There’s an article that talks about a better way to think about COVID-19.
I must admit I’ve been learning a lot about epidemiology and disease transmission lately.
In any case, the point of this article is that we’re not thinking about about the way COVID-19 is actually being transmitted, as opposed to other infections.
As I mentioned in my previous post, we have mainly been worrying about the R∅ of SARS-CoV-2. If it’s higher than 1, then there is a chance for increases in transmission. The previous pandemics have largely been due to influenza, and the R∅ for the 2009 H1N1 pandemic was estimated at 1.46. An R∅ of <1 would ultimately not be self-sustaining, and would die off quickly.
And this is what we’ve been trying to do this whole time. Because R∅ is also dependent on our own behavior. By socially distancing and wearing masks, we have been able to keep the R∅ to smaller numbers. Yet, even with all our precautions, we have paroxysms of infections, each setting off little shock waves.
Apparently, our main issue is thinking that COVID-19 acts the way influenza does in terms of its infectivity. Influenza has a fairly consistent transmission. Once you figure out “how infectious” a specific strain is, every person with it generally will infect a number of other people, where the number they infect is R∅. This results in a consistent, linear relationship, known as a deterministic one.
With SARS-CoV-2, apparently this is not the case. While most people don’t infect anyone (i.e., an R∅ of <1), there are a certain number of people who can be considered “super-spreaders", who can infect a huge number of people if the conditions are correct—there was one South Korean person who infected 5,000 within a megachurch. The problem is that we don’t know what makes people a super-spreader. Maybe they’re really loud? Carry a lot of virus in their nasopharynx?
Ultimately, what this means is that transmission does not follow the predictable linear fashion of a deterministic infection, where the R∅ is also the overall transmissibility. Rather, the k of the disease is large. And what is k? It’s a measure of the variability of the disease transmission. Think of it as the standard deviation (or, for us in medicine, the RDW of the CBC). With a large k, we are pointing out that transmission is more chaotic, or stochastic.
So what does that mean for us? Well, when you find someone who is positive, there’s a significant chance that he or she is not that contagious. But if you do backwards contact tracing, you might be able to go back and find the super-spreader. And those people should be isolated until they are no longer contagious.
Furthermore, you should avoid creating conditions where super-spreader events can happen. That means: no crowds, wear a mask, avoid prolonged contact. But this moves the emphasis towards avoiding large crowds of people, especially if they are not wearing masks. A perfect example is the recent Republican meetings at the Rose Garden, where a number of people have since become positive. While it was outside, there was prolonged physical contact amongst the attendees, and no one was wearing a mask.
This means that we have a way to fix it, but it requires people to actually wear masks and care for their fellow American, which apparently is not possible for a significant number of people in the country. We will see what happens as this moves forward.