Vaccine Efficacy vs Effectiveness: What the Percentages Actually Measure

Efficacy and effectiveness sound interchangeable, but they describe a vaccine's performance under two very different conditions. Efficacy is the risk reduction measured inside a randomized controlled trial, where a vaccinated group is compared with a placebo group under tightly controlled, close to best-case conditions. Effectiveness is how well that same vaccine performs once it reaches the far messier real world, estimated from observational studies of ordinary people. Both figures are almost always reported as a relative risk reduction, and that shared framing is exactly where a confident headline number can mislead.

Efficacy: the number a trial produces

The World Health Organization defines vaccine efficacy as the reduction in disease measured in a controlled clinical trial, based on how many vaccinated people develop the outcome of interest compared with how many who received placebo do. The U.S. Centers for Disease Control and Prevention frames it the same way for influenza: efficacy is the percent reduction in how often illness occurs among vaccinated people compared with people given a placebo, established in randomized, double-blind trials where neither participants nor researchers know who got the vaccine.

The resulting percentage has a precise meaning that is easy to misread. When WHO says a vaccine has 80% efficacy, it means the vaccinated group had an 80% lower risk of disease than the unvaccinated group over the trial period. It does not mean 80% of vaccinated people are protected and 20% are not, and it does not describe your personal odds. Efficacy is a comparison between two groups under ideal study conditions, nothing more and nothing less.

Effectiveness: the number the real world produces

Efficacy is measured before licensure; effectiveness is measured after. Once a vaccine is in wide use, it meets conditions no trial can reproduce: circulating strains that drift, imperfect cold storage, missed doses, and people with the age, pregnancy, or chronic illness that trials often exclude. WHO notes plainly that effectiveness can differ from efficacy because we cannot predict exactly how a vaccine will perform across a much larger and more variable population. Effectiveness is usually, though not always, lower than the efficacy that preceded it.

Influenza is the clearest worked example, because effectiveness is re-estimated every season. In interim estimates for the 2024 to 2025 season, published in the CDC's Morbidity and Mortality Weekly Report, four surveillance networks found vaccine effectiveness against medically attended outpatient influenza in the rough range of 32% to 60% depending on age group and network, and effectiveness against influenza-associated hospitalization between 41% and 78%. Those numbers move year to year with how well the vaccine matches the season's dominant strains, which is why a single lifetime figure for the flu shot does not exist.

Why the test-negative design

Most modern effectiveness estimates come from a test-negative design, the method behind the CDC flu figures. Researchers take everyone who shows up for care with the same respiratory symptoms and test them all. Those who test positive for the virus are the cases; those who test negative are the controls. Because both groups were sick enough to seek care and get tested, the design cancels out much of the bias from people who are simply more likely to visit a doctor, letting investigators compare vaccination status on fairer terms.

The trap in a relative-risk headline

Here is the part that trips up even careful readers. Efficacy and effectiveness are almost always quoted as a relative risk reduction, which compares the two groups' risks against each other and says nothing about how common the disease was to begin with. A vaccine can post an impressive relative number while the absolute change in any one person's risk stays small, if the underlying risk during the study was low.

Olliaro and colleagues made this explicit in The Lancet Microbe. Using the pivotal COVID-19 trial data, they contrasted relative risk reductions of roughly 95% and 94% for the two mRNA COVID-19 vaccines with the corresponding absolute risk reductions, which were about 0.84% and 1.2%. Both pairs of numbers came from the same trials. The relative figure looks at only the people who could have benefited; the absolute figure spreads the benefit across the whole enrolled population, including the large majority who were never going to catch the disease during the study window. Neither is wrong, but reporting the relative number alone, without the base rate, exaggerates how much a single vaccination shifts an individual's odds.

That base rate is not a fixed property of the vaccine. When background disease risk is high, a given relative risk reduction converts into a large absolute benefit and a small number of people needed to vaccinate to prevent one case. When background risk is low, the same relative percentage buys far less absolute protection. This is why the authors warned that comparing vaccines, or setting policy, on relative risk reduction alone is inappropriate.

Reading a percentage responsibly

A vaccine percentage is only interpretable once you know what sits behind it. Is it efficacy from a trial or effectiveness from the field? What outcome does it count, infection, symptomatic disease, hospitalization, or death, since a vaccine can be modest against catching a virus yet strong against severe illness? In which population, and over what stretch of time? And crucially, what was the absolute risk in the unvaccinated group, so the relative headline can be anchored to something real? A number without those answers is a slogan, not evidence. This article is educational and is not a substitute for individualized medical advice.