Common sense science for the COVID-19 epidemic

The COVID-19 epidemic has taken up much media space since March. Derivatives and integrals have never been so widely discussed in prime time news. Nor have engineers, scientists and mathematicians from diverse backgrounds spent so much of their professional time studying a very limited number of time series. 

Interestingly, some of the discussion falls into avoidable traps: over-fitting data, neglecting prior knowledge, cherry picking. I will apply the usual tools of the physical sciences to do sanity checks- dimensional arguments, measurement errors, limits of models, Bayesian inference.

Using these tools, I will try to build robust tests of simple hypotheses: estimate basic epidemic parameters such as R0, discuss the fatality rate, age and sex dependent susceptibilities, and reach an understanding of the current state of the epidemic.