What is our current state of pandemic knowledge, and what can we expect in the next year?
- Jeffrey Morris
- Sep 17, 2020
- 2 min read
I was asked to give a presentation by the University of Pennsylvania Faculty-Staff Christian Forum today, entitled "COVID-19: A Biostatistician Looks Back to Project Forward".
My key goals were to communicate my motivation for writing this blog and its key themes, and to summarize the current state of knowledge about the pandemic in response to some key questions given to me ahead of time, including our most current knowledge of how the virus spreads, what this means for which mitigation strategies and precautions are most important for us to follow, how different countries have dealt with the pandemic and how it has turned out, what different types of covid-19 tests are being used and their properties. and what we know about immunity and vaccines. I also gave best case and worst case predictions for the short term (remainder of 2020) and the longer term (2021 and beyond).
Below is a link to the video which is roughly 1 hour.
This is the abstract from my presentation:
Abstract:
The novel virus SARS-CoV-2 has produced a global pandemic, forcing doctors and policymakers to “fly blind,” trying to deal with a virus and disease they knew virtually nothing about. Sorting through the information in real time has been a daunting process—processing data, media reports, commentaries, and research articles. In the USA this is exacerbated by an ideologically divided society that has difficulty with mutual trust, or even agreement on common facts. Biostatistician Jeffrey Morris will summarize for us key principles which he has observed about the pandemic, and implications for what we can expect in the coming year. Jeff has authored a website and blog to apply statistical data science to evaluate and communicate emerging information about this pandemic. While accounting for subtle scientific and data analytical issues and uncertainties about our current knowledge, it also seeks to filter out political and other subjective biases.

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