Local modeling

Mathematical modeling and analysis of SARS-Cov-2 disease with reinfection

This article was originally published here

Comput Biol Chem. 2022 Apr 6;98:107678. doi: 10.1016/j.compbiolchem.2022.107678. Online ahead of print.

ABSTRACT

The COVID-19 infection which is still infecting many people around the world and at the same time people recovered after recovery are infecting again. This reinfection of individuals after recovery can worsen the disease in the population with so many challenges for the health sectors. We investigate in the present work by formulating a mathematical model for SARS-CoV-2 with reinfection. We first briefly discuss the formulation of the model with the reinfection assumptions, and then investigate the associated qualitative properties of the model. We show that the reinfection model is locally asymptotically stable when R00≤1, we show that the model is globally asymptotically stable. Additionally, we consider available data on the Pakistan coronavirus to estimate the parameters involved in the model. We show that the proposed model shows a good fit to the infected data. We calculate the basic reproduction number with the numerical value of the estimated and fitted parameters is R0≈1.4962. Additionally, we simulate the model using realistic parameters and present the graphical results. We show that infection can be minimized if realistic parameters (which are sensitive to the basic reproduction number) are taken into account. Further, we observe the model’s prediction for the total number of infected cases in the future fifth layer of COVID-19 in Pakistan which may begin in the second week of February 2022.

PMID:35413580 | DOI:10.1016/j.compbiolchem.2022.107678