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.