Decoding COVID John Houghton

Harvard Epidemiologist, Dr. Stephen Kissler and John Houghton discuss data modeling for diseases with special consideration of SARS-CoV-2 variants, including B.1.1.7 (UK), P.1 (Brazil), and B.1.351 (South Africa).  This is a deep dive on the nuts and bolts of COVID-19 modeling including insightful definitions of R0, generation interval, start date, and population size.



How R0 as a measure becomes substituted with Rt as an outbreak progresses

Review data model created by John at the beginning of the epidemic

The SIR model (Susceptible, Infectious, or Recovered)

How does reinfection change the SIR model? Introducing SIRS (or SIS)

Probabilistic vs deterministic modeling

The explosiveness of exponential growth

Can new variants be introduced at an exponential rate?

Discussion of Lancet paper: Resurgence of COVID-19 in Manaus, Brazil, despite high seroprevalence - The Lancet

Math check: If a variant is 40% more infectious than an R0 3.0 wild type-virus, what is the new R0?



Check out Dr. Kissler's podcast: Pandemic: Coronavirus Edition.

In our first episode, we discuss how SARS-CoV-2 attacks germinal centers in lymph nodes and spleens, resulting in a weakened immune response.  Review paper from the life sciences journal Cell:  Loss of Bcl-6-Expressing T Follicular Helper Cells and Germinal Centers in COVID-19.  Hosted by John Houghton, with special guests Dr. Faz Alam, Microbiologist and graduate of the Imperial College of London, and Danny Chan, PhD candidate, Infectious Diseases, University of Chicago and President of Biotech Without Borders.  Faz and Danny are co-hosts of the YouTube Microbiology Journal Club and they also covered the same paper in their September 6, 2020 episode.