Thursday , May 28 2020
Home / Bryan Caplan /Mitigation Multiplies

Mitigation Multiplies

Summary:
I hesitate to join the ranks of the abundant newly-minted amateur epidemiologists out there.  But here goes. I’ve heard many people claim that a population can’t reach herd immunity to any disease until 60-70% of the population has been infected.   This is a grave overgeneralization; as this primer explains, the critical value for herd immunity directly depends on how contagious the disease is: The critical value, or threshold, in a given population, is the point where the disease reaches an endemic steady state, which means that the infection level is neither growing nor declining exponentially. This threshold can be calculated by taking R0, the basic reproduction number, or the average number of new infections caused by each case in an entirely susceptible

Topics:
Bryan Caplan considers the following as important:

This could be interesting, too:

Scott Sumner writes Libertarianism, not libertarians

Bryan Caplan writes The Roots of Caution

Bryan Caplan writes Social Anxiety, #MeToo, and Disaster

Alberto Mingardi writes Mariana Mazzucato on Covid-19 and “small” government

I hesitate to join the ranks of the abundant newly-minted amateur epidemiologists out there.  But here goes.

I’ve heard many people claim that a population can’t reach herd immunity to any disease until 60-70% of the population has been infected.   This is a grave overgeneralization; as this primer explains, the critical value for herd immunity directly depends on how contagious the disease is:

The critical value, or threshold, in a given population, is the point where the disease reaches an endemic steady state, which means that the infection level is neither growing nor declining exponentially. This threshold can be calculated by taking R0, the basic reproduction number, or the average number of new infections caused by each case in an entirely susceptible population that is homogeneous, or well-mixed, meaning each individual can come into contact with every other susceptible individual in the population,[9][29][42] multiplying it by S, the proportion of the population who are susceptible to infection, and setting this product to be equal to 1:

Thus, since measles is ultra-contagious, you don’t reach herd immunity until over 90% of the population is immune.  The critical value for flu, in contrast, is barely one-third of that.  Estimates of the critical value for COVID-19 range from 29-74%.  Check out this table.

Mitigation Multiplies

The standard way of boosting immunity, of course, is vaccination.  As vaccination goes up, S goes down – and society moves toward herd immunity. Yet in principle, anything that reduces susceptibility to contagion has the same effect.  If people wash their hands more, that effectively reduces S.  If people socialize less, than reduces S.  If people stop shaking hands, that reduces S. If people live in a low-density area, that reduces S. 

Critically, all of these defensive factors multiply.  If washing your hands more, socializing less, ending handshakes, and living in West Virginia each reduces S by 2%, then doing all four reduces S to .98^4=92.2% of its original value.  It’s the same as the logic of contraception.  Suppose you use birth control pills, condoms, withdrawal, and 50% abstinence.  Your probability of pregnancy equals your base probability, multiplied by the failure rates of all four methods.

Some of my friends overrate R0, imagining that getting R0<1 prevents full infection of the population.  But with a finite population (i.e., any actual population), you can infect everyone with an R0 far below 1.  Suppose your society has 15 people, and 10 are already sick.  Then even with R0=.34, all 15 people eventually catch the disease.  After all, the infinite sum of 10 + .34*10 + .34^2*10+…=10/(1-.34)>15.

That’s the bad news.  The good news is that infection and vaccination are only the two best-known ways to effectively shrink S.  An endless list of behaviors are not only on the shelf, but are already in play.   Paid voluntary human experimentation would help us find the low-hanging behavioral fruit in a matter of weeks, but at least almost everyone today bases their precautions on germ theory rather than witchcraft.

Additional good news: Fatality rates vary dramatically by age and even more dramatically by health status.  So once you multiply the effect of all forms of mitigation to figure out when we’ll hit herd immunity, you shouldn’t mechanically multiply that by the average infection mortality rate to estimate total deaths.  As Dan Klein puts it:

Let’s look at Wikipedia’s definition of herd immunity. It is based on a threshold condition where the still-susceptible proportion of the population multiplied by R0 equals 1.

What is R0? It is “the average number of new infections caused by each case in an entirely susceptible population that is homogeneous, or well-mixed” (Wikipedia, italics added).

Well-mixed is what we strive to prevent! We strive to separate the vulnerable from the rest of the population.

I’m not so optimistic about the “we” part.  But you can definitely do so.  If you’re vulnerable, take high precautions.  If you’re not vulnerable, give the vulnerable their space.

P.S. Yes, you could just as easily say that behavior affects R0 rather than S, but I thought my way was a bit clearer.

Bryan Caplan
Bryan Caplan is Professor of Economics at George Mason University and Senior Scholar at the Mercatus Center. He has published in the New York Times, the Washington Post, the Wall Street Journal, the American Economic Review, the Economic Journal, the Journal of Law and Economics, and Intelligence, and has appeared on 20/20, FoxNews, and C-SPAN. Bryan Caplan blogs on EconLog.

Leave a Reply

Your email address will not be published. Required fields are marked *