Went out last nite, a local mall was absolutely packed with cars, far more than I have seen since this started. Barnes & Noble was very busy. Ate at a restaurant, basically full, loved to hear the buzz of many voices. Almost in tears at the sight of people letting themselves live again.
And then I have to ruin my morning by reading CV-19 research. Some things just can’t be modeled, we don’t understand all the relevant factors, we don’t know their relative contribution to the formula, we don’t know how they interact with other factors. So it appears with meteorological factors and CV-19. There absolutely is a seasonal/geographic pattern. What the formula representing that pattern is, seems unknowable, which is too bad, because it would help in predicting case resurgence. You can generalize, for example, in Minnesota CV-19 seems to like mid-March to mid-May and October to mid-November. The rest of the time it vacations in Florida and California. Anyway, here is another paper from the Netherlands trying to incorporate a variety of factors, including weather, into a model of spread. (Medrxiv Paper) The authors included data on mobility behavior and the level of mitigation restrictions in their analysis. They used a six day lag for cases and a ten day lag for hospitalizations to explore potential relationships. During “pleasant” weather, i.e., sunnier and warmer, there was lower case growth than during unpleasant weather. This trend was slightly increased when bars and restaurants were also closed. The same was true for hospitalizations. Looking at various restrictions paired with weather showed only minor impact on the trend apparently associated with weather. The researchers’ interpretation of the results, which I believe is accurate, is that weather affects transmission more through viral characteristics than through human behavioral ones. That impact could be both on the virus itself, in terms of its organic stability, and in terms of factors affecting transmission, such as droplet evaporation and life cycle.
This study attempts to review the research on the non-CV-19 health effects of the attempts to suppress spread. (Medrxiv Paper) Noting that most studies on the topic are methodologically flawed, they find more compelling evidence that there have been effects on mental health, on domestic abuse and on reductions in exercise. There was less compelling evidence in other areas, such as increased alcohol abuse, primarily because of difficulty in directly attributing such consequences to the suppression measures.
I like big bad news and I cannot lie. This study looks at the effect of lockdowns on dementia patients. I can tell you it isn’t good by looking at excess dementia deaths this year. (Medrxiv Paper) And this paper further confirms that. Isolating even more a group with limited social contacts and limited cognitive ability has been devastating. The authors conducted a meta-review of the research and found clear evidence that there was additional cognitive decline, development of further behavioral issues and declines in daily activity functioning. People actually interested in overall public health might take factors like this into account when designing mitigation measures, but no, coronamonomania.
Antibody surveys are the usual method of ascertaining the true level of infections in a population and in determining the nature of adaptive immunity following infection. We are reminded by this paper that results of research are only as good as the method of getting the results. (Medrxiv Paper) These researchers tracked antibodies in a group of mild and asymptomatic cases using three different assays. While the antibodies clearly persisted for over 8 months, the assays showed highly variable performance, with one missing 40% of infections.
For those eager to find cause for alarm in variants, here is a paper from France analyzing the results from over 60,000 PCR tests which specifically looked for variants. (Medrxiv Paper) As an initial matter, note that they ignored “positive” tests with cycle numbers over 30 because they are unreliable. The B117 variant had come to be dominant, accounting for over 80% of positives. Positive tests for this strain showed slightly lower cycle numbers on average, indicating higher viral loads, which would be consistent with easier transmission and infectivity, although the authors cautioned about reading too much into this finding. Cycle number also decreased with age, indicating the usual greater susceptibility to infection among the elderly.
Another weapon in the terror campaign has been reinfections (ooooohhhh, just think how scary reinfection with a variant is!), although it has been overshadowed by variant fear in recent weeks. I expect a return to that theme as it becomes apparent that vaccination isn’t absolute 100% protection against infection or reinfection. This study looked at reinfection levels in Switzerland from April last year to January this year. (Medrxiv Paper) As have other studies, they compared infection rates in those with prior infections to those persons who had never been infected, in a matched cohort design. About 1% of the prior infected group had new infections, versus 15.5% of the previously uninfected cohort. This implies a 95% or so protection against reinfection over at least 8 months, which is remarkably similar to the protection afforded by mRNA vaccines.
And this study looked at whether reopening schools may have had an effect on case levels in the community. (Medrxiv Paper) This was a county level study in Indiana trying to associate in-person learning with case levels. The lag period was 28 days, which seems bizarre. How does being in school one day affect cases 28 days later, given everything we know about incubation periods, infectiousness periods, etc. The authors found a very, very small increase in cases 28 days later based on the proportion of students in a county attending school in person.
And that’s aaaaalllll, folks!