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Without A Vaccine, Herd Immunity Won’t Save Us

Daniel Arlein has already had COVID-19. In March, the 36-year-old small business owner and DJ, who lives in Brooklyn, tested positive for the viral infection and suffered through two weeks of flu-like symptoms.

Arlein has since recovered, and while he’s still being careful — avoiding leaving the house, washing his hands more often and wearing a face mask — he can’t help feeling a bit relieved to have already had the infection.

“The only way it’s helping me is psychologically, to be able to go out in the world and still be careful but not be freaked out that I’m going to get sick,” he said. “I have no idea if I will get sick again. I feel like I won’t, but I have no idea if I can get it again.”

Most people understand immunity to mean that once a person has been exposed to a disease, they can’t get it again. It’s an easy concept to grasp, and some people have hoped that widespread immunity could be the way out of this pandemic: If enough of the population becomes immune to the disease, the spread would be stopped, since the virus would run out of new, susceptible targets. The “herd” of immune people would protect everyone.

But getting to herd immunity without a vaccine isn’t as simple as the idea itself. A number of variables can affect when herd immunity is reached — and what it costs to get there — and they vary depending on the disease. How infectious is the disease? How deadly is it? And how long do people stay immune once they’ve gotten it? Adjusting any of these variables can drastically change the outcome of this equation. You can probably sense where this is heading …

We’ve built a very simplified version of how those variables interact. (You’ll see just how simple in the methodology beneath the simulator.) To be clear, this is not about COVID-19 itself — instead, our calculator shows how a theoretical disease we’re calling Fictionitis would play out in a population that has never encountered it before and does nothing to try to stop it.

You’ll notice that each variable plays a role in setting a herd immunity threshold and reaching it.

The more people a person with Fictionitis infects on average, the higher the herd immunity threshold rises, but the faster spread also means that the threshold is reached more quickly. That, of course, can lead to a huge portion of the population getting ill at once, which would overwhelm hospitals. Unless the death rate is extremely low, that would be a devastating mix. A disease that doesn’t spread as readily will stick around for longer, but it helps maintain a flatter curve.

If you shortened the immunity duration, you may have also seen that the blue bar showing how much of the population is susceptible rose again even after the herd immunity threshold had been crossed. That’s because if immunity fades while the disease is still active, people who were previously immune once again become at risk for infection. Herd immunity only truly works while the recovered population has immunity to the disease.

For COVID-19, of course, we can’t change these variables, and we still haven’t nailed down their exact values, anyway. What we do know so far paints a stark picture: This disease is too deadly, too contagious and too new to depend on post-infection immunity (as opposed to immunity via vaccination) as a solution. Naturally acquired herd immunity is not the answer.

What is herd immunity?

If everyone in a population is immune to the infection, it can’t spread. But we can prevent a disease’s spread even without everyone being immune. If enough people are immune, the infection is unlikely to spread to big swaths of vulnerable people because those who are immune, the “herd,” protect them. The more people who are immune, the more likely it is that infectious people will only come into contact with people who cannot be infected, ending the spread. This creates a societal barrier between the infectious and the vulnerable.

The moment when herd immunity kicks in depends on how contagious the pathogen is, which is measured by what experts call the basic reproduction number, or R0 (pronounced “R naught”). The R0 is simply the average number of people an infectious person will spread the disease to in a population where no one is immune, so an R0 of 3 would mean an infected person spreads the disease to, on average, three other people while they’re contagious.1

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The higher the R0, the higher the proportion of the population that needs to be immune to stop its spread. This is known as the herd immunity threshold, and the formula for finding it is actually pretty straightforward: 1 – 1/R0.2 For a really contagious disease like measles, which has an R0 between 12 and 18, 93 to 95 percent of the population needs to be immune to stop the spread (this is why the U.S. has had recent measles outbreaks when vaccination rates dropped even slightly).

“The higher the proportion in a population that is infected, the fewer places there are for that virus to go, the fewer people are susceptible to being transmitted,” said Greta Bauer, an epidemiologist and biostatistician at Western University in Ontario, Canada. “That makes sense, right? If one person, on average, infects two other people but half the population is immune, they’re only going to be able to infect one other person.”

For COVID-19, we’re still not certain what the R0 is, so we don’t yet know what the herd immunity threshold is. For now, it’s estimated to be anywhere from 70 to 90 percent. But here’s the problem: To reach even the lower end of that range naturally in the U.S. — imagine giving up on any interventions and just letting the disease run its course — 230 million Americans would eventually become infected and, depending on the fatality rate (more on that later), millions could die.

And reaching herd immunity as the outbreak is raging is a completely different scenario than, for example, doing so after a vaccine has been created. With a vaccine, you can immunize people before they’ve encountered the virus, so by the time the virus gets to a vaccinated population, it has nowhere to spread. But in an active outbreak, even once the herd immunity threshold is reached, the infection keeps going. It takes time for the spread of the disease to crest because, for a while at least, many contagious people will each still infect a small number of vulnerable people, which means even more people will get sick and die. It’s a phenomenon known as “overshoot.”

“The disease sort of stops increasing at the point when you reach herd immunity, but there’s still lots and lots of people infected. It only slowly goes down, and on its way down, [it] infects another third of the population,” said Richard Neher, an evolutionary biologist at the University of Basel in Switzerland. “If you drive a car and suddenly you switch off the engine, it doesn’t stop instantly.”

So think of crossing the herd immunity threshold as determining the fate of the disease (it’s now bound to die out) rather than its status (it’s dead).

Since the new coronavirus is highly contagious (meaning a large percentage of the population would have to get it to slow its spread), the human toll of reaching herd immunity without a vaccine would be staggering. And that’s assuming that once a person gets sick, they stay immune for a long time. But at this point, we don’t know if that’s the case.

How long are we immune once we’ve had it?

To reach that herd immunity threshold we either need a vaccine, or we need a lot of people like Arlein who have had the virus and are now immune. Except we don’t actually know if Arlein, or anyone else, is really immune.

Typically, when we encounter a new pathogen, our immune system mounts a defense that includes producing antibodies to fight off the infection. Afterward, some of those antibodies and immune cells hang around, allowing our body to “remember” the offending microbe and more easily fend it off in the future.

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“The vast majority of anything that you or I have been infected with in our lives, our immune system has developed immunity to and remembers,” said Shane Crotty, an immunologist at the La Jolla Institute for Immunology in California. “There are definitely exceptions, but that’s the norm.”

Those exceptions are why experts, including the World Health Organization, can’t presume that having had COVID-19 means you can’t get it again, even though antibodies have been detected in recovered patients.

“The presence of antibodies, everybody thinks that means immunity, but I study HIV and there’s a huge antibody response to HIV, and it’s never able to neutralize that virus,” Bauer said.

Researchers have begun trying to find out how much protection COVID-19 antibodies give people who’ve recovered from the disease. There’s a chance that the immune response from COVID-19 is enough to prevent someone from getting sick again, but not necessarily from getting infected, which means they could still be contagious to others, according to Crotty.

It’s likely COVID-19 confers at least some immunity, though. For one, there are no confirmed cases of someone getting COVID-19 twice. Early reports from South Korea drew a lot of attention after patients tested positive for the virus again weeks after having recovered, but researchers later said that dead virus fragments from the original infection likely triggered the positive tests, rather than a second infection. One early study from China — which has not yet been peer reviewed, so take it with an extra grain of salt — also measured neutralizing antibodies in 94 percent of patients.

Previous research done on similar coronaviruses, like the ones that cause SARS and MERS, also offers some promising signs. In a mouse study testing a SARS vaccine, for example, researchers stimulated an immune response that staved off a dose of the virus.

But why would we fail to become immune to a disease? There are a few things that could be happening. Our bodies could stop short of completely killing off the virus in the first place, allowing it to lie dormant and reemerge later (that’s the case with HIV). The virus could evolve enough that our old antibodies won’t work anymore, whether we got them from natural exposure or a vaccine (this is what the seasonal flu does, and it’s part of why we need a new vaccine every year). Or the immune response we produce could just fade too quickly, making us susceptible to reinfection almost immediately.

With the new coronavirus, there’s not much evidence that either of the first two scenarios is in play, but the third possibility — that our immunity fades quickly — remains an open question, and one we won’t be able to answer until more time has passed. Coronaviruses also cause common colds, after all, and humans seem perpetually susceptible to those. In one oft-cited study, for example, people were given a dose of a cold-causing coronavirus, got sick and recovered, then were given another dose a year later. Most of the patients got reinfected, showing how quickly their immunity waned. (And most of them didn’t get sick, which opens up a whole new barrel of fun: If COVID-19 works the same way, some people who had the disease and recovered could wind up picking up — and spreading — the novel coronavirus again despite not being symptomatic.)

“One reason is because your immune system just doesn’t remember all things equally, and to some extent that memory is tied to how severe the initial infection was,” Crotty said.

That said, for SARS and MERS, both of which were also caused by coronaviruses, immune memory cells were detected in patients several years after infection, though because those outbreaks have ended, we don’t know if those immune cells would protect against reinfection.

The only way to know if COVID-19 immunity lasts for, say, 10 years is to wait until a decade has passed and see if anyone who was infected once ever got reinfected. (We’re just full of good news, aren’t we?)

Who’s had it?

Even if it turns out that infected people become immune for some period of time, we still aren’t close to herd immunity solving our COVID-19 problem for us. So few people have had the disease that we’re nowhere near herd immunity yet, and the fatality rate is so high that closing that gap would be devastating.

Eventually, reliable serological tests, which detect antibodies, can be administered to large samples of the population. That will give us a better sense of how many people actually had the infection, and thus the disease’s true fatality rate. There was some hope that these serological surveys would reveal the disease was much more widespread — and therefore way less deadly — than we thought. If, for example, you have 50 deaths in a community and 1,000 recorded cases, the fatality rate is 5 percent (50 out of 1,000). But if a serological survey of that community later revealed that there were actually 3,000 cases, that fatality rate drops to 1.7 percent.

Unfortunately, early serological surveys suggest the fatality rate isn’t low enough to offer us much comfort.

In the U.S., there have been 81,507 deaths as of May 12.3 For a fatality rate of 0.1 percent, the same as the seasonal flu, we’d have to find out that 81.5 million Americans, or nearly a quarter of the U.S. population, had already had COVID-19. But based on early serological surveys, the World Health Organization says it’s likely that only about 2 to 3 percent of the population has been exposed so far.

Some serological surveys have reported wildly different estimates of how many people may be immune. A recent survey in California, for example, found that something like 2 to 4 percent of the population had antibodies, while studies in Germany and Massachusetts found antibodies in 15 to 30 percent of those tested.

One reason for these huge variations could be that rates are genuinely higher in hotspots. Indeed, in New York, the hardest-hit city on the planet, as much as 21 percent of the population may have already been exposed, according to preliminary results from a serological survey. But if even in New York, less than a quarter of the population has antibodies, it’s pretty unlikely that levels are nearly that high in the rest of the country. And New York has also seen a huge number of deaths: at least more than 19,563 as of May 12. Even if this early estimate is correct and 21 percent of New York’s 8.4 million residents have already been infected, that comes out to 1.8 million people, which still puts the current fatality rate at 1.1 percent, or more than 10 times that of the seasonal flu.

“Looking at what percentage of the population might actually have been infected, the numbers of the cases are much higher and the case fatality rate looks like it might be around half a percent,” said Jeremy Rossman, a virologist at the University of Kent. “People say, ‘Oh that’s a trivial number, it’s minuscule.’ But, when you think about, say, the population of the United States, 0.5 percent is a tremendous number, and these are people’s lives.”

The other potential explanation for why those serology survey results are all over the map is there may be problems with the way they were conducted. None of the papers mentioned above have been published in peer-reviewed journals yet, and many experts have raised concerns about false positives and how people were recruited for studies, suggesting even these low levels might be overestimating the true prevalence of the disease.

So let’s go back to that 70 percent herd immunity threshold. If the fatality rate is around 0.5 percent and 70 percent of Americans have to get sick before their immunity starts protecting others, that means more than 1.1 million people would die. In New York, even having 21 percent of the population exposed, if that serological survey is accurate, has overrun hospitals and led to the death of one in every 400 New Yorkers, while the vast majority of the population remains susceptible.

“That’s the cost of getting to 20 percent,” said Emma Hodcroft, a postdoctoral epidemiology researcher at the University of Basel in Switzerland. “It really illustrates the price you’re going to pay if you want to get up to the 60 percent or 70 percent that you’ll need for herd immunity, and I hope it really illustrates why that just isn’t a feasible plan.”


  1. Of course, many illnesses aren’t spreading among a population where no one is immune, so to calculate the spread of a disease people have encountered before, you need R, the effective reproduction number, which changes depending on the circumstances — immunity can make the R go down, but so can public health actions like social distancing.

  2. In practice, finding the threshold is a little more complicated. That formula relies on a number of assumptions, including that infected and vulnerable people behave similarly and that immune people are distributed pretty evenly throughout the population, which isn’t always the case. With COVID-19, for example, some working papers have suggested that since not every individual is equally susceptible, and more susceptible people (like front-line workers, who are encountering more potentially infectious people than those who are able to stay home) will tend to get a virus early, its spread might start to slow as it runs out of the most susceptible people and increasingly has to spread among less susceptible people, like those who have fewer contacts.

  3. As of 6:00 p.m.

Kaleigh Rogers is FiveThirtyEight’s technology and politics reporter.

Julia Wolfe is FiveThirtyEight’s former senior editor, data visualization.

Laura Bronner is a senior applied scientist at ETH Zürich and FiveThirtyEight’s former quantitative editor.