MODELING COVID-19 EPIDEMIC TO GUIDE DECISION MAKING

A coronavirus has many crown-like spikes on its surface. Two recent examples of these viruses are SARS-CoV-1 and SARS-CoV-2. The former caused the 2003 outbreak of severe acute respiratory syndrome (SARS), that according to the World Health Organization (WHO), as of July 5, 2013, infected a total of 8,439 people and 812 died worldwide. The latter caused the coronavirus disease 2019 (Covid-19), that the WHO declared a pandemic on March 11, 2020. Unlike the SARS-CoV-1, the SARS-CoV-2 is much more contagious and widespread, and it has adversely affected life in almost every country. The Centers for Disease Control and Prevention (CDC) reported that as of July 24, 2020, there were over 15 million confirmed cases of Covid-19 in the world, among them the US had 4,024,492 cases out of which 72,219 were new cases as of July 25, within a 24-hour period. It reported 143,868 total deaths in the US due to this disease that included 1,113 new deaths during this 24-hour period. Among the US cases, one million new cases were added during July 9-24, 2020, indicating an exponential growth of new Covid-19 cases relative to the timeline of SARS-CoV-1. One way to understand and predict the impact of Covid-19 is to formulate a mathematical model to predict the spread of illness, hospitalization, death, recovery, etc. based on assumptions about the characteristics of the disease and behavior of individuals. Many institutions, universities, and organizations have formulated mathematical models for this purpose. Some notable organizations for this purpose include the Covid-19 Forecast Hub that hosts over 30 international research groups and their models, the CDC, and the FiveThirtyEight (Best & Boice, July 24, 2020; ABC News Internet Ventures, 2020). The purpose of this research is to introduce basic terminology about the spread of infectious diseases and to formulate basic epidemic models to analyze Covid-19 to guide managerial decisions.