A Head Full of Coronavirus Research, Part 4, and a Model Tease

It has taken a while and my friend Darin Oenning and another very helpful reader have given me tremendous assistance and pointed out some very interesting aspects of the Minnesota model, so tomorrow I am hoping to have a much longer post out on it.  The issues with that model are common to a number of models.  In the meantime if you go to this site, from the UK,  you may have to scroll down to the May 21 posts, you will see a number of comments about the Minnesota model.  (Lockdown Notes)

A few columns and papers again tonight.  First up, a group of doctors sent a letter to the President expressing concern about the shutdowns’ effect on health and health care.  (Dr. Letter)   I have made the point from the start that these shutdowns and the terrorizing of the citizenry have caused serious damage to the health system and to the health of millions of Americans.  These physicians make the same point, from personal experience.  Children aren’t getting vaccinated or well-child care, people aren’t getting cancer screenings or treatments, people aren’t going to the ER with chest pain, and on and on.  Meanwhile we took billions of dollars of revenue away from hospitals, physicians and other providers.  Really smart.

Sometimes when something new pops up people get fixated on a certain aspect that really isn’t that important.  The R or transmissibility number for the infection is one of those items and an article explains why.  (R Article)   The article refers to a study by some researchers who say that metric is misleading and subject to misuse.  The author notes that even early values for R are subject to the environment in which an outbreak is occurring and the behavior of the population.  And different models tend to calculate it differently.  We have seen initial R values ranging from 1.4 to 11.  Clearly in a diverse country like the US, this value will vary widely from urban to rural regions.  R is also lagged, it takes a while for people to become symptomatic so it isn’t providing real-time guidance on the extent of the outbreak.  More important than transmission rates is what is happening to the people who become sick.

Next up, an article that expounds on my favorite theme, the panicked response of our so-called leaders.  Why wait a couple of weeks to get some valuable information about what is actually occurring when you can over-react and kill an economy and tens of millions of jobs.   (RCP Article)   They point out the complete lack of risk to the general population, a risk that was ignored because of crazy models build on unreliable data.  The author also points out how politicians are trying to claim that the lockdowns saved lives when there is no evidence that as many deaths as modeled were ever going to occur.  Once again Sweden looks like a model of sanity, using common sense and not having anything like the deaths models predicted for that country.

Next up is a paper that looks at interactions between age groups as they relate to epidemic dynamics.  (Medrxiv Paper)   You will recall that contact models are perhaps the critical part of a larger epidemiological model and that most of those contact models are built from work in a single set of studies in Europe.  These authors just looked for relationships in infection rates across age groups and found that higher rates of infection among younger people raised the risks to the elderly and that higher rates of infection among the elderly raised the infection risk for all other age groups.  A mechanism is not proposed, although the authors write as though causation were actually involved, which is not shown,  nor did the authors separate out the elderly in congregate living settings.  Multigenerational housing patterns were also not considered.

How about another study on coronavirus immune system cross-reactivity?  (Medrxiv Paper)   The reason I am so interested in these papers is that I am convinced that many people are simply not getting infected despite exposure and that the many asymptomatic illnesses must be due to some immune defense capability.  Since we all get coronavirus exposure, we have antibodies to some strains, but we also have immune components called T cells that function against specific pathogens.  The authors basically used sequencing of coronavirus strains to predict areas that would provoke immune response and then tested those predicted areas agains prior work identifying actual T cell activation.  They found a large number of sequenced areas that were common across all strains.  They also identified some shared potential sequences with influenza viruses.

Next up some more work to characterize the antibodies acquired by persons who have been infected by coronavirus.  (Medrxiv Paper)  The authors assessed antibodies in 41 Australian patients with mild to moderate disease.  They found antibodies against the spike protein and its receptor-binding region.  They also found memory B cells and T cells specific to this variant of coronavirus.   They also investigated antibodies in 27 uninfected patients and found little cross-reactivity.  Although binding antibodies were universally found in infected patients, they did not all have antibodies or other immune components that led to clearance of the virus from plasma.