VA Tech talk: COVID Data Science: Evaluating and Aggregating Emerging Knowledge in the Pandemic

On 9/24/21 I gave a talk at Virginia Tech on evaluating and aggregating emerging knowledge in the pandemic. It might be the most comprehensive summary I've given about the key points about the current state of the pandemic. Based on my work on this covid-datascience.com blog site, the main points are:

  1. Skilled, objective quantitative evaluation of emerging data and literature in the pandemic is crucial to overcome biases, misinformation, and misunderstanding.

  2. Statistical data scientists have unique skills that help them play a leadership role in this process, and given how often quantitative nuance is misunderstood by the public, media and even policymakers, should get more involved to "have a seat at the table" of policy and decision makers, and have greater visibility and participation with the media and in scientific communication with the public.

  3. I step through a number of key examples whereby many in the public have been confused or misunderstood what was going on because of quantitative nuance, often people who are virus or vaccine skeptics opposing mitigation and vaccination, but also sometimes the scientific establishment themselves.

  4. Based on these examples, I highlight how the careful understanding and interpretation of the data leads to clarity and overcomes misinformation and confusion.

  5. In the process, I also summarize what I view as the current state of knowledge in vaccine safety, effectiveness vs. infection and severe disease, variants, waning immune protection from vaccination, and what we know about immune protection after recovery from previous infection.

Here is a link to the talk, which is 1 hour long with 15-20 minutes of questions at the end.





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