Presenter: Christian Riordan
Authors: Christian Riordan
Faculty Advisor: Rajnish Kumar
Institution: Dixie State University
Since its emergence in December 2019, coronavirus disease 2019 (COVID-19) has impacted several countries, affecting more than 240,000,000 people worldwide (World Health Organization) and making it a global public threat. Covid 19 is mainly transmitted and spread between people who are in close contact with each other, typically one metre (Nazario). Due to the rapid spread and the deadly consequences of those that come with contracting Covid-19 it is important to know the individual risk that one faces everyday. Several studies show that there are variable factors that play a role in the likelihood of an individual contracting Covid 19, these factors include age, sex, race, location, and sociodemographic (Anderson, Rozenfield). Also we can make predictions based off of chest x-rays. Using X-ray imaging and infection rate data collected from multiple US states coupled with statistics of given factors we are able to use linear regression to predict the likelihood of an individual contracting the disease. We have developed a mathematical model incorporating variable factors and utilized linear regression to simulate an individual’s likelihood of contracting Covid 19.