Quantitative Finance faculty, Professors Erhan Bayraktar and Asaf Cohen, applied their expertise in mathematical modeling to the realm of epidemiology in order to study one of the world’s most pressing issues: how to minimize both loss of life and economic damages during the COVID-19 pandemic.
Together with doctoral candidate April Nellis, Professors Bayraktar and Cohen developed a macroeconomic susceptible-infected-removed (SIR) model to simulate the spread of disease and the effect on the economy under various lockdown scenarios. They present their model as an exit time control problem in which lockdown ends with either the arrival of a vaccine or the achievement of herd immunity. Their results indicate that social distancing and mask usage can help a population reach herd immunity before the arrival of a vaccine while also reducing the mortality rate, length of lockdown, and economic losses.
A synopsis of the researchers’ work was featured in Michigan News. Their original article is available here.