has been published in the medRxiv* preprint server in which scientists used a SEIR model and a Bayesian inference framework to estimate the basic reproduction number of COVID-19 across Africa.
Background
The first case of COVID-19 in Africa was reported in Egypt on February 14, 2020. By the end of October 2021, 47 African countries were affected, with over 6.07 million confirmed cases and over 150,00 deaths. Africa has been regarded as one of the most vulnerable continents due to strong trade links with China and a suboptimal health system.
To understand the transmission dynamics of the disease, several mathematical models have been developed and analyzed. In these models, the basic reproduction number (R0) is used to capture the initial growth rate of a disease in a completely susceptible population. It is the expected number of secondary cases of the disease caused directly by a single infected individual. R0 indicates how contagious a disease is and how fast it will spread.
Due to the uncertain nature of the pandemic, there is a need to understand the evolution of the disease across communities adequately. In the present study, scientists used a susceptible-exposed-infectious-recovered (SEIR) model (with a Bayesian inference framework) to estimate the basic reproduction number (R0) for COVID-19 across Africa. It must be noted that the estimates presented are based on the reported number of COVID-19 cases in African countries before non-pharmaceutical interventions were implemented.
A new study
The SEIR model used in this analysis had four compartments, namely: susceptible (S), exposed (E), infectious (I), and recovered/removed (R). Individuals in the E compartment were assumed not to transmit the disease, while infectious persons in I could transmit at some rate. The infectious compartment I contained both symptomatic and asymptomatic individuals. Scientists assumed that recovered individuals did not get re-infected during the epidemic period that was considered.
Data on daily cases of COVID-19 for each country from the publicly available data set on the GitHub page of “Our World in Data” were obtained. The countries considered in this study were selected based on the availability of data. Twenty-four countries were selected and divided into the following regions: West African, Southern African, North African, and East African. Only the first few days of the epidemic were considered to capture the evolution of disease at the early stage of the outbreak.
Main findings
R0 for Nigeria (in Western Africa) was estimated to be 3.86, while that for Ghana was 5.91, probably because the rise in the number of cases in Ghana was much higher during the first fifteen days. The estimated basic reproduction number for Senegal was R0 = 3.78, while that for Mali was 3.98.
In the case of the Southern African countries, the R0 for South Africa was estimated to be 7.02. This was followed by Zambia with R0 = 2.59 and Namibia with R0 = 2.37. The reproduction number for Malawi was 2.16. The ordering reflected the current known situation in that, as of September 30, 2021, South Africa had the highest number of (2,902,672), followed by Zambia (209,046), Namibia (127,589), and Malawi (61,580).
In North Africa, the largest basic reproduction number was estimated for Morocco (3.92), followed by Tunisia (3.87), Algeria (3.31), and Egypt (2.72). Similar results were obtained for East African countries. Sudan had the smallest reproduction number (1.98), followed by Ethiopia (2.55), Kenya (3.77), and Rwanda (4.04).
Among the Central African countries considered, Cameroon had an R0 of 3.74, Chad (2.03), Gabon (2.37), and the Republic of the Congo (2.54). Among these countries, Cameroon was the first to have a COVID-19 case, followed by the Republic of the Congo, Gabon, and Chad. Among the African island countries, Madagascar (4.97) and Mauritius (9.66) had the highest reproduction numbers.
Conclusion
The COVID-19 pandemic continues to spread in an uncertain manner worldwide despite the availability of vaccines. More research is needed to adequately understand the transmission dynamics of the virus and its variants. In this study, scientists used a SEIR model (with a Bayesian inference framework) to estimate the basic reproduction number of COVID-19 in selected African countries based on the number of cases during the early stages of their epidemic before major non-pharmaceutical interventions were implemented. The R0 estimates could be used by public health officers to plan and map out strategies to combat the pandemic adequately.
This news article was a review of a preliminary scientific report that had not undergone peer-review at the time of publication. Since its initial publication, the scientific report has now been peer reviewed and accepted for publication in a Scientific Journal. Links to the preliminary and peer-reviewed reports are available in the Sources section at the bottom of this article. View Sources
Article Revisions
- May 8 2023 - The preprint preliminary research paper that this article was based upon was accepted for publication in a peer-reviewed Scientific Journal. This article was edited accordingly to include a link to the final peer-reviewed paper, now shown in the sources section.