Los Alamos National Laboratory and New Mexico Consortium affiliate scientist Alan S. Perelson, along with colleague Ruian Ke, have reviewed the literature on modeling COVID-19 and other infectious diseases. Recently, their review has been published as a paper titled, Mechanistic Modeling of SARS-CoV-2 and Other Infectious Diseases and the Effects of Therapeutics in Clinical Pharmacology and Therapeutics.
Kinetic modeling is the study of the dynamics or rate of change of a process or system to either gain enhanced understanding or predict an outcome. Since the AIDS epidemic, the medical, pharmaceutical, and modeling communities have been looking at kinetic modeling of virus infections and the effects of therapeutics.
This has led to modeling of not only HIV but many other viruses such as hepatitis C virus (HCV), hepatitis B virus and cytomegalovirus, which along with HIV cause chronic diseases, and viruses such as influenza, respiratory syncytial virus, West Nile virus, Zika virus, and severe acute respiratory syndrome coronavirus 2 (SARSCoV-2 or COVID-19), which cause acute (short lived) infections.
In this study, the authors first review the historical development of mathematical models to understand HIV and HCV infections. They look at the effects of treatment by fitting the models to clinical data. Next, they look at the more recent work of applying these models toward understanding the COVID-19 and its treatment. Last, they highlight the important areas where additional modeling can assist in providing insights in the future.
Past viral modeling work has helped gain understanding for many viral infections and given scientists crucial insights into viral pathogenesis and the effects of treatment. This review will hopefully be beneficial in optimizing nonpharmaceutical and pharmaceutical interventions of the coronavirus disease 2019 (COVID-19) pandemic.
To learn more read the entire paper at: Mechanistic Modeling of SARS-CoV-2 and Other Infectious Diseases and the Effects of Therapeutics.