The race is on. Vaccines against the virus that causes Covid-19 are needling into shoulders around the world, the tip-of-the-hypodermic spear of a year-long scientific triumph. But that protean virus, like all the things that infect humans and make them sick, jukes and dodges.
Virology versus epidemiology. Vaccinology versus evolution. Mutation versus mutation, transmission versus infection, virus versus vaccine. Start! Your! Engines! The past (horrible, tragic, no-good, very bad) year might have seemed like a straightforward battle between scientists and a virus to find new drugs and vaccines. But this wasn’t just a stand-up fight; it was also a bug hunt—a subtle push-pull across a dozen different vectors. Viruses aren’t exactly alive, but they still follow the same rulebook as every living thing on Earth: Adapt or die. Understanding those more occult forces—how viruses evolve inside us, their hosts, and how they change the ways they get from one person to the next—will define the next phase of the pandemic.
It’s easy to freak out about new variants of the SARS-CoV-2 virus, with their science-fiction nomenclature. There’s B.1.1.7, which looks to be a whiz at infecting new people. And you’ve got B.1.351 and P.1—maybe not any better at transmission from host to host, but better at evading an immune response (a natural one, or the kind a vaccine induces). A bunch of the immune-escaping ones share the same single mutation, even if they’re only distantly related. That, as the saying goes, is life. “The way the virus evolves, the fundamentals of evolution, are the same. What’s different is that’s playing out on a very, very large scale. There’s just so many people who are infected, and each person has a lot of viruses in them. So there are a lot of opportunities for the virus to make mutations and try new things,” says Adam Lauring, a virologist at the University of Michigan who studies viral evolution. “Every now and then one of those takes off. It’s a rare event, but when the virus has so many opportunities to game this out, it’s just going to happen with increasing frequency.” This is as much a game of epidemiology, in other words, as it is one of evolutionary biology.
So while it can seem like these variants have some kind of evil intention—to make people sicker, to kill all humans!—that’s not what’s going on. Viruses don’t want anything; they’re just verbs. Infect, reproduce, infect. A virus that kills too efficiently doesn’t get to be a virus for very long, because dead hosts can’t walk around breathing on uninfected-but-susceptible suckers. So one hypothesis says that these successful mutations are mostly changes in the way the virus infects. That is, they improve the way the virus gets into a human, or gets into a human cell, or reproduces in that cell (because the more virus a person makes, the more they give off, and the more likely it is to get to some other person).
That’s probably why all these similar variants seem to be arising all at once, and quickly. Viruses are just nubbly little dollops of proteins wrapped around big molecules of code, of genetic material. In SARS-CoV-2, that material is RNA. And some viruses pop mutations more frequently than others.
Viruses evolve because they reproduce—in fact, that’s pretty much their whole shtick—and mistakes creep into that genetic material in the process. Over the course of generations, sometimes those random or “stochastic” mistakes actually make the virus better at doing its thing; sometimes they make it worse. Which is to say, the circumstances of a virus’s life, or sort-of-life, play out against random changes to the code underlying its genes. (SARS-CoV-2 seems to mutate at about the same pace as other RNA viruses, even though like other coronaviruses in its family it has a built-in error-correction mechanism. It needs it, because its genome is so big, relatively speaking—three times the size of the genome in HIV, the virus that causes AIDS, for example. “Without proofreading, it would likely create too many mutations per virus replication event to remain viable,” says Katrina Lythgoe, an evolutionary epidemiologist at the Big Data Institute at Oxford University. That kind of genomic suicide is called crossing the “error catastrophe threshold.”)
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