COVID-19 Transmission Dynamics and the Impact of Vaccination: Modelling, Analysis and Stimulations

dc.contributor.authorMalinzi, Joseph
dc.contributor.authorJuma, Victor Ogesa
dc.contributor.authorMadubueze, Chinwendu Emilian
dc.contributor.authorMwaonanji, John
dc.contributor.authorNkem, Godwin Nwachukwu
dc.contributor.authorMwakilama, Elias
dc.contributor.authorMupedza, Tinashe Victor
dc.contributor.authorChiteri, Vincent Nandwa
dc.contributor.authorBakare, Emmanuel Afolabi
dc.contributor.authorMoyo, Emmanuel Afolabi
dc.contributor.authorFunollet, Eduard Campillo
dc.contributor.authorNyabadza, Farai
dc.contributor.authorMadzvamuse, Anotida
dc.date.accessioned2025-02-10T13:16:40Z
dc.date.available2025-02-10T13:16:40Z
dc.date.issued2023
dc.descriptionJournal Article
dc.description.abstractDespite the lifting of COVID-19 restrictions, the COVID-19 pandemic and its effects remain a global challenge including the sub-Saharan Africa (SSA) region. Knowledge of the COVID-19 dynamics and its potential trends amidst variations in COVID-19 vaccine coverage is therefore crucial for policy makers in the SSA region where vaccine uptake is generally lower than in high-income countries. Using a compartmental epidemiological model, this study aims to forecast the potential COVID-19 trends and determine how long a wave could be, taking into consideration the current vaccination rates. The model is calibrated using South African reported data for the first four waves of COVID-19, and the data for the fifth wave are used to test the validity of the model forecast. The model is qualitatively analysed by determining equilibria and their stability, calculating the basic reproduction number R0 and investigating the local and global sensitivity analysis with respect to R0. The impact of vaccination and control interventions are investigated via a series of numerical simulations. Based on the fitted data and simulations, we observed that massive vaccination would only be beneficial (deaths averting) if a highly effective vaccine is used, particularly in combination with nonpharmaceutical interventions. Furthermore, our forecasts demonstrate that increased vaccination coverage in SSA increases population immunity leading to low daily infection numbers in potential future waves. Our findings could be helpful in guiding policy makers and governments in designing vaccination strategies and the implementation of other COVID-19 mitigation strategies.
dc.identifier.citationMalinzi, J., Juma, V., Madubueze, C., Mwaonanji, J., Nkem, G., Mwakilama, E., Mupedza, T., Nandwa, V., Bakare, E., Linda-Zulu, I., Moyo, Campillo-Funollet, E., Nyabadza, F., Madzvamuse, A., & Pleasant, M. (2023). COVID-19 transmission dynamics and the impact of vaccination: modelling, analysis and simulations. Royal Society Open Science. 10. 221656. 10.1098/rsos.221656.
dc.identifier.urihttps://repository.daystar.ac.ke/handle/123456789/6250
dc.language.isoen
dc.publisherRoyal Society Publishing
dc.subjectCOVID-19
dc.subjectvaccinations
dc.subjectmathematical modelling
dc.subjectparameter estimation
dc.subjectsensitivity analysis
dc.subjectbifurcation analysis
dc.titleCOVID-19 Transmission Dynamics and the Impact of Vaccination: Modelling, Analysis and Stimulations
dc.typeArticle

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