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Modeling COVID-19 in South Africa using a Vaccine Structured Model with Time-Varying Transmission Rates |
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PP: 945-963 |
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doi:10.18576/jsap/150340
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Author(s) |
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Aubrey Ndovie,
Claris Shoko,
Sivasamy Ramasamy,
Olusegun S. Ewemooje,
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Abstract |
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| Since the beginning of COVID-19 in December 2019, the whole world has been under a myriad of public health challenges. South Africa was one of the affected countries in this predicament. Due to the unique characteristics of this virus, including its evolution into new strains, popularly known as variants of concern (VOCs), COVID-19 posed significant challenges to governmental containment efforts. These efforts consisted of mainly non-pharmaceutical interventions (NPIs) and vaccination which essentially must be quantified to inform future pandemic responses. This research uses a stratified compartmental epidemiological model consisting of eight classes that divide the population into vaccinated and non-vaccinated individuals. With the help of ordinary differential equations (ODEs) and time-varying transition rates, the COVID-19 outbreak in South Africa is simulated. By examining data from the post-vaccination phase to the end of the state of emergency, the changes in the transmission rate to government policies and vaccination drives is correlated. Simulations demonstrate that the national vaccination campaign significantly alleviated the impact of Delta and Omicron variants. Hypothetical scenarios show that doubling the vaccination rate would have further reduced the disease burden. The baseline effective reproduction numbers at the four interval starts were 1.2654, 0.74376, 1.4761 and 0.56624, respectively. Compared with the baseline total of 2.1373 million predicted cases, the no-vaccination scenario produced 6.3375 million predicted cases, whereas enhanced vaccination reduced predicted cases to 1.1024 million. This study substantiates that NPIs and vaccination were critical interventions that significantly reduced the spread of COVID-19 and its variants in South Africa. |
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