Estimation of the probability of reinfection with COVID-19 coronavirus by the SEIRUS model

Alexander Okhuese Victor

A recent study by Victor (2020) , Nesteruk (2020) and Ming and Zhang (2020) focuses on the epidemic outbreak cased by COVID-19 coronavirus due to the global trend of the pandemic with its origin from mainland China. In his study, Nesteruk (2020) used the popular SIR (Susceptible-Infectious-Removed) model to obtain optimal values for the model parameters with the use of statistical approach and hence predicated the number of infected, susceptible and removed persons versus time. This model approach by Nesteruk (2020) has been a major breakthrough in modelling disease control as used by several authors (Ming and Zhang, (2020) and Victor (2020) among others). However, although there exist a global interest in knowing the rate of infection that will occur over time globally, in this study we adopt solutions from Victor (2020) and Victor and Oduwole (2020) for a new deterministic endemic model (Susceptible -Exposed -Infectious -Removed -Undetectable -Susceptible: SEIRUS) originally developed for the control of the prevalence of HIV/AIDS in Africa.