Notes on Engineering Health, August 2021

Evolution and Public Health

What does it take for a virus to create new variants and to evolve into a more deadly foe? 

If we were to model the probability of a virus gaining a function — e.g., escaping a vaccine, increasing its virulence, or being more harmful to children — in the simplest possible way, we would describe it as a function of the virus’s mutation rate (M), its replication rate (R), and the evolutionary pressure applied to it (P) — the evolutionary, or selection, pressure being any change in the environment that advantages particular mutations in the virus that are passed on to the next generation. This simple probability function would look like this:

       P(Gain of function)=f(M, R, P) 

These types of models are developed by researchers when conducting evolution experiments on a plethora of organisms from viruses to bacteria to eukaryotic cells

R in these models is composed of both the replication rate of the virus in its host (Rh) and its reproduction rate from host-to-host, the now infamous R0. Breaking these two variables out, the probability function then gets only mildly more complicated:

       P(Gain of function)=f(M, Rh, R0, P)

Experimentally, the rates of mutation (M) and replication within the host (Rh) are parameters that are challenging to change as they are inherent properties of the organism. M and Rh depend respectively on how accurately and quickly polymerases replicate DNA (or RNA). What is clear is that low mutation and replication rates make the probability of a gain of function lower. 

P is, however, a parameter scientists can more easily control experimentally. For example, in a 2016 Science publication, a team of scientists created a striking visualization of how quickly E. coli can adapt to increasing concentrations of antibiotics. In this instance, the evolutionary pressure in the system is the antibiotic concentration and its increase by an order of magnitude at regular intervals. Depending on the desired outcome, the pressure has to be tweaked with precision: too high of a jump in concentration, the bacteria won’t be able to adapt and will be eradicated; too low of a jump, adaptation might not be necessary and a gain of function won’t occur. 

If we turn our attention to the COVID-19 epidemic, there is no doubt that some collective and individual actions can reduce the probability of producing a more deadly variant: reducing R0 by masking, and increasing P enough to eradicate the virus by getting vaccinated are the most obvious methods. The US (and the entire world really) are currently in a dangerous phase where the vaccination rate is high enough to promote the selection of mutations that will evade the vaccine’s efficacy but still too low to eradicate the virus entirely. It is important to note that the effect of vaccination on the ability of the virus to spread (and thus mutate) is hard to measure but is clearly not linear. According to data from and recent models, the highest risk for vaccine escape occurs at intermediate levels of vaccination. Not getting a vaccine when the opportunity presents itself and entrenching uneven access to vaccines across the globe boost the emergence of new variants, and the likelihood that one of them will eventually evade the existing vaccines is all but certain. 

The giant evolutionary experiment we are collectively, and largely unwillingly, part of is following well-studied rules and everyone should understand them. If you want to read further, here are good recent articles from STAT and the The Atlantic that go over these rules, and a PLoS article that goes into greater technical detail. 

Jonathan Friedlander, PhD & Geoffrey W. Smith