Coronamonomania Thrives in Darkness, Part 14

The fun part of the briefing yesterday was the state wants all parents to test their school kids and themselves at least every two weeks.  This is ridiculous.  Lots and lots of poorly collected tests and erroneous results.  But for God’s sake, we have to find some way to keep the terror up.  That will help.  Leave the kids alone, they are fine.  See below from the British Medical Journal and the NYTimes.  And see the related point in the next paragraph about testing in Minnesota.  Dr. Osterheimlich took a sanity pill yesterday and told a cable program that we have to learn to live with the virus and get back to normal, although he did go full UFO on variants again.

I have mentioned several times the answers Scott Johnson at Powerline gets to his questions to DOH.  This week was a doozy of a response in regard to a question on the effect of false positives in a low prevalence environment.   Just so we are clear, whatever the lab-tested accuracy of a diagnostic test supposedly is, it isn’t in real clinical practice.  And those accuracy numbers are dependent on what the true prevalence is in a population.  While there are simple formulas to estimate that, the real math is pretty complicated because you are in essence trying to find the most likely of a variety of accuracy scenarios.  Generally, the lower the true prevalence is in a population, the less accurate test results become, that is they have more false positives and/or negatives.  Prevalence in Minnesota currently is very low.  So if you are random sampling a large percent of the population (and yes, as I will explain more below, the testing program isn’t random sampling, although it might as well be) in this low prevalence environment you are getting a high percentage of erroneous results and in particular, you are very likely to overestimate prevalence.

DOH’s response, and in fairness, for all we know they may have a mailroom clerk answering these questions, we certainly should hope it isn’t their experts, went along these lines.  The first paragraph was “maybe you don’t understand positive predictive value” and we are not randomly sampling, although they acknowledged sending test kits to teachers, for example, without regard to whether they had symptoms or were possibly exposed.  Here is the truth.  Health care facilities require testing regardless of symptoms or exposure.  Employers require testing.  People just decide they want to get tested.  DOH could collect and maybe has collected data to indicate whether people are being tested because they have symptoms or good reason to believe they were expose, or for some other reason.  So give us the relative proportion.  I would strongly suspect that on any given day half the tests are not of people who “should” be tested.  No it isn’t random sampling, but you aren’t testing a population where you know true prevalence, you are trying to determine it and the more people you test who are highly unlikely to be infected, the higher your false positive rate will be.  And if you are testing high proportions of people who very likely aren’t truly infected, you are going to get false positives, and the more you do that, the more false positives you get.  The consequences are huge.  If we implement the absurd suggestion that we test every school child and parent and teacher, you can see the danger.  Take a school with zero cases across those populations.  Now test everyone.  You are going to get positives.  They are all false but you are going to quarantine and isolate and potentially close the school.

The second paragraph went on and on about how accurate PCR tests are, although acknowledging that they pick up people who aren’t infectious.  Lots of people who aren’t infectious.  The third paragraph said that it is “erroneous” to just take the active cases number and divide by the population to get current prevalence.  Now we are told, active cases are “only the tip of the iceberg”.  For every identified case “there are many more out there: it could be anywhere from 10x to 100x more.”  You can laugh now if you want to.  The state currently says there are about 481,000 detected cases in Minnesota.  If there were 10x more, that would be an astounding 4,800,000, plus the original 480,000, so wow, 5,280,000.  Shit, we are done, that is 90% of the population, we have hit population immunity and we can stop the emergency and all the mitigation measures.  Now that 100x number troubles me a bit.  I was not aware that the population of Minnesota approached 48,000,000; but it would be cool if we were the most populous state in the country.  Maybe there are a lot more illegal aliens here than I realized, all living in caves underground apparently.    In a complete non-sequitor, the next sentence says antibody surveys indicate a prevalence of maybe 20% of the state’s population.  That would be more like 1,150,000 cases.  The best estimates by the CDC and others, are that Minnesota has 3 times to 6 times as many cases as are reported.  But good to know DOH is keeping up on the data and science and uses woke math, where the right answer doesn’t matter, just skin color, gender (pick one of 20) and sexual orientation.

The British Medical Journal article noted above summarized the evidence on schools’ role in transmission, basically insignificant, the low risk to children, and recited the by now well-established litany of harms from closing schools.  They should be open, period.  (BMJ Article)   And the New York Times also took a sanity pill, but doesn’t get teacher contributions either, so maybe that explains it, and discovers that we are really harming children by keeping schools closed, especially minority and low-income children.  (NYTimes Article)  The column cites a Federal Reserve Bank study which is worth reading both for its estimate of the damage we have done to children’s educations and the economic impact of that damage.  As I keep saying, the cure was far worse than the disease, and the ill effects of that cure will be with us for decades.

Just a reminder in regard to a study on duration of culturable virus.  This study I believe I posted on when it was put online and it has now been print published at the New England Journal of Medicine.  (NEJM Letter)   I bring it up again because of the continuing saga of testing issues.  Here is the critical sentence:  “Viral culture was positive only in samples with a cycle-threshold value of 28.4 or less.”  No patient had a culturable sample longer than 12 days after symptom onset, and almost all positive cultures occurrred within 10 days or less.  But we are using cycle thresholds as high as 40 or more to determine infectiousness and close schools, etc.

This study is complicated from an immune system perspective.  Basically we all have different sets of pattern recognition molecules that detect invading pathogens, and those variations can be linked to race, ethnic groups and thus vary by country.  The study found that those variations by country were associated with mortality from CV-19, which would explain some of the differences in death rates across countries.  (Cell Study)

A lot of transmission occurs in the household.  This paper examined household transmission by an index case in Ontario, Canada.  (Medrxiv Paper)  Only 32% of households had any secondary transmission.   Larger households, households with a symptomatic index case, households with a delay between symptoms and seeking testing and households with older people were more likely to see secondary transmission.

Surface transmission appears to not be a thing.  This study at a hospital at a university in California found no viable virus, although some tests were positive for RNA, on surfaces.  (Medrxiv Paper)

And another study on factors in transmission with a focus on particulate matter levels, this one from New York.  (Medrxiv Paper)   Again, pretty poor study as far as I can tell, but again finding that more particulate matter was associated with more cases.  They found some association for cases and deaths with population density, an association of deaths with an older population and no association with temperature.