Abstract
The COVID-19 pandemic has had a considerable impact on global health and economics. The impact in African countries has not been investigated thoroughly via fitting epidemic models to the reported COVID-19 deaths. We downloaded the data for the 12 most-affected countries with the highest cumulative COVID-19 deaths to estimate the time-varying basic reproductive number (R(t)) and infection attack rate. We develop a simple epidemic model and fitted it to reported COVID-19 deaths in 12 African countries using iterated filtering and allowing a flexible transmission rate. We observe high heterogeneity in the case-fatality rate across the countries, which may be due to different reporting or testing efforts. South Africa, Tunisia, and Libya were most affected, exhibiting a relatively higher R(t) and infection attack rate. Thus, to effectively control the spread of COVID-19 epidemics in Africa, there is a need to consider other mitigation strategies (such as improvements in socioeconomic well-being, healthcare systems, the water supply, and awareness campaigns).
Original language | English |
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Article number | 32 |
Pages (from-to) | 1-16 |
Number of pages | 16 |
Journal | Bulletin of Mathematical Biology |
Volume | 84 |
Issue number | 3 |
DOIs | |
Publication status | Published - Mar 2022 |
Keywords
- Attack rate
- Pandemic
- Reproduction number
- SARS-CoV-2
- Seroprevalence
ASJC Scopus subject areas
- General Neuroscience
- Immunology
- General Mathematics
- General Biochemistry,Genetics and Molecular Biology
- General Environmental Science
- Pharmacology
- General Agricultural and Biological Sciences
- Computational Theory and Mathematics