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THE CORONAVIRUS CRISIS
The end of this pandemic sometimes gets boiled down to two words: herd immunity.
But now, as an academic debate swirls over when or even if America can get to a high enough percentage of people with immunity to reach that goal, some scientists say it's time for the public to stop worrying about it.
"I think we're focusing too much of our time, our effort, on quibbling over a number," says Lauren Ancel Meyers, a professor at the University of Texas at Austin and head of the university's COVID-19 Modeling Consortium. Instead, Meyers and others say the public should follow one simple piece of advice: Get vaccinated.
How Herd Immunity Works — And What Stands In Its Way
"This pandemic ends when enough people are protected from severe illness, and selfishly you want to be protected from severe illness," says Devi Sridhar, a professor of public health at the University of Edinburgh in Scotland.
Vaccination "helps you and it helps your community."
What does herd immunity mean anyway?
The idea of herd immunity began with cows, not people. In 1916, veterinarian Adolph Eichhorn and colleagues noticed that a herd of cattle could become collectively immune to a disease if enough animals survived the initial infection.
Since then, the herd immunity threshold has become a commonly used term in epidemiology to refer to the mathematical tipping point of an infectious disease outbreak. When a certain percentage of people are immune, either through infection or vaccination, a virus runs out of places to spread. The epidemic — or, in this case, the pandemic — fades, and life goes back.
The threshold for herd immunity can vary widely from disease to disease. And with so many unknowns about the coronavirus, it's been a topic of much discussion. Over the course of the pandemic, estimates for the threshold needed to reach herd immunity have fluctuated from as low as 20% to as high as 90% or more of population.
The term herd immunity remained largely in academic circles until the spring of 2020. That's when, as the coronavirus spread across Europe, politicians such as British Prime Minister Boris Johnson suddenly found themselves talking about it on television.
The group of scientists advising Johnson at the time, according to Sridhar, included many modelers of the pandemic. Modelers build computer simulations, or models, of the future.
It was a time before vaccines, when the virus looked as though it was ripping through Asia and Italy unchecked. Some of the modelers Johnson was listening to "ran projections that showed that this was unstoppable, uncontrollable," Sridhar says. "And this led to this approach of 'herd immunity,' which is just let the virus go, let nature take its course."
It was the "take it on the chin" strategy as described by Johnson. This flavor of herd immunity was an appealing idea for conservative politicians and pundits who wanted to see economies kept open. But the policy was never enacted in Britain, in part because modelers at Imperial College London showed just how bad things could get. Today, it's widely accepted that letting the coronavirus run unfettered through a population would have led to an even more staggering death toll.
"I think if we could go back in time and they were completely honest, both the public health advisers and the leadership would say that's the wrong approach," Sridhar says.
But herd immunity stuck around in the public consciousness. Even into last fall, the Trump administration continued to toy with the idea of reaching herd immunity by allowing the coronavirus to spread mostly unchecked.
Then, when the first vaccines rolled out in December, the term got even more life — this time focusing on the immunity that's gained through vaccination. Experts such as presidential adviser Dr. Anthony Fauci began talking a lot about it, with a best guess goal of 75% to 85% nationally. "If you get that level of herd immunity, you could essentially crush this outbreak in this country," Fauci said during an interview on NPR's Morning Edition.
The appeal of this notion is clear. Achieving herd immunity sounds like a simple goal that spells the end of the coronavirus. It feels concrete — something to grab onto in a time filled with so much uncertainty, a finish line for which to strive.
But the problem with framing the goal that way, say the scientists who actually build the models, is that the herd immunity threshold is far harder to calculate reliably than many in the public realize.
Computer models aren't exactly like real life
In any model of the pandemic, "we make a bunch of assumptions that we know aren't true," says Samuel Scarpino, director of the Emergent Epidemics Lab at Northeastern University. For example, he says, computer models often drastically oversimplify the way people interact with each other, assuming for example, that "the way I decide who I'm going to have lunch with is that I put everybody in a bag and I shake the bag up and I draw somebody out at random and that's who I have lunch with."
In the real world, people only have lunch with a relatively small number of social contacts — not a random sampling of the community — and that changes the herd immunity threshold.
"It's also complicated by the fact that we may not have an even distribution of immunity," Meyers says. The herd immunity threshold is usually presented as a single, overall percentage of a population. But in a given city, "you may hear numbers like 50% of a population are immunized. But is that really 50% in every single neighborhood? Or do we have some pockets of very high levels of immunity and other pockets of low levels of immunity?"
The distinction matters. If the east side of a city is immunized and the west side isn't, then an outbreak could still spread quickly in that unimmunized area and overwhelm hospitals.
Finally, the herd immunity threshold doesn't actually mean you won't have new infections at some point in the future. "Even after you've reached the herd immunity threshold, you can still get little stuttering chains of infection going on within that population," says Erin Mordecai, a professor of biology at Stanford University. "It's just that on average the disease won't grow at that point."
"People talk about herd immunity as if it's sort of the end point, you either have it or you don't, and once you have it you keep it," says Marc Lipsitch at Harvard University. "That's not true either."
Factors such as the spread of new variants, or a time of year that drives more people indoors, or otherwise leads to more mixing, can cause huge swings in how many people need to be immune to reach or maintain herd immunity.
Since December, there have been real-world complications that have clouded the outlook for reaching the herd immunity threshold. Data out of Asia and Brazil suggests reinfection may be more common than thought. Vaccine hesitancy has emerged as an issue, as has the rise of more transmissible variants, which can drastically drive up the percentage of people who would need to be immunized to get to herd immunity. Based on current conditions, and the fact that young children are not yet eligible for vaccination, Lipsitch says he believes as much as 90% to 100% of adults would need to get vaccinated to cross the threshold.
"Based on the best calculations I know how to do, it will be impossible or very difficult to reach [herd immunity] in many parts of the United States," he says.
But that could all change again in the future, depending on new real-world conditions.
And in the end, Mordecai says, it may not matter so much, in terms of corralling the virus enough so that the number of severe cases of COVID-19 significantly drops.
"Our vaccine campaigns rarely reach the level that we actually have herd immunity to the flu," Mordecai points out. "And yet most years we're able to avoid major pandemics of the flu." A combination of immunity through vaccination and prior infection provides a high enough level of protection that the hospitals are never overwhelmed, she says. Even though the coronavirus is a far more serious disease, "that's the kind of thing that could happen with COVID-19."
In fact, none of the scientists interviewed says they believe the herd immunity threshold is the right goal for the public to worry about — they urge emphasizing vaccination instead. Sridhar points to the original political origins of the herd immunity discussion.
"Many high-income countries, because we have people who are very, very clever, have tried to use math to outsmart a problem that is basically common sense," Sridhar says. "More infections are bad, and the way to stop them is to get vaccinated. It's that simple."
Meyers says she believes computer models have been extremely helpful in this pandemic as a warning to policymakers, and to devise local policies for cities and states. But she agrees the elevation of the herd immunity threshold in particular hasn't been useful.
Instead, she says, the computer models all show a clear way forward: "Every vaccination gets us a step closer, every vaccination makes our community, our society a safer, place.
From NPR USA , and I copied as link wouldn't work and removed advertising which was under every 2nd paragraph.
THE CORONAVIRUS CRISIS
The end of this pandemic sometimes gets boiled down to two words: herd immunity.
But now, as an academic debate swirls over when or even if America can get to a high enough percentage of people with immunity to reach that goal, some scientists say it's time for the public to stop worrying about it.
"I think we're focusing too much of our time, our effort, on quibbling over a number," says Lauren Ancel Meyers, a professor at the University of Texas at Austin and head of the university's COVID-19 Modeling Consortium. Instead, Meyers and others say the public should follow one simple piece of advice: Get vaccinated.
How Herd Immunity Works — And What Stands In Its Way
"This pandemic ends when enough people are protected from severe illness, and selfishly you want to be protected from severe illness," says Devi Sridhar, a professor of public health at the University of Edinburgh in Scotland.
Vaccination "helps you and it helps your community."
What does herd immunity mean anyway?
The idea of herd immunity began with cows, not people. In 1916, veterinarian Adolph Eichhorn and colleagues noticed that a herd of cattle could become collectively immune to a disease if enough animals survived the initial infection.
Since then, the herd immunity threshold has become a commonly used term in epidemiology to refer to the mathematical tipping point of an infectious disease outbreak. When a certain percentage of people are immune, either through infection or vaccination, a virus runs out of places to spread. The epidemic — or, in this case, the pandemic — fades, and life goes back.
The threshold for herd immunity can vary widely from disease to disease. And with so many unknowns about the coronavirus, it's been a topic of much discussion. Over the course of the pandemic, estimates for the threshold needed to reach herd immunity have fluctuated from as low as 20% to as high as 90% or more of population.
The term herd immunity remained largely in academic circles until the spring of 2020. That's when, as the coronavirus spread across Europe, politicians such as British Prime Minister Boris Johnson suddenly found themselves talking about it on television.
The group of scientists advising Johnson at the time, according to Sridhar, included many modelers of the pandemic. Modelers build computer simulations, or models, of the future.
It was a time before vaccines, when the virus looked as though it was ripping through Asia and Italy unchecked. Some of the modelers Johnson was listening to "ran projections that showed that this was unstoppable, uncontrollable," Sridhar says. "And this led to this approach of 'herd immunity,' which is just let the virus go, let nature take its course."
It was the "take it on the chin" strategy as described by Johnson. This flavor of herd immunity was an appealing idea for conservative politicians and pundits who wanted to see economies kept open. But the policy was never enacted in Britain, in part because modelers at Imperial College London showed just how bad things could get. Today, it's widely accepted that letting the coronavirus run unfettered through a population would have led to an even more staggering death toll.
"I think if we could go back in time and they were completely honest, both the public health advisers and the leadership would say that's the wrong approach," Sridhar says.
But herd immunity stuck around in the public consciousness. Even into last fall, the Trump administration continued to toy with the idea of reaching herd immunity by allowing the coronavirus to spread mostly unchecked.
Then, when the first vaccines rolled out in December, the term got even more life — this time focusing on the immunity that's gained through vaccination. Experts such as presidential adviser Dr. Anthony Fauci began talking a lot about it, with a best guess goal of 75% to 85% nationally. "If you get that level of herd immunity, you could essentially crush this outbreak in this country," Fauci said during an interview on NPR's Morning Edition.
The appeal of this notion is clear. Achieving herd immunity sounds like a simple goal that spells the end of the coronavirus. It feels concrete — something to grab onto in a time filled with so much uncertainty, a finish line for which to strive.
But the problem with framing the goal that way, say the scientists who actually build the models, is that the herd immunity threshold is far harder to calculate reliably than many in the public realize.
Computer models aren't exactly like real life
In any model of the pandemic, "we make a bunch of assumptions that we know aren't true," says Samuel Scarpino, director of the Emergent Epidemics Lab at Northeastern University. For example, he says, computer models often drastically oversimplify the way people interact with each other, assuming for example, that "the way I decide who I'm going to have lunch with is that I put everybody in a bag and I shake the bag up and I draw somebody out at random and that's who I have lunch with."
In the real world, people only have lunch with a relatively small number of social contacts — not a random sampling of the community — and that changes the herd immunity threshold.
"It's also complicated by the fact that we may not have an even distribution of immunity," Meyers says. The herd immunity threshold is usually presented as a single, overall percentage of a population. But in a given city, "you may hear numbers like 50% of a population are immunized. But is that really 50% in every single neighborhood? Or do we have some pockets of very high levels of immunity and other pockets of low levels of immunity?"
The distinction matters. If the east side of a city is immunized and the west side isn't, then an outbreak could still spread quickly in that unimmunized area and overwhelm hospitals.
Finally, the herd immunity threshold doesn't actually mean you won't have new infections at some point in the future. "Even after you've reached the herd immunity threshold, you can still get little stuttering chains of infection going on within that population," says Erin Mordecai, a professor of biology at Stanford University. "It's just that on average the disease won't grow at that point."
"People talk about herd immunity as if it's sort of the end point, you either have it or you don't, and once you have it you keep it," says Marc Lipsitch at Harvard University. "That's not true either."
Factors such as the spread of new variants, or a time of year that drives more people indoors, or otherwise leads to more mixing, can cause huge swings in how many people need to be immune to reach or maintain herd immunity.
Since December, there have been real-world complications that have clouded the outlook for reaching the herd immunity threshold. Data out of Asia and Brazil suggests reinfection may be more common than thought. Vaccine hesitancy has emerged as an issue, as has the rise of more transmissible variants, which can drastically drive up the percentage of people who would need to be immunized to get to herd immunity. Based on current conditions, and the fact that young children are not yet eligible for vaccination, Lipsitch says he believes as much as 90% to 100% of adults would need to get vaccinated to cross the threshold.
"Based on the best calculations I know how to do, it will be impossible or very difficult to reach [herd immunity] in many parts of the United States," he says.
But that could all change again in the future, depending on new real-world conditions.
And in the end, Mordecai says, it may not matter so much, in terms of corralling the virus enough so that the number of severe cases of COVID-19 significantly drops.
"Our vaccine campaigns rarely reach the level that we actually have herd immunity to the flu," Mordecai points out. "And yet most years we're able to avoid major pandemics of the flu." A combination of immunity through vaccination and prior infection provides a high enough level of protection that the hospitals are never overwhelmed, she says. Even though the coronavirus is a far more serious disease, "that's the kind of thing that could happen with COVID-19."
In fact, none of the scientists interviewed says they believe the herd immunity threshold is the right goal for the public to worry about — they urge emphasizing vaccination instead. Sridhar points to the original political origins of the herd immunity discussion.
"Many high-income countries, because we have people who are very, very clever, have tried to use math to outsmart a problem that is basically common sense," Sridhar says. "More infections are bad, and the way to stop them is to get vaccinated. It's that simple."
Meyers says she believes computer models have been extremely helpful in this pandemic as a warning to policymakers, and to devise local policies for cities and states. But she agrees the elevation of the herd immunity threshold in particular hasn't been useful.
Instead, she says, the computer models all show a clear way forward: "Every vaccination gets us a step closer, every vaccination makes our community, our society a safer, place.
From NPR USA , and I copied as link wouldn't work and removed advertising which was under every 2nd paragraph.
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