Mathematical model and interpretation of crowding effects on SARS-CoV-2 using Atangana-Baleanu fractional operator

The novel coronavirus disease (COVID-19) outbreak, which infects a normal person through droplets of infected person and has its route via mouth, eyes, nose, or hands is caused by Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2). Coronavirus causes severe infections that include acute respiratory distress syndrome, acute lung injury, and various others. SARS-CoV-2 infection activates innate and adaptive immune responses, but uncontrolled, inflammatory, and impaired responses lead to harmful tissue damage. Crowding is the major factor involved in the increasing trend in COVID-19 cases. Modeling of this effect will help in predicting the effects of overcrowding on the overall population. In this chapter, we define a model depicting the crowding effects of SARS-CoV-2 virus and examine the existence and uniqueness of the results involving Atangana-Baleanu fractional operator using a fixed-point method. We then interpret the model explaining its significance.