Will We All Get it Eventually? The Long-Term Epidemiology of COVID-19

How much curve-flattening is enough?

In the early days of the coronavirus pandemic the phrase “flatten the curve” got into the national zeitgeist.

By shutting down large aspects of society, social distancing, and other public health measures we would slow the spread of the coronavirus to avoid overwhelming our hospital system. Grim stories from Italy of triaging ventilators and patients dying in corridors made the problem that much more real.

And so far, it seems we have flattened the curve. We have not had to deny life-saving treatments because ventilators or ICU beds were not available. This was due in no small part to herculean efforts on the part of healthcare workers to expand capacity, but also to the efforts of everyday Americans who took the precautions seriously.

But one question has been sitting in the back of my mind since the talk of curve-flattening started. Does everyone get the coronavirus eventually?

It’s an important question. This is a novel virus for which none of us are likely to have any existing immunity. We are ripe for infection and the rate of spread (without social distancing) is rapid. The presence of asymptomatic spread makes the situation even worse.

Of course, the more people get it, the more people become immune and the harder it is for the virus to continue to spread. The equation to calculate the percent of the population who needs to be immune to confer broad herd immunity is pretty straightforward. It’s 1–1/R0. If each person with the disease infects three others, then once two out of three people are immune, the disease doesn’t have enough targets to keep spreading. I made a graph showing the relationship between the R0, and the population percentage necessary to confer herd immunity here.

For COVID-19, we probably have to have 65–70% of the population immune before the thing dies out. I’ll just point out we are nowhere close to that. Even in New York city, American epicenter of the disease, seroprevalence studies only suggest about 25% of the population is immune.

If our battle against coronavirus is a baseball game, we’re somewhere in the second inning.

But if 65% of us are going to get it eventually, then you can make a particularly utilitarian and somewhat strange argument about our public health measures. Maybe, we should flatten the curve just enough to avoid overwhelming our hospitals but no more.

Get through this as quickly as possible without leading to excess deaths.

It even gives a quantifiable metric to score the government’s response. As long as a single person doesn’t get denied care because of hospital overcrowding, it’s a victory.

There’s a lot appealing about this argument.

But I want to deconstruct it a bit from a practical, epidemiological, and ethical perspective.

First the practical. Delaying the spread of the disease doesn’t only help hospitals cope with surges. It also buys us time to do medical research, identify treatments, and find vaccines. And I want to point out that this isn’t all pie-in-the-sky maybe we’ll have a large randomized clinical trial of a new drug. This is highly practical stuff as we figure out how to treat COVID-19.

Think of how much we’ve learned in these few months — about the utility of proning — about delay of intubation — about the risk of thrombosis that is changing how we care for these patients.

You’re way better off getting sick from coronavirus now than you were in March.

Another practical issue is that there is really no way to just skirt under overwhelming our hospitals. We can’t just dial up and dial down the disease spread — it is different in different places and substantially lags policy choices. There’s also a stochastic element here — outbreaks will happen and they will not be predictable.

Second, the epidemiological. It turns out that outbreaks don’t just stop when you reach herd immunity. They have inertia. Here’s Dr. Albert Ko, Chair of Yale’s Department of Epidemiology of Microbial Diseases:

“You can overshoot predicted herd immunity. That’s just because of the dynamics when you have such high transmission or attack rates”

Albert Ko, MD

Chair, Department of Epidemiology of Microbial Diseases

Yale University

Finally, the ethical. Even if we assume the total death rate is the same (which I hope at this point I’ve convinced you is not the case), compressing those deaths into a shorter period of time still robs people of life. I mean, look, 100% of people die eventually. As physicians, the war against death is one we will always lose. But we fight the battle to push that day as far into the future as possible. I think we need to keep that in mind as we continue to struggle with COVID-19, every day is a victory.

A version of this commentary first appeared on medscape.com.

Writing about medicine, science, statistics, and the abuses thereof. Commentator at Medscape. Associate Professor of Medicine at Yale University.

Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store