The Centers for Disease Control and Prevention will host a webinar at 10 a.m. May 20 with Dr. Arni Rao, director of the Laboratory for Theory and Mathematical Modeling in the Medical College of Georgia.
The webinar is titled “Innovations in Mathematical Modeling for Describing Epidemics and Providing Time-Sensitive Recommendations: Experiences from HCV, HIV and COVID-19.”
“This talk is about our new mathematical innovations done during the past 20 years to handle various epidemics such as HCV, HIV, bird flu and COVID-19,” Rao said. “These innovations didn’t stop at publications in top journals of mathematics and medicine, but were also able to bring policy changes, bring political commitments and introduce new policies in managing and controlling the epidemics.”
As COVID-19 began spreading across the United States, Rao developed a mathematical model and algorithm to help health organizations track its spread. His previous work has helped predict the spread of HIV and avian influenza.
Rao was the leading co-editor of two volumes of the Handbook of Statistics. His research focuses on the development of novel mathematical modeling and theories as applied to biology and biomedicine. In addition, he founded the Laboratory for Theory and Mathematical Modeling, housed in the MCG Department of Medicine’s Division of Infectious Diseases. Rao also proved a major theorem in stationary population models.
He said he is thankful for the opportunity to reach a wider audience through this webinar.
“The CDC is known to do research that brings practical value in public health and hospital administrations. So being a mathematician and modeler working on public health issues, this gives me very good opportunity to reach a wider audience through the CDC,” he said.
The webinar will begin at 10 a.m. May 20 (EST) and last about an hour and a half. Questions from the audience will be welcomed by chat.
Access the webinar online here, with the password 916955. To access by phone, call 669-254-5252 or 646-828-7666, meeting ID 161 821 2816, password 916955.