COVID-19 Models Assumptions and Inferences

Wrong but Useful: COVID-19 Models, Assumptions, and Inferences 

A primer on mathematical (mechanistic) modeling for infectious diseases such as COVID-19, including a bit of history, underlying mathematics, and sensitivity of inferences drawn from these models to key assumptions.
 

Peter RebeiroDr. Rebeiro is an Assistant Professor of Medicine & Biostatistics and the Associate Director of Graduate Studies for the Epidemiology PhD Program at Vanderbilt University. Dr. Rebeiro’s research interests include quantifying clinical, contextual, and geographic patterns and correlates of retention in care and other HIV Care Continuum outcomes among persons living with HIV in North, Central, and South America, and in other IeDEA regions (https://www.iedea.org/). Dr. Rebeiro is interested in the application of appropriate causal inference methods to examine the impact of clinic/program-level interventions to improve retention and HIV Care Continuum outcomes, the application of spatial analysis methods to quantify geographic and temporal variation and clustering of suboptimal HIV Care Continuum outcomes, and geographic mapping of outcomes to disseminate epidemiologic data in a timely and easily digestible format.

Registration for this event will close at 11:00am EDT on Tuesday, July 14.

 

 Event Date
Tuesday, July 14, 2020
Start Time: 12:00pm
End Time: 12:30pm

 Location

Virtual
Baltimore, MD 21205

Status message

Registration for this session is closed. Please email Elizabeth Rigsbee, erigsbee@jhu.edu, with any questions. Recordings of past events can be found at the link below.

https://www.jhsph.edu/alumni/attend-an-event/