#coronavirus How to analyze and not analyze #COVID-19 deaths

Corona virus on Market analysis background. 3d illustration. Epidemic virus. Market trade. Licensed via 123rf.com

Guest essay by Indur M. Goklany

Don’t look just at deaths from coronavirus, look at cumulative deaths from comorbidities. Since most people dying from coronavirus also exhibit comorbidities,[1] and it is unclear how deaths are assigned to the former rather than one of the co-morbidities and whether there is a uniform accepted methodology from one doctor to another (or one hospital to another or one country to another) in the assignments, it is not clear how much credence can be given to coronavirus death estimates at this time. 

This also means that we shouldn’t attempt cross-country and cross-jurisdictional comparisons because they could mislead.  It is best to look at (and compare) aggregate excess deaths from all co-morbidities rather than just one or another co-morbidity. I would suggest looking at excess deaths against an average over the last 5-10 years for both all-cause deaths and deaths from all coronavirus-plus- comorbidities to get an idea about how devastating coronavirus has been versus an average year.

To compare deaths between jurisdictions, don’t look at absolute deaths, look at death rates, based on population sizes. It makes no sense to compare absolute numbers of deaths in Italy, UK, San Marino, and Sweden against those in the U.S.   

Each area is different.  From where I sit — in Northern Virginia — New York is another country.  And from upstate New York, New York City is also another country.  Risk factors such as population density, use of mass transit, presence of people who have recently travelled elsewhere, norms regarding appropriate social distance, household size, age composition of households, and all the other coronavirus risk factors are likely to be different in each area.  One should, therefore, expect each location would have its own curve that would have to be flattened.  Some areas may literally be “ahead of the curve” since these areas have had some advance warning before the virus was brought into their communities and may not need to take drastic measures to flatten the curve.  Aggregating data across urban and rural areas does not make much sense. 

I wouldn’t be surprised if at the end of the current period with most populated areas currently shut in by individual choice or government decree, once all the data are in, excess deaths for all causes are not negative relative to the 5- or 10-year average, since physical distancing should also reduce transmission of the flu (influenza and pneumonia kill about 50,000+ Americans annually)[2].  At least, I would hope that would be the case, so we can look back and see that some good came of our flattening our economy.  At least one can hope.


[1]https://ift.tt/2Wa5fls

[2] https://ift.tt/2Rg5o3o

via Watts Up With That?

https://ift.tt/2ywJlPu

April 5, 2020 at 04:49PM

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