After what passes for excitement in the world of coronavirus studies this morning in regard to PCR tests, back to the more mundane world of real research. But first, a reader passed on to me a news story about the city of Sturgis, recently invaded by a massive horde of foaming at the mouth, motorcycle riding, CV-19 infectors; offering free testing to anyone who wanted it. 650 people got tested. 26 were positive. All asymptomatic. What a downer. Based on the NYTimes story, 2.6 were actually positive. Based on the Medrxiv paper, maybe .6 were. (Sturgis Story)
This study is another in the long, long line regarding the adaptive immune response to a CV-19 infection. (Medrxiv Paper) The work is based on only three patients, finds extensive antibody development and that the antibodies were cross-reactive to other seasonal coronaviruses. In fact, some of the CV-19 antibodies may have developed from memory B cells that were part of the adaptive immune response to seasonal CV.
And here is a paper that reviews the understanding of the cellular immune response to CV-19 infection. (Medrxiv Paper) It covers 61 articles. The authors’ summary of the research is that most patients with severe disease develop robust T cell responses, but the protectivity of those responses in regard to attempted reinfection is unclear. I think they are a little too cautious. They do properly note the difficulty of doing widespread screening for T cells.
Finally, a paper from New Zealand, land of the “we will kill ourselves and our economy, but by God, at least we won’t have any coronavirus” lockdowns. (NZ Paper) Apparently the author is one of a growing number of New Zealanders who wonder if the extreme lockdown makes any sense. He says that a minimum of 3.3% of the country’s GDP was lost just during its extreme lockdown, which was the most stringent in the world. The rationale was saving lives. He wonders if lockdowns actually do that. He used data from US counties to compare areas with lockdowns versus those with more moderate mitigation measures. He used a variety of adjustments and variables to try to limit the correlation to the actual effect or non-effect of lockdowns. He found no difference in deaths in counties with lockdowns versus those without.