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Statistical Data Science, COVID-19, & Society; Current knowledge on immunity, vaccines, & variants

Here is an .mp4 file of a Keynote address I gave at the Innovations in Design and Analysis & Dissemination: Frontiers in Biostatistics (IDAD): Kansas University Medical Center overviewing how subtle quantitative issues have contributed to confusion in the pandemic response, highlighting the important role of biostatistical data scientists in helping sort through these nuances, and discussion the efforts I've made through this blog page.

Topics I cover include:

  • Finding the middle ground between the extremes of denialism and alarmism, and politicization of knowledge discovery during the pandemic.

  • The phenomenon of wartime science -- the need to accelerate scientific discovery and application, but yet the risk of false results and mistakes from rushing things too much, with some examples from mask efficacy and a case of scientific fraud in a major Hydroxycholoroquine paper.

  • Brief mention of other themes on the blog, including evidence-based assessment of targeted mitigation strategies, evaluating and dispelling conspiracy theories and myths, and understanding the importance of each data type and its limitation

  • I describe the impact of COVID-LAB efforts led by David Rubin and CHOP and whose statistical modeling was led by Jing Huang, my junior colleague at Penn Biostatistics, in which a modeling framework to predict county-level cases was able to successfully predict some of the regional surges and came to be a key tool used by Deborah Birx in the White House Pandemic response team to focus her efforts in getting local leaders to incorporate better mitigation. This group also demonstrated the impact that can be made when focus on rapid dissemination of results is emphasized by modeling groups.

  • Current knowledge on reinfections (rare) on immune protection after recovery (substantial and robust)

  • Current state of knowledge on the vaccines -- efficacy in preventing infection and transmission, safety and population validation

  • Current understanding of the major variants, and what this means for transmission, severity of disease and immune protection.

  • What we can expect in the next 6 months: vaccination, population (herd immunity), and evaluating what happens when population vaccination is nearly complete.

  • A call for biostatisticians to engage more in society, to have a seat at the table with policy and decision makers, and be visible to the media and public, to ensure our understanding of quantitative nuances in science and society are taken into account.

The presentation is about 1 hour in length. Here is a link to the presentation:

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They also showed how effective it is for modeling groups to prioritize the quick distribution of results.

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