Modeling the transmission dynamics of COVID-19 with genetically resistant humans

Abstract

The emergence of a coronavirus disease (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus (SARS-COV 2) has caused an unprecedented global societal and public health crisis. A mathematical model that incorporates an individual’s ability to resist COVID-19 infection is considered to study the dynamics of COVID-19. Detection and testing for COVID-19 in individuals who has ability to resist the infection, proper preventive measures, and timely medical care are essential in managing and controlling COVID-19 outbreak. These allows us to make quantifiable predictions about the effects of testing utilization on the COVID-19 prevalence. First, we analyze the disease-free state of the COVID-19 model, calculate the baseline control reproduction number, and obtain the local stability of disease-free equilibrium. The model is calibrated using data obtained from Nigeria Centre for Disease Control and key parameters of the model are estimated. Sensitivity analysis is carried out to investigate the influence of the parameters in curtailing the disease. Numerical simulations are then used to explore the behavior of the model solutions involving the novel variable (genetically resistant humans) and control measures. Our results suggest that strict intervention effort (early detection of genetically resistant individuals, testing and isolation of the infected individuals) is required for quick suppression of the disease.