Today's lesson in math: magnitudes. Are the NYC and Santa Clara study reaching really different magnitudes? Not really. Let me explain why using round numbers they use. The studies announce that real corona infection is understated by some number say 10x and 50x. 1/n
Those numbers sound really far apart don't they? They are actually much closer than they sound in a key way. Let's assume you estimate observed corona cases are 10% of the total infections that means total infections are 10x. If you estimate observed infections are 2% 2/n
Today means real infections are larger by a magnitude of 50x. With a small change in the percentage of observed cases you can have an enormous change in the magnitude difference. Why is this important? Lots if reasons small percentage differences can manifest themselves 3/n
Testing errors, disease date of arrival, weather, urban environment etc etc etc. At this stage of research we want to focus on general directionality rather than exact magnitude. Lots of general consistency, more research and consistency needed to explain variations. Done.
