A Mathematical Model of COVID-19 Transmission
Abstract
Disease transmission is studied through disciplines like epidemiology, applied mathematics, and statistics. Mathematical simulation models for transmission have implications in solving public and personal health challenges. The SIR model uses a compartmental approach including dynamic and nonlinear behavior of transmission through three factors: susceptible, infected, and removed (recovered and deceased) individuals. Using the Lambert W Function, we propose a framework to study solutions of the SIR model. This demonstrates the applications of COVID-19 transmission data to model the spread of a real-world disease. Different models of disease including the SIR, SIRmp and SEIRpqr model are compared with respect to their ability to predict disease spread. Physical distancing impacts and personal protection equipment use are discussed with relevance to the COVID-19 spread.
Keywords
Cite
@article{arxiv.2105.11626,
title = {A Mathematical Model of COVID-19 Transmission},
author = {R. Jayatilaka and R. Patel and M. Brar and Y. Tang and N. M. Jisrawi and F. Chishtie and J. Drozd and S. R. Valluri},
journal= {arXiv preprint arXiv:2105.11626},
year = {2022}
}
Comments
12 pages, NN20 Conference proceedings, published version