MATHEMATICAL MODELLING OF COVID-19 TRANSMISSION DYNAMICS IN NIGERIA WITH CONTROL THROUGH VACCINATION, TREATMENT, AND AWARENESS CAMPAIGNS
DOI:
https://doi.org/10.4314/njt.2025.3692Keywords:
COVID-19 transmission dynamics,, Mathematical modelling, , Vaccination, Treatment, Awareness campaignsAbstract
The COVID-19 pandemic, though significantly reduced by 2023, still poses a risk of resurgence in Nigeria due to suboptimal vaccination uptake and weak adherence to preventive measures. To better understand and strengthen control strategies, this study develops a mathematical model of COVID-19 transmission dynamics with control through awareness campaigns, use of safe vaccines, and treatment of infected individuals. The proposed model is formed using a system of nonlinear ordinary differential equations with eight compartments. Analytical results established the boundedness and positivity of the solution, as well as the existence and stability conditions for both the disease-free and endemic equilibria. The basic reproduction number, derived using the next-generation matrix approach, was greater than one in the absence of interventions but declined below unity when vaccination and awareness coverage improved, indicating potential elimination of the disease. Sensitivity analysis revealed that vaccination completion rate, isolation with treatment, and awareness campaigns are the most influential parameters in reducing transmission. Numerical simulations, based on Nigerian data, showed that without awareness campaigns COVID-19 could persist with high infection levels, while increased vaccination awareness markedly reduced susceptible and infectious populations. Long-term projections further indicated that sustained vaccination, awareness campaigns, and treatment can eradicate the disease. The results of the analysis showed that the proposed controls are effective to eradicate and prevent a resurgence of COVID-19 in Nigeria. Hence, it is recommended that public health awareness, vaccination, and treatment be implemented at full scale for effective disease control.
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