Comment by Aussierotica on 02/09/2021 at 12:00 UTC

-1 upvotes, 1 direct replies (showing 1)

View submission: COVID denialism and policy clarifications

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And you should be able to provide one to counter it.

What are the preferred methods of counting? Raw corpse numbers, or /per some population metric? With or without co-morbidities? Broken down by age brackets and standard / actuarial life expectancy? Degree of medical intervention prior to death? Time since vaccination for the vaxxed? 1 or 2 or 3 doses?

Lying with statistics is fun! And I hate that our governments don't seem to give us very useful figures, or then walk back something that they'd definitively said the day before (e.g. Covid-19 death of a teenager was *actually* due to bacterial meningitis. Oopsie)

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Comment by beestmode361 at 02/09/2021 at 13:26 UTC

3 upvotes, 1 direct replies

Here is a nice article explaining how to do this analysis. There are actually clear guidelines on how to analyze this data in a genuine way. The article walks through the commonly misconstrued Israeli data and explains why the vaccines are still effective despite the initial concern brought by the data.

“”” Adjusting for Vaccination Rate It is true that nearly 60% of active serious cases are vaccinated, but such an analysis based on raw counts can be misleading since it is heavily influenced by the vaccination rates.

When vaccination rates are low, use of raw counts can exaggerate the vaccine effectiveness, and when vaccination rates are high, use of raw counts like this can attenuate the vaccine effectiveness, making it seem lower than it in fact is.

Note that a high proportion (nearly 80%) of all Israeli residents >=12yr have been vaccinated.

To adjust for vaccination rates, one should normalize the counts, of severe cases in our setting, for example by computing number "per 100,000"

“””

https://www.covid-datascience.com/post/israeli-data-how-can-efficacy-vs-severe-disease-be-strong-when-60-of-hospitalized-are-vaccinated