Watch: How predictive modeling could help us reopen more safely

By | May 14, 2020
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Increasingly specific social distancing questions are weighing on states and municipalities as they inch toward relaxing COVID-19 restrictions. Now, a team of computer science and medical researchers based at U-M is working on a tool that could provide more precise answers.

The team is mashing up census data, virus transmission rates, and decades of social science research to create a customizable prototype that can visually model an individual household. They hope to make an open-source version available within the next few months, enabling decision makers to evaluate how proposed policies would affect virus transmission rates in different types of households.

“We want to give policymakers the power to ask ‘what-if’ questions about the effects of specific policies and actions, before they’re implemented,” said Nikola Banovic, assistant professor of electrical engineering and computer science. “By trying out dozens or hundreds of possible interventions in a simulation, we could much more quickly find policies that would keep people safe while minimizing disruption to daily life.”

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