“Minimizing the dramatic effects of the pandemic on society is of utmost importance which is why MIDAS funded this extremely meaningful project.”

-H.V. Jagadish, Director, MIDAS

Markovian And Non-Markovian (Discrete) Spatio-Temporal Processes with Active Decision Making Strategies For Addressing The COVID-19 Pandemic

Drs. Moulinath Banerjee and Ya’acov Ritov, Professors of Statistics, are developing cutting-edge statistical models that incorporate many complex features of the pandemic, including people‚Äôs mobility patterns, testing capacity and pressure on the healthcare system, and last but not least, active decision making strategies as the epidemic evolves. Their model will help policymakers understand both the short-term and long-term impact of the pandemic on human health and on the economy.

The MIDAS COVID-19 Propelling Original Data Science (PODS) grants were awarded on May 13th, 2020, each of the 7 teams received funding of up to $30,000 with projects starting immediately and expected to finish by the end of 2020. These projects demonstrate the resolve, expertise, and creativity of U-M data scientists facing a public health crisis. To learn more about the other projects please visit our COVID-19 PODS awards page.

We are challenged by the coronavirus and hope to minimize the dramatic effects of the pandemic on society, from the children to the elderly, from the have to the have-nots, from the healthy to those at risk. Our goal is to understand the dynamics of the current COVID-19 pandemic as well as explore appropriate control strategies for minimizing its impact on society, both in terms of human and fiscal costs. Our approach is rooted in the maxim that the core of understanding reality lies in its abstraction and a solid theoretical formulation of its underpinning mechanisms. - Ya'acov Ritov