Coronamonomania Lives Forever, Part 53



By Kevin Roche November 14, 2021

Still catching up and when this is published I will momentarily be there on research summaries.  Momentarily.

Miracle of miracles, a Democratic Governor, in Colorado, says something completely rational and sensible about masks.  Governor Polis said he saw no reason to implement a mask mandate, because New Mexico has one and their case rates look like Colorado’s.  Way too much common sense.  (Colo. Story)

A study on breakthrough infections in a county in Florida.  There were a relatively small number of breakthrough events, which occurred on average 100 days after full vaccination.  75% were Delta.  Some transmission by breakthrough infections were identified.  The viral load was about 38% lower in breakthrough cases.    (Medrxiv Paper)

An enduring mystery is why some people don’t get infected after exposure.  The virus undoubtedly enters their upper respiratory tract but never gets going.  A new study which followed health care workers with frequent exposure found that among those who never showed signs of active infection, there was a much stronger pre-existing T-cell response, which had as a dominant target the replication transcription complex of the virus.  As it sounds like, this part of the virus is responsible for creating new virus particles.  This part of the virus is highly conserved, that is, very similar, across coronaviruses, so it is likely that prior seasonal coronavirus infection led to these T-cell responses.  This could also provide guidance for development of better vaccines.  (Nature Study)

Another enduring mystery is why we keep using PCR tests that we know are far too sensitive, don’t distinguish between infectious and non-infectious persons and lead to unnecessary anxiety and quarantines.  This paper describes a new approach to PCR testing that focuses on segments that are associated with viable virus.  It appears to do a far better job of distinguishing between actual cases and random positives.  Hospitals won’t like this, because it will cut down on their payments.  (Medrxiv Paper)

Myocarditis appears to be the most common potentially serious adverse effect of vaccination.  This study examined data on a large number of vaccinated persons.  It comes from Moderna, so buyer beware.  It confirms, however, that young males are likely experiencing myocarditis after vaccination at higher rates than the background prevalence.  Otherwise the rates appear at or lower than background and lower than in actual CV-19 infection.  (Medrxiv Paper)

This study from Norway is one more looking at vaccine effectiveness, with a focus on age. Effectiveness against infection was 72%, against hospitalization, 93% and against death, 88%. Somewhat lengthy follow-up period for some subjects.  Lessening of protection against infection in the elderly, and a smaller lessening of protection against hospitalization in those groups.   Somewhat significant protection was shown even with one dose.  It is interesting to think about the effect of partly vaccinated persons on breakthrough analyses.  They likely understate breakthrough proportions, but they also could result in lower apparent rates if they are lumped in with the completely unvaxed.   (Medrxiv Paper)

And this study from the Netherlands examined vaccine effectiveness against hospitalization. Effectiveness was very high, with no fully vaccinated persons being admitted to ICU or dying.  But there were some breakthrough hospitalizations, and this study was conducted in the late spring, with relatively short follow-up after full vaccination.  (Medrxiv Paper)

Not sure why I even report these studies, which are basically made up modeling, based on bad analytic methods.  But this study does a meta-review of all these bad modeling studies and claims that the euphemistic non-pharmaceutical interventions, i.e. lockdowns, had a great effect on limiting transmission.  Let’s see, if you run your study period through a whole wave and your NPI is in place for the whole wave, you could claim your NPI was responsible for the decline in cases, or you could do the right thing and assume that you have a confounding variable.  (Medrxiv Paper)



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