In this issue, I dig into another discussion of variance where we apply the concept to examine COVID-19 response and prevention. Thank you for subscribing, and if you enjoy reading this, please forward the newsletter to your friends. ~ Kevin
A few weeks ago we talked about polling numbers and the issue of variance. We discussed the fact that there was more variance between in the results of several national polls as compared to several smaller state polls. The concepts we discussed a few weeks ago have many applications and might provide an informative way for us to look at Covid-19. Learning how to cook one dish can sometimes help us learn how to prepare another.
P.S. When I was in Miami I enjoyed eating a famous Venezuelan beef dish and this weekend I made an attempt that you can view below. I miss Amaize!
Specifically, I discussed the idea of variance, which points to the degree things deviate from the average. High variance changes a lot and low variance changes little. For example, I would characterize the daily temperature every October as high variance from the average. In contrast, the number of average laughs I get from jokes is a low average and low variance. On the campaign front, before the events of what felt like a long weekend, Florida maintained a higher variance for Trump's polling numbers. But there was a low variance for Biden and Trump in Pennsylvania and North Carolina. Good old Ohio deserves to be in the mix for future analysis.
How does the topic of variance relate to learning more about Covid-19?
Analysts, including Dr. Tufekci, have recently argued for approaches that consider both the average infection rate (R0) of Covid-19 as well as the variance. Several studies indicate that the average person who gets Covid-19 will infect about 3 other people. I believe it is worth asking, how average is average? We are now learning that it is not uncommon for one or even zero to be infected from a single COVID patient. So what is pushing the average to 3? Super spreaders. As we know, these are folks who may be knowingly or unknowingly spreading the disease. While there may not be a drastic number of super spreaders, every day there are a few who have a dramatic effect.
At this point, it is not clear what characteristics super spreaders have, other than the fact that they interact with a lot of people. In fact, that may be the only pattern of their behavior we are able to identify. However, this factor can be kept in mind as practices and policies are established. As a society, we should not hear this and become discouraged or defeatist.
Even though there are a few super spreaders, there are effective approaches that can help to counter their impact. Perhaps the most important approach in the U.S. this year was the rapid canceling of large events. Curbing large gatherings indoors is also extremely important to lessen the impact of the super spreader. Part of the risk with large gatherings indoors relates to the size of the group. But such events also raise concerns because it is believed the virus stays airborne longer due to ventilation and air conditioning.
Also, Dr. Tufekci makes a strong policy argument for backward contact tracing. This would more accurately help locate some potential super spreader cases. Backward tracing would look at a patient who recently was diagnosed and find out whom they came in contact within the days before they were known to be sick. This is not to determine whom they infected (which is important) but rather to determine who infected them. Probabilistically, this approach can help identify potential super spreaders and quickly trace their interactions to break transmission chains. My non epidemiological mind looks at it like a tree. The forward tracing is like the branches of recent interactions by the patient, whereas the backward tracing looks at the root sources for how the patient contracted COVID-19. With robust testing and contact tracing infrastructure in place these approaches can help further reduce spread.
We are witnessing the confluence of this practice, potential seasonal increases in COVID-19 cases, and the likely distribution of a vaccine in the year ahead. Hopefully, the vaccine comes soon. But regardless of when an effective vaccine is widely available, we will benefit by considering the role of variance, super spreaders, and effective ways to minimize spread across social clusters.
At the end of the year, I plan on diving into lessons learned from 2020. Two parts come to mind including humility when developing expectations in our lives. Another lesson is considering the effect of the seemingly small thing like the rare super spreader can have in molding our world. I think society can regularly conflate the important events and assume large groups or forces are behind them. This perception is further challenged because those who may have major effects in one circumstance can have negligible influence in another. This year we have had countless examples of the effects of a small virus, small sparks, small errors, small actions, and small thinking. The only thing that seems large is the number of words trying to explain these small things… with little success.
News:
Thought:
I am enjoying the chance to share these newsletters with you in the form of the new podcasts and appreciate your continued feedback. You can reply to this email or leave your comments below. I sincerely enjoy chatting and learning what folks think. Thank you ~ Kevin
The Real Deal:
My attempt:
COVID-19 and Variance