Modeling Aids Pandemic Decision-Making

Decision-making during the COVID-19 pandemic is fraught with tradeoffs. Business closures suppress transmission but hurt the economy. Mass testing can help contain the virus but strains medical resources.

Özgür Araz is developing models that help officials visualize these pros and cons and make cost-effective decisions that maximize public health. Araz, associate professor of supply chain management and analytics, said his predictive analytics tools improve the public good.

“Through modeling, we can determine how to save more lives by allocating scarce resources to places that need them most at the right time and contributing to effective policies,” he said.

His April 2020 paper in Health Systems and Food Safety and Inspection Service presented a framework for setting up efficient COVID-19 testing sites. It integrates epidemiological and health care delivery models with supply chain management data.

Araz has also published pandemic decision-making models related to school closures, vaccine distribution, social distancing, and ventilator and resource allocation, which can help mitigate the COVID-19 crisis.