RIT scientists develop method to help epidemiologists map spread of COVID-19
Rochester Institute of Technology scientists have developed a method they believe will help epidemiologists more efficiently predict the spread of the COVID-19 pandemic. Their new study, published in Physica D: Nonlinear Phenomena, outlines a solution to the SIR epidemic model, which is commonly used to predict how many people are susceptible to, infected by, and recovered from viral epidemics.
The method was created by Nathaniel Barlow, associate professor in RIT’s School of Mathematical Sciences, and Steven Weinstein, head of RIT’s Department of Chemical Engineering. They say that by using this solution to the model, epidemiologists can quickly forecast many different scenarios of how COVID-19 could spread based on a variety of variables. Projections produced by mathematical models help public officials make policy decisions about when to impose and lift restrictions aimed at flattening the curve of infection rates.