On the dynamics of a COVID-19 model with vaccination and social processes

Following several nations' removal of COVID-19 restrictions, vaccination became the main COVID-19 control measure. Most countries engaged in massive vaccination to curb the disease's spread. Therefore, it is imperative that policymakers understand COVID-19 dynamics and prospective changes amid variances in COVID-19 vaccine coverage, especially in most African countries where vaccine uptake is generally lower than in high-income countries. This study presents a compartmental model for COVID-19, which incorporates dynamic social processes and vaccination. It is assumed that information about the infectious population invokes fear, which in turn influences social distancing and vaccination. Qualitative analysis of the model is carried out by determining its basic reproduction number, steady states, and global sensitivity of some of the parameters relative to the reproduction number. The model is calibrated using COVID-19 data for South Africa for the third and fourth waves. Numerical simulations are used to investigate the effects of vaccination and control measures. Based on the fitted data and simulations, we observed that a disease-free equilibrium state can easily be reached, and deaths can be averted if massive vaccination with a high-efficacy vaccine in combination with non-pharmaceutical interventions is used.