Coronavirus: A few thoughts

A few passing thoughts on the current state of following the coronavirus epidemic:

1. Apples and oranges: As mentioned yesterday, changing the criteria for determining who is infected with corona virus, who has recovered, and who dies of the disease makes it very difficult if not impossible for anyone, including "experts" to track the course of the contagion. It is difficult to make week-to week comparisons of reported data when those data measure different things in different ways.

2. There is a noticeable tendency for people to seek single-cause explanations for differences in the coronavirus experiences of different locations and at different times. Some examples include: the extent of testing; the presence and timing of social distancing, if any; the age of the population; the extent of smoking and other habits; the nature of financing of particular healthcare systems, etc. It is unlikely that there is any universal intervention or cause to explain difference observed across populations or from time to time. The experience of South Korea is unlikely to translate to New York, or Spain, or anywhere else. Differences in the effects of coronavirus, its spread and mortality are much more likely due to constellations of factors that interact in unknown ways and which are not always amenable to observation or measurement. The single factor idea is a fallacy.

3. Similar to the above, there are a great many isolated observations that should be considered as representative phenomena only with great skepticism. Such observations include "young people are dying of the virus," "people who were thought to have recovered are testing positive again," and alleged cures associated with various interventions. These are anecdotes and, to the extent that they are useful, are such because they remind us that generalities associated with this virus come with a whole lot of asterisks. One should be very cautious about generalizing the experiences of one group of people to wider populations, even if the isolated observation is itself true.

4. The observation above is highlighted by the fact that data are all over the place. Out of 7.7 billion people on the planet there is not a single one who legitimately knows the prevalence of the disease, the mortality, whether the infection confers immunity, whether abnormally low or abnormally high rates of infection or death are due to such things as government responses, or people's natural behavioral changes to an acknowledged threat. Because the data are all over the place, it is almost impossible to assess the effect of interventions. A person looking at the experience of New York and comparing it with say Oklahoma or Wyoming, might be tempted to say that social distancing does not work. (Although a more pragmatic approach is to consider that the differences between New York and elsewhere is due to unique combination of factors, rather than one or two things). It is not only the reported data, which is contaminated by constantly changing criteria, that is all over the place; so are the predictions of various models and experts and credentialed sooth-sayers. This will eventually reveal itself in the public becoming distrustful of those who purport to be managing this crisis. There is only so much "3 million deaths... no 600,000, no, 20,000, no, 125,000, no 400,000...,""we don't have enough ventilators, we have enough ventilators, we have too many AND not enough...","go out and live your life, no, stay home, only go out for necessities,...hey, those aren't necessities..." etc. before people start suspecting not only a lack of reliable data, but of competence and good faith.

5. New York is an outlier, no matter how you look at it. On the one hand the infection and mortality rates are noticeably higher than one would expect from the country as a whole. Yet supposedly a large number of people are dying of coronavirus at home without a formal diagnosis, and the percentage of positive test results is higher than elsewhere. This would suggest that the already elevated reported percentage of the population infected underestimates the true number of infections. Again, this is most likely accounted for by a constellation of factors unique to New York, but still, the anomaly is quite noticeable, and suggests that the social distancing strategies that seem (whether this is true or not we don't know) to be beneficial elsewhere are of markedly diminished efficacy in New York.

6. No one can say with certainty whether there will ever be an effective vaccine.

7. Many of the countries, and American states who are assumed to report reasonably accurate data demonstrate an interesting phenomenon. The daily new case profiles seem to contain oscillations, with a period of six or seven days when there seem to be more, then less new cases, and these are superimposed on the underlying bell-shaped trend.

8. Using the data from Colorado, which reports new cases both as to date of onset of symptoms and date of diagnosis, it appears that "infectious period" used in the simple spread sheet models described previously is nine days.