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Causal Relationships

Causal Relationships

April 28, 2020 · C.E. Carter

Federal and state health officials claim there exists a causal relationship between taking distancing measures, like economic shutdown, and the mitigation of the spread of infectious disease. They won’t use the words “causal relationship” outright, but their adamancy that officials force the adoption of these distancing policies is indicative that they believe very strongly that “if we do social distancing, then COVID-19 will be mitigated”.

Let me credential myself for a second, before we get too far into this. I have a Bachelor’s Degree in Mathematics from Clarkson University. My coursework and research work focused on mathematical modeling and Bayesian statistics, which are disciplines that seek to understand and model real-world phenomena in order to draw conclusions and make policies. During my education I collaborated with professors and graduate students on a great variety of research work pertinent to these kinds of problems. So, I often know enough of what I’m talking about to be able to tell when someone else is trying to pull the curtain over my eyes.

To establish a causal claim based on empirical information, you must demonstrate beyond a reasonable doubt that some phenomenon was the cause of another. It’s as simple as that; don’t think too hard about it. To do this, we look for things that any ordinary person would look for when establishing causality:

  1. We must be sure that the supposed antecedent event actually occurred in some logically prior fashion to the supposed consequent. If you claim that event A caused event B, but B occurred before A, you know that A could not have caused B based on every sane theory of time and cause-and-effect. If you claim that drinking coffee made you jittery, but you felt jittery before you had any coffee, then the coffee didn’t cause the jitters.
  2. We must demonstrate the consequent under the proposed conditional, and the negation of the consequent under the counterfactual conditional (you might be thinking to yourself “slow down there, boy”). All this means is that we must be sure that event A caused event B by checking the case when event A is not the case. If we see that A implies B, but also that the negation of A implies B, then we know that B must be caused by something other than A. If you claim that a drug treats a disease, but sugar pills also seem to treat the disease, then you can’t conclude that the drug was the cause of the disease being treated.

Hold that second point in your head.

Every major modernized nation on the planet has adopted social distancing as a mitigation strategy, but without any one of them not adopting distancing measures there is no way to be sure if the distancing caused the lessening of the outbreak or not. There is no way to tell if distancing caused the mitigation, or if the virus just ran through the population quietly and people became resistant to reinfection, mitigating the disease. There is no way to tell if the initial projections were accurate and distancing caused mitigation, or if the initial projections were blown way out of proportion and the virus spread through the population as it normally would have without distancing. We don’t have any sugar pills, and thus, we don’t have a reliable counterfactual situation yet from which we could draw inferences (although I’m holding out for Sweden to be a prime example).

No matter how convincing the arguments from health officials sound, unless we have counterfactual evidence of statistically significant unmitigated disease spread in the absence of social distancing, there is no evidence that social distancing and economic shutdown is an empirically verified method of mitigating COVID-19.

So, what justification do health officials have for distancing?

Most of the decisions surrounding this disease have been formulated based on computer models. Basically, an epidemiologist comes to an applied mathematician like me and says “this disease has rate of spread x, and case-fatality rate y, and preexisting cases z, etc., show me what happens if an outbreak occurs”, and I build a mathematical model to simulate in the computer. This is called “modeling from first principles” as opposed to “data-driven modeling” which is done in the empirical analysis of causality. Modeling from first principles is great when you don’t have a lot of data about a phenomenon you would like to understand, but you do have some idea for the mechanism of the phenomenon. This is why it’s used so often to model disease outbreak; representative data is hard to come by. By making a model from first principles, you can run through a bunch of different scenarios as to how the outbreak would respond to different situations, like different levels of distancing, and you could construct your own causal analysis based on the assumptions of the model you built.

The problem with this is the heavy reliance on the assumptions of the computer model. If one parameter of the model, say, the rate of spread of the disease, or the case-fatality rate, or the numerosity of preexisting cases, etc. is sufficiently off, then the results of simulating the model are no longer indicative of reality, and the policies that were inspired by the simulations are groundless. New data from studies about the nature of the disease should be used to update the parameters of the model so that better policies can be made.

What new data do we have?

  1. It is likely that the virus is able to travel through the air much further than 6 feet. On particles emitted from human breathing and talking, some studies suggest that the transmission distance can be as much as four times the CDC recommended social distancing distance. Other studies have found that the virus can easily travel on air pollutants for much, much further.
  2. The virus can last for much longer than was previously anticipated on non-porous surfaces like steel or smooth plastic, which are often found in grocery stores, drug stores, gas stations, and other public places which must be frequented by every American household.
  3. Antibody testing in the state of New York suggests that about 1 in 4 residents of New York City had contracted COVID-19 at some point in the past few months. The new estimates suggest a case-fatality ratio of about 0.5%, which is almost a full order of magnitude less than the original estimates of 2-5%, and about 4-5x what the ordinary seasonal flu is.
  4. These antibody studies also make a strong case for the preexistence of the disease in the United States. This is especially compelling given the evidence that the disease is now though to have originated in China much earlier than we thought. Anecdotal evidence from my own research suggests that many people I know could have had the disease around mid-January, including myself, my parents, my siblings, their coworkers, and my coworkers. COVID-19 is a highly asymmetric disease, meaning the symptoms don’t manifest the same way for every case, so if you had a strong headache, chills, sweats, fatigue, joint aches, or a strange foot rash a couple of months ago, you may have had COVID-19, and you may have spread it to everyone you interacted with around that time.
  5. Most researchers have re-specified their computer models, and have revised down their estimates of the number of cases and the number of deaths due to COVID-19 by orders of magnitude.

This new evidence suggests that the virus is far more contagious than we previously thought, capable of traveling yards through the air on human breath (or perhaps hundreds of yards via other means), which renders the six foot social distancing guideline about as useful as remaining any other arbitrary distance away from people, including the normal distances at which people normally interact with one another during periods of societal normalcy. It is just as unsafe to go the park or to the grocery store with someone who has COVID-19 as it is to go inside a small business with someone who has COVID-19. It also suggests that the virus is far less deadly than we thought previously, with a case-fatality rate on the order of a very bad flu with a vaccine. Demonstrably, the assumptions of the computer models created by the CDC and other heath researchers are wrong, as evidenced by the dramatic differences in both the contagiousness and the deadliness of the disease, and that means that the simulations of the models are likely off by several orders of magnitude. Therefore, based on first principles, there is no evidence of a causal relationship between social distancing and the mitigation of COVID-19.

The American people have been told that complete economic shutdown and the revocation of the Constitutional Right to Assemble (endowed to us by our Creator, mind you) is a necessary cost to “stop the spread and save lives”. Officials, with the information at the time, weighed the options of leaving the country free under the impending deadly contagion, versus a shutdown with a mitigation of the contagion. The obvious option was shutdown. In light of new evidence, the game would be more strategically played by taking advantage of the low case-fatality ratio by isolating at-risk populations (old, immune-compromised, obese, etc.) and letting the more resilient populace return to normal societal functions in order to establish herd immunity to COVID-19. This, accompanied with continued research and testing efforts, will give researchers a greater body of data to understand the epidemiological dynamics and medical characteristics of the disease. The high contagiousness of the disease would mean it would run through the more resilient population in a matter of weeks with relatively little load on the health care system.

With all of this in view, I have little faith in my government to admit its wrongdoing, even if it is more of a catastrophe to its own people than any virus could be. In the state of New York particularly, I would like to believe that Governor Andrew Cuomo is a man who is able to admit that his decisions overstepped the reasonable actions which should have been taken against COVID-19, in addition to the Constitutional rights of all New Yorkers to exercise their freedom to assemble. But, if I had to estimate more realistically, I see within Andrew Cuomo no intention to give New Yorkers their rights back anytime soon, even if it comes to complete economic devastation.