Mathematics Colloquium: Inferring Distributions of COVID-Positive Individuals from Wastewater Tests on a College Campus
Inferring Distributions of COVID-Positive Individuals from Wastewater Tests on a College Campus
Dr. Nathan Cahill
Director, Mathematical Modeling Ph.D. Program
Associate Professor, School of Mathematical Sciences, RIT
We will show, in the case of RIT’s current 16 wastewater sampling sites, how this Bayesian Network inference strategy can yield important information that could help health officials decide on further coronavirus testing and mitigation strategies.
Abstract:
As a part of its overall strategy for monitoring the level of COVID-19 infection on campus, RIT is testing wastewater for traces of coronavirus on a twice weekly basis. Viral RNA is shed when people use the bathroom, and this shedding can occur well before individuals with coronavirus may become symptomatic. Therefore, monitoring changes in coronavirus levels in wastewater from particular areas on campus can help health officials develop strategies for further testing and enhanced mitigation efforts. In this talk, we discuss the problem of predicting (inferring) the number of COVID-infected individuals in an area based on the results of wastewater testing. In a simplified scenario where wastewater is collected from a single location, this prediction can be done by exploiting Bayes Theorem, a topic taught in undergraduate probability classes. In the more complicated scenario where wastewater is collected from multiple locations, some of which may be upstream or downstream of each other, this prediction can be done with the help of a Bayesian Network that models the causal relationships between the multiple sampling sites and the populations whose wastewater flows through these sites. We will show, in the case of RIT’s current 16 wastewater sampling sites, how this Bayesian Network inference strategy can yield important information that could help health officials decide on further coronavirus testing and mitigation strategies.
Speaker Bio:
Nathan Cahill is an Associate Professor of Mathematical Sciences and the Director of the PhD Program in Mathematical Modeling at RIT. He earned BS and MS degrees in Applied Mathematics at RIT, attained the rank of Principal Scientist at Eastman Kodak and Carestream Health where he was granted 26 US patents, and earned a DPhil in Engineering Science from the University of Oxford. In 2009, he returned to his RIT roots and joined the faculty of the School of Mathematical Sciences, where he carries out research in overlapping areas between computational mathematics, mathematical modeling, computer science, and engineering. He is a SIAM Member, an IEEE Senior Member, and a SPIE Rising Researcher.
Intended Audience:
All are welcome. Those with interest in the topic.
This event is co-sponsored by the Fram Chair in Critical Thinking.
Event Snapshot
When and Where
Who
This is an RIT Only Event
Interpreter Requested?
No