Two statistical methods are used to measure vaccine effectiveness: absolute risk reduction and relative risk reduction. What is the difference?
WASHINGTON – We’ve all heard by now that the Pfizer COVID-19 vaccine has an efficacy rate of 95%, Moderna 94% and Johnson & Johnson about 66%; what you may not know is the technical term for this rate, called “relative risk reduction”.
Some people online suggest that we should instead turn to another statistical method of effectiveness, called “absolute risk reduction”.
Some articles emphasize this peer reviewed article, arguing that if you look at absolute risk reduction instead of relative risk reduction, the risk of getting or dying from COVID-19 can only drop by a very small percentage if you get the vaccine.
So what does this other metric tell us?
What is absolute risk reduction and does it show that the risk is so much less than the relative risk reduction?
We asked two experts in math and health, Dr Stephen Kissler, Ph.D. in Applied Mathematics and Postdoctoral Fellow at the TH Chan School of Public Health at Harvard University, and Dr Ali Mokdad, PhD in quantitative epidemiology and professor of global health at the Institute for Health Metrics and Evaluation at the University of Washington.
In the context of COVID, says Kissler, absolute risk reduction compares how much your risk decreases by getting vaccinated.
For example, let’s say there’s a vaccine study, where 100 people get vaccinated and 100 people get a placebo. In the vaccine group, only one person got sick and in the placebo group, ten people got sick.
Let’s break it down for person A, who got the vaccine, and person B, who didn’t.
For person A, the absolute risk is 1 in 100, because only one person got sick in this whole group.
For person B, this absolute risk is 10 in 100, because 10 people have fallen ill.
If you compare those two numbers, it’s a nine percent difference. This is called absolute risk reduction.
Now let’s talk about relative risk.
“The relative risk is asking ‘what are my chances of getting infected compared to someone vaccinated? ”, Says Kissler.
To do this, we compare our vaccinated person, person A, with our unvaccinated person, person B.
For person A, the relative risk is 1 in 10, because only one vaccinated person got sick compared to 10 unvaccinated people who got sick.
For person B, the relative risk is 10 out of 10.
“For unvaccinated people, it’s 10/10 (10 infections in the unvaccinated group versus 10 infections in the (same) unvaccinated group),” Kissler explained via email. “For this reason, the relative risk in the ‘benchmark’ group will always be 100%!”
If you compare those two numbers, it’s a 90% difference.
“It’s a lot higher, isn’t it … and that was the problem the newspaper raised was that the relative risk calculation in this case is a lot higher,” Kissler said. . “So what’s correct? Should we quote 90%? Or should we quote 9%? Because these give you a very different intuitive perception of the difference in risk you get for being vaccinated. . Well, I think both are helpful. “
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Dr Mokdad says it’s not at all unreasonable for the public to hear about relative risk reduction rather than absolute reduction. The decision is to send a public health message, rather than tossing numbers and percentages to the public. He says the purpose of public health messages is for information to connect with the public to help them better understand complex topics.
“If I come to you and tell you the absolute difference in lung cancer if you smoke, [it] does not connect. But, if I come to tell you, “if you smoke, that you are nine times more likely to get lung cancer,” then that’s a public health message, “says Mokdad.” That’s what we want, is that we want to get in touch with the public. , and we scientists need to speak a language that connects to the public. If I can’t explain it to someone who is not an epidemiologist or a scientist, then I have failed miserably.
Our Verify researchers spoke with the author of the circulating scientific article. He believes the public has a right to know the double digits.
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