About the topic: Early on during the COVID-19 pandemic, researchers had tremendous difficulty understanding the lethality of the novel corona virus. In this talk I review the main reasons why estimating the infection fatality rate (IFR) is so challenging and discuss how Bayesian models can help address these challenges. Specifically, I consider a Bayesian model developed for estimating the IFR and it’s association with different variables of interest. When the model was fit to European data from May 2020, the overall COVID-19 IFR was estimated to be 0.47%, 95% C.I. = [0.34%, 0.63%] and a significant relationship was established between the infection rate in a given country and the time between that country’s first reported infection and the imposition of social distancing measures. See https://arxiv.org/abs/2005.08459 for more.
About the speaker: Harlan Campbell is a postdoctoral research fellow in statistics at the University of British Columbia with funding from from ReCoDID (https://recodid.eu/) and the WHO (https://www.who.int/reproductivehealth/projects/ZIKV-IPD-MA.pdf). Dr. Campbell’s work focusses on questions of meta-research and statistical methods for measurement error, evidence synthesis and equivalence testing.
About the TI Methods Speaker Series: The TI Methods Speaker Series are offered free of charge and everyone is welcome. The event is held at noon on the last Wednesday of each month. During the COVID-19 pandemic, while physical distancing measures are in effect, the TI Methods Speaker Series are offered via videoconference. The presentations are recorded and the video recordings are posted online. Click here to view the scheduled topics for 2021 and click here to view a list of TI Methods Speaker Series talks offered in 2020.
