Predicting Coronavirus Cases

systrom ^ | March 19, 2020 | Kevin Systrom

[IndispensableDestiny]

The SIR model attempts to explain both of these situations. Assume every individual is in one of three states: susceptible, infected, or resistant. In a simple world, patient zero is infected, everyone else is susceptible and nobody is resistant.

With every step in time, some susceptible people become infected, some infected people recover to be resistant, and resistant people stay resistant.

[IndispensableDestiny]

A good explanation of the SIR model used to predict coronavirus cases. An understanding of some math is required. Kevin Systrom is not an epidemiologist, he founded Instagram. Also take a look at The Numbers Behind Social Distancing.

[NobleFree]

Fun stuff! But it's GIGO - case counts have at least as much to do with prevalence of testing as with prevalence of the disease.

[InterceptPoint]

Fun stuff! But it’s GIGO - case counts have at least as much to do with prevalence of testing as with prevalence of the disease.
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While that is true, we have an official count of a bit less than 500,000 cases. We have 330 million Americans.

Yes, testing would change the count but not the fact that we are nowhere close to seeing a large percentage of the population as survivors of infection. Not even close.

This analysis is, unfortunately, correct. What he doesn’t know and we don’t know is how the current slowdown/shutdown will affect us long term - months to many months. But his analysis is absolutely based on the correct methodology. At least IMHO.

[Basket_of_Deplorables]

This is such a perfect opportunity to use AI to develop really good models. So much data, and so many different tactics taken in so many countries. Let it time itself, until it accurately predicts the actual situation in each major country. Include political philosophies...