We have all become familiar with the importance of monitoring the number of COVID-19 cases for setting policies and managing limited health care resources. But how do inaccuracies in tests for the virus impact the curves that describe the epidemic?
Paul teamed up with Drexel University epidemiologists Igor Burstyn and Neal Goldstein to study this question, using publicly available COVID-10 testing data from Alberta and Philadelphia. They develop a Bayesian method, placing priors on...