Using Probabilistic Reasoning in Epidemiology

See Julia Galef on Aumann's Agreement Theorem, in particular this video:


And see Coronavirus A War Against Humanity?

Here are some lectures on Markov Chains which may be of use:


Part II:


And this may be interesting too:


Here's an example of how these ideas could be used to study a pandemic in real time:


See my YouTube comments:
11:10 this will be an interesting test of the mortality rate prior. Check how the mortalities stack up in the next few weeks, and compare that with the new cases confirmed in a place where aggressive testing is being carried out. In fact recommend to your government that they choose one area and test as near to 100% of the population as they can at as frequent intervals as feasible, then you will get good data that may show you where in the country you have hotspots, and if you record the demographics of mortalities and the causes, such as bacterial pneumonia or whatever, you will also be able to use census data to identify higher mortality risk persons, and to learn how to reduce avoidable deaths. This is all work the WHO should have been doing all along, of course. You will also learn how natural immunity develops and causes the virus to mutate to less lethal forms over time.
And maybe talk to the CDC and ask them how they know that a lockdown doesn't retard the development of natural immunity. https://youtu.be/XPCoU-ab1OA Christ, you only need to look at how the 1918 Spanish Flu started to see that this is extremely likely to be significant. See https://logicafterthought.blogspot.com/2020/03/coronavirus-war-against-humanity.html
See Baum–Welch algorithm. Here's Hannah Fry showing how Thomas Bayes was thinking about this, before he died, ...


This is Soviet-era mathematics. See Putin Says Sanctions Made Russians Use Their Brains and The Right Way to Formalise Mathematics. Why doesn't Putin seem to know about it? See Russian Aid for Italy


I have my suspicions. See my YouTube comment.

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