Epistemology and COVID 19

In the 20th Century, the philosopher  Karl Popper  drew the boundaries of demarcation between science and pseudoscience in terms of falsification. Exactly what Popper did and did not mean by falsification can be disputed. But the history of the philosophy of science throughout the 20th century has at leats taught us that distinguishing warranted and unwarranted claims to knowledge is more complex than simply shouting “non falsifiable” in crowded theaters. Or as one of Popper’s disciples Imre Lakatos  put it, “negative criticism does not kill a research program.”  At any rate, it doesn’t kill it instantly. While criticism is essential to good science, it’s not sufficient: you need to go further and provide a better theory. Simply poking holes, real or imagined in a scientific theory is not sufficient to establish that the theory is entirely unreliable. If the best explanation we have to date is reliable then rather than rejecting the theory, we should act on theory while we work to improve it. This is particularly important when we are dealing with phenomena such as the COVID 19 outbreak. As of today, there are approximately 1.2 million confirmed cases and 64,700 deaths attributed to COVID globally and roughly 8500 total deaths in the US (See data from John’s Hopkins ). Estimates of statistically expected deaths in the US alone, even with stringent measures, range  from approximately 85,000 to over 200,000.  If one wishes to engage in measuring the likelihood of one’s own death you can do so here. Estimates of deaths without stringent measures in the US are approximately 2 million.

The idea that science is fallible and subject to revision is well understood, at least among those acquainted with the philosophy of science, though not always with the general public. Similarly, there are areas of science such as epidemiology which have to deal in probabilities that are 1) conditional on human responses, 2) based in assumptions where we lack full information and 3) potentially subject to a degree of actual uncertainty. Nor does it help that the lack of understanding of statistics runs rampant in the general public and that government officials and the media provide simplistic accounts of these issues. This combination provides ample ammunition for those who are skeptical of the information reported by the CDC and critical of stringent measures to control the spread of COVID 19. But that does not mean that they are correct.

To get a sense of the range of opinion that for lack of an immediate and accepted term I will call the “lock down deniers” I recommend the following sites which range from quasi mainstream to the fringe: Just FactsGateway Pundit  , and Truth to Power, or, have a look at this You Tube video .  I confess to having no idea as to what constitutes “legitimate” or “representative” among the deniers but these sites clearly echo themes that have seeped into national discourse in multiple ways. For the record, I fully agree that crises such as the one we are experiencing can be, and often are, used to erode the kinds of liberties protected in our Constitution. We should indeed be vigilant against abuses but that cause will not be served by unwarranted claims. In addition, the consequences of erroneous claims in this instance are high, involving, potentially millions of lives. Rather than delve into the arguments about whether or not 5G networks are significant contributor to mortality from COVID 19, I will focus on  a few of the quasi mainstream arguments.

  1. The death rate for those who contract COVID 19 is closer to the flu than is reported.

This is almost certainly true and is widely acknowledged. There’s no cover up here. But to say that it is “closer” to the flu doesn’t tell us very much. Thus far, the best information we have is that the global mortality rate from reported COVID 19 cases is running at about 6%, a number that is much higher in fact than the standard 2-4% estimates. This figure varies significantly country by country and also seemingly by the stage of reporting. It is widely acknowledged that there are an unknown number of asymptomatic cases as well as cases that did not lead to reports. If we guesstimated a mortality rate for the entire population of 1% and an infection rate of 30%, that would result in over 1 million deaths in the US alone. That is still much higher than the flu. The assumed presence of a large number of asymptomatic cases is also part of the problem as it increases the likelihood of contracting the disease.

     2. More people die from accidents and suicides

So far. But if conservative estimates of a statistical 84,000 deaths given public adherence to stay at home orders are valid, that is substantially higher than accidents and suicides. So we are talking about “excess mortality”.  By comparison, approximately 50,000 US military personnel died over 13 years in the Vietnam War. If we are acting to prevent 1 million deaths, then that number exceeds all US military personnel lost in wars other than the Civil War. By comparison, approximately 600,000 military personnel perished in the Civil War.

     3. Corona virus is less susceptible to evolution, will not mutate and is unlikely to recur

It is difficult to discern what this claim is based on. It has already evolved going from Bats, to Pangolins, to humans and then to human to human spread. There are multiple strains already and the more opportunities we give it to spread, the more it will spread.

    4. The age distribution of mortality means that the costs of the disease are less severe.

I leave it to the reader to weigh the values implied by this statement.

2 thoughts on “Epistemology and COVID 19

    1. If anything, my views have strengthened. The initial models predicted 1-2 million deaths, if no preventative steps were taken to stop its spread. The prediction was that deaths would be 100,000 to 200,000 deaths with preventive measures. We have now witnessed approximately 570,000 deaths as of today, with case mortality as predicted from the beginning at 1.5% to 2%, and hospitalizations at about 20%. Add to this the impact of long term after effects from COVID. These numbers are borne out by excess mortality data and have been pretty consistent globally.


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