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Mathematics of Modeling a Pandemic: The Journey Continues

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    Grzegorz Rempala
    Over the last several weeks many mathematicians, statisticians, and data scientists have found themselves involved with various efforts in response to the public health crisis caused by the COVID-19 pandemic. Did predictive modeling really help with COVID preparedness and decision making? Can we use it to slowly move away from the current measures of social distancing and reopen our economy. Following up on my earlier seminar on the topic, I will try to give a perspective of how various mathematical methods turned out to work (or not) in practical settings of the daily predictions of the pandemic size in Ohio. In particular, I will briefly outline some new ideas and possible improvements in the methodology of "dynamic survival analysis developed by the OSU COVID response team to help predict COVID hospital burden.

    This is a Follow-up on the talk Prof. Rempala gave on March 24, 2020 titled Mathematical Models of Epidemics: Tracking Coronavirus using Dynamic Survival Analysis.

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