One day, Alice gets sick.
This is Charlotte. She is healthy.
Although Alice is contagious, she cannot infect Charlotte because they do not spend any time together.
Enter Bob, a mutual friend.
Alice makes Bob sick, and Bob makes Charlotte sick. Charlotte gets sick even though she never spent any time with Alice.
Let’s back up and try again. Alice is sick and Charlotte is healthy, but this time, Bob is immune.
An immune Bob acts as a wall between Alice and Charlotte, and Charlotte never gets sick. The disease is unable to spread.
This is the essence of what disease experts call “herd immunity.” Although Charlotte was susceptible to the disease, she was protected by someone else in her community — her herd — who was immune.
In communities larger than Alice, Bob and Charlotte’s, a spreading disease will slow and eventually stop once a certain share of the population becomes immune. Epidemiologists call that percentage the “herd immunity threshold.”
To see herd immunity in action, we can watch as a fake disease — we will call it simulitis — spreads through three communities, each of 200 people. In the first community, no one will be immune to simulitis. In another, 40 percent of the people will be immune. And in the third, 80 percent will be immune.
As you watch the simulations below, notice how in the 40-percent community, simulitis manages to infect many healthy people. Only once the share of immune people crosses a certain threshold — for simulitis it is about 80 percent — are most of the healthy people protected from the sick people.
Each time you restart the simulation, the immune people scatter randomly, opening new paths for the disease to spread while closing others. Try as it might, simulitis rarely spreads far in the community on the right.
The herd immunity threshold of real diseases varies. Measles, an especially contagious disease, only slows down after about 95 percent of people become immune. Scientists are still determining the herd immunity threshold of SARS-CoV-2, the coronavirus that produces the deadly disease covid-19. Estimates range from about 40 percent to about 80 percent.
As the coronavirus continues to spread across the United States, some have suggested that rather than try to disrupt it, it would be better to let it run its course. In time, they argue, there will be so many immune people that the virus will stop spreading on its own.
The United Kingdom and Sweden pursued such a strategy early on but abandoned it when officials saw it would not work. More recently, television host Laura Ingraham tweeted that pursuing herd immunity was the “only practical way forward.”
Yet even if coronavirus antibodies prevent repeat infections — an assumption still being studied and debated — evidence suggests the United States remains far from achieving herd immunity. To get there, Americans would probably have to endure a scale of death and loss many times greater than they already have.
One way to measure the gap between herd immunity and reality is through seroprevalence surveys, in which researchers draw blood from thousands of people and check to see how many of them have coronavirus antibodies. Because people infected with the coronavirus often fail to show symptoms, these surveys can reveal more people with antibodies than case numbers alone would suggest.
In late July, the Centers for Disease Control and Prevention published the results of coronavirus seroprevalence surveys at 10 sites across the country. Compare those results to a 60 percent herd immunity threshold, the midrange of current estimates.
Coronavirus herd immunity threshold
vs. serosurvey results
New York City, by far the closest to achieving herd immunity, was somewhere between one-half and one-third of the way there. This, in a city where more than 23,000 people have already died of covid-19 and at least 230,000 people have tested positive for the coronavirus.
The CDC data is based on blood tests conducted months ago, so it is likely that the country has moved closer to reaching the herd immunity threshold. To measure how much closer, a team of nine scientists from Harvard and Yale universities built a statistical model that estimates the share of people in each state who have had a coronavirus infection.
Seroprevalence in the United States, they estimate, stands at about 9 percent. Even in New Jersey, the state whose population has the highest share of antibodies, seroprevalence is estimated to be only about 20 percent.
Coronavirus herd immunity threshold
vs. modeled seroprevalence estimates
“There’s just way too little seroprevalence in all of these states to come anywhere close to achieving herd immunity,” said Marcus Russi, a Yale epidemiologist who helped build the model.
Even the higher range of the estimates, which suggest seroprevalence in the United States could be as high as 25 percent, remain far from the herd immunity threshold.
To build herd immunity without the sickness and death of uncontrolled spread, pharmaceutical companies are racing to develop a coronavirus vaccine.
Making and distributing a safe and effective vaccine is part of the challenge. The other part is convincing people to take it, said Jason Schwartz, a vaccine expert at the Yale School of Public Health.
“There’s lots of consensus about the kinds of best practices that help disseminate evidence to help the public do well in a health crisis,” Schwartz said. “At the top of the list is to have very, very clear messaging that is amplified regularly, repeatedly, isn’t complicated or undermined or conflicted or muddled.”
Throughout the pandemic, Schwartz added, “there’s been such a cacophony of different messages, and that understandably has caused great confusion and ultimately great harm to the public. We can’t repeat that with respect to a vaccine.”
The alternative to waiting for a vaccine — letting the virus run rampant through a population unfortified by herd immunity — is far worse.
To estimate how much worse, just three numbers are needed: the total population, the coronavirus’s herd immunity threshold and its fatality rate — the percentage of infected people who die.
Multiplying those three numbers together reveals roughly how many people would need to die for the population to develop herd immunity. You can do the grim calculation yourself.
Cases to reach
Cases to reach
Deaths to reach
Reported covid-19 deaths
in the United states
Deaths to reach
Many thousands of additional infections and deaths would be expected even after herd immunity is reached.
“The epidemic doesn’t stop on a dime when you hit herd immunity,” said Carl Bergstrom, a biologist at the University of Washington who uses computer simulations to model populations’ vulnerability to disease.
“The herd immunity point is when you’re at the peak of the epidemic. So you’ve come up the curve,” Bergstrom added. “But you still got to go all the way back down.”