And thank you @angrybklynmom for pointing out that the CDC estimate for Pediatric C19 admissions is off a model and is ~10x higher than actual HHS data (~30k).
This is a numerical & narrative thread looking at the relationship between NPI (mandate) stringency and state level COVID outcomes in the USA.
Contents: 1) discuss motivation 2) present methods and sources 3) present results and implications
2
Motivation:
NPIs are disruptive. Nowhere in life do we entertain harm unless there is potential benefit. We are 16 months into this and have completed a full "epidemic cycle". We are in a period of COVID-19 quiescence nationally.
It's a good time to examine the results.
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So why examine the USA in isolation?
1) We have a heterogenous response (Oxford Stringency Avg 41.6 SDEV 9.2)
2) We have diverse demographics in key variables
3) '57, '68, 2009 Influenza pandemic outcomes suggest wide inter-country variation and 2+ years to "mature"
I will be discussing this paper (along with a recent contribution) in an upcoming thread, but it highlights the importance of system level thinking over analyzing an intervention in isolation:
"In Hong Kong and Bangkok during 2008–2011, large randomized controlled trials were conducted to investigate the efficacy of surgical face masks and enhanced hand hygiene in reducing transmission of influenza in households."
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"[Influenza A is believed to spread via contact, large droplets and aerosols, but the relative importance of each of these modes of transmission is unclear. Volunteer studies suggest that infections via aerosol transmission may have a higher risk of febrile illness.]"
3) Review the # of patients required to assess efficacy & safety in the <18yo population
4) Review "# needed to treat" (NNT) & "# needed to harm" (NNH)
5) Extend discussion to "# needed to vaccinate" (NNV) & possible limitations of this concept
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I downloaded the VAERS data for 6-17yo (so effectively just 16yo and 17yo) validated through 5/19/2021. I restricted analysis only "serious" events (returned 124 results).
The quoted thread, applies to all aspects of COVID policy.
One can’t discuss the limitations of archaic compartmental models, subtleties of inferential statistics, & computational modeling under uncertainty to incurious, social-credit seeking politicized acolytes.