Drowning in Coronavirus Research, Part 83

By September 10, 2020 Commentary

I want to start by making an observation I omitted in my latest post on Minnesota’s futile and useless mask mandate. The Incompetent Blowhard and the Health Department have boxed themselves into a horrible corner.  On the one hand they want cases to be high so they can justify their unjustifiable actions and keep the population cowed.  On the other hand, high cases prove the mask mandate isn’t working, and it isn’t.  Where is that exact sweet spot for cases?  They are going to have a really hard time finding it.

I am not going to summarize the actual papers, but people keep looking for things that might protect against CV infection or severe illness.  One recent paper found a strong relationship between vitamin D levels and reduced infections.  Others have suggested that flu or other vaccines have a protective effect.  Recent studies have shown that a common steroid can be very beneficial in treating more serious illnesses.

And this came to my attention after the post on testing research.  The group advising the United Kingdom on its coronavirus response issued a statement on mass population testing.  (SAGE Statement)   This group noted the care with which mass testing must be undertaken and the very high likelihood of excessive false positives in a low-prevalence environment.  So care must be taken to immediately have a method of verifying the supposedly positive results.  Here is a quote that illustrates the dangers of mass testing in a low prevalence world:

“It is well known that widespread use of a test with imperfect specificity in a population with low prevalence will generate more false positives than true positives. For example, suppose one were to test 100,000 people of whom 200 were infected and 99,800 were not infected. A test with 80% sensitivity and 96% specificity would find 160 true positives and 3,992 false positives. The situation can be rectified with follow-up, confirmatory testing of the 4,152 with a positive first test using a different second test that has very high specificity (perhaps at greater expense or slower turnaround). If those 4,152 individuals were re-tested with a test with 99% specificity the number of false positives would fall to just 40 – see Annex B for detailed illustrative examples. This calculation relies on the strong assumption that the two tests have independent errors.”

Do you see that number of false positives in this example?  If you apply it to the current testing regimen in Minnesota, there is a high likelihood that initial positive test results are inaccurate at least 30% of the time.  The statement further explains the problems with the interaction between virus levels and test results.

This study also relates to testing as it deals with the issue of how long patients with severe disease have viral shedding.  (CID Paper)   41 severely ill patients from China were followed and tested regularly.  They had positive PCR test results for an average of 31 days with a range of 18 to 48 days.  But we now know that the study is meaningless because there was no effort to determine if there actually was viable virus in the samples and we aren’t told the cycle number threshhold for determining “positivity”.

This paper examined the relationship between age and the need for health care treatment in CV-19 disease in Ontario Canada.  (Medrxiv Paper)   All cases in the province were examined.  Hospitalization risk plateaued roughly in the age 54 to 90 range.  Deaths were highly concentrated in the very old, with a peak around age 90.  100% of adults under 40 survived hospitalization.  After that age survival began to decline substantially, with a 50 year old have a 90% chance of survival.  The authors express concern that a wider epidemic would lead to significant hospitalizations, but they are ignoring the front-loading phenomenon.

And finally for this edition, research profiling the immune response in people with mild CV-19.  (Medrxiv Paper)   The authors used three healthy donors and 10 patients with asymptomatic, moderate or severe disease.  They found, on a small sample, that asymptomatic patients had a different immune response, with a greater portion of certain natural killer cells, and more T helper than T killer cells.  Their helper T cells were similar to those detected in unexposed individuals and they hypothesized that an immune response prompted by prior coronavirus infections may be responsible for asymptomatic cases.

 

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