UNDERSTANDING COVID-19 DYNAMICS THROUGH MATHEMATICAL MODELS: THE INFLUENCE OF FEAR

The fear associated with an infectious disease plays a major role in the management of the infectious disease. Thus, this study tried to assess the impact of fear of infection on the spread of COVID-19 using a mathematical modelling approach. The model considered was shown to have two equilibria points, namely, the COVID-19 free equilibrium (CFE) and the COVID-19 persistent equilibrium (CPE). The computed reproduction number ( RC1) was used to validate the local stability of the CPE whenever RC1 is above one while the CFE is globally asymptotically stable RC1 1. Next, we show that the condition RC1 1 is sufficient to halt the spread of COVID-19 by showing that the model possesses forward bifurcation. The sensitivity analysis suggests that the fear of infection does not influence the RC1 while numerical simulation indicates that the population of all infected humans, COVID-19 deceased individuals and the concentration of the COVID-19 viruses in the environment increases as the fear of infection (1) reduces.