File:Martenson.Scenario.png

Summary
Source: How We'll Get Through The Coronavirus Debacle Chris Martenson, April 7, 2019 (From 17.22)


 * Refs: Report 13 - Estimating the number of infections and the impact of non-pharmaceutical interventions on COVID-19 in 11 European countries Imperial College London Covid-19 Reports



Knowing the true infection rate would allow one to determine the fatality rate. If infections have been more widespread than estimated then the fatality rate is lower. If they are not more widespread then the fatality rate has not been overestimated. Nassim taleb argues contra John Ionnidis that uncertainty in data increases the risk of underestimation.

Scenario B?

 * Up to 4% of Silicon Valley is already infected with coronavirus - Antonio Regalado, MIT Technology Review, April 17
 * Antibody study suggests coronavirus is far more widespread than previously thought Kari Paul, The Guardian, April 18, 2020
 * COVID-19 Antibody Seroprevalence in Santa Clara County, California (Preprint) - John Ionnidies et al, MedRxiv April 17, 2020

False positives?

 * Chris Martenson If the new Antibody tests are 93.5% accurate (i.e. "sensitivity') then this means if true incidence of Covid in population is 1%, the test will return a false positive 82% of the time.
 * L C Wheeler I tried to make a pair of visualizations that show what what this thread is saying in a way that I hope is easy to understand...