ArticleVirulence2025
Predicting the evolutionary and epidemiological dynamics of SARS-CoV-2 in South Africa.
Article in Virulence, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Since the outbreak of coronavirus disease 2019 (COVID-19), the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has continuously mutated and evolved, causing several waves of infection. Predicting the evolutionary and epidemiological dynamics of SARS-CoV-2 remains a challenge. This study combines the epidemic data of different variants of SARS-CoV-2 in South Africa to predict their evolutionary and epidemiological dynamics. Based on the susceptible-infectious-recovered-susceptible (SIRS) transmission dynamics, we consider the transmission rate as an evolutionary trait and the disease-deduced mortality and recovery rates as trade-off functions of the trait. Using the adaptive dynamics method, combined with the epidemic data of the five most recent variants in South Africa, we find that South Africa will be continuously invaded and infected by the new mutant strain with a higher transmission rate. In addition, we find that changing the recovery rate by enhancing treatment, for example, will alter the trade-off function and thereby affect the evolutionary dynamics of SARS-CoV-2, which may evolve into a continuously stable strategy. This study is the first to use evolutionary dynamics theory to predict the future evolutionary and epidemiological dynamics of SARS-CoV-2, which is helpful for the government to predict the epidemic dynamics of COVID-19 and to take effective measures in advance, and it is proposed that advancing treatment time and improving treatment efficiency will contribute to disease control.
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