Skip to main content
Calcimator

Vaccine Efficacy Calculator

VE from vaccinated and unvaccinated incidence rates.

About this calculator

This calculator computes vaccine efficacy (VE) and related epidemiological statistics from case counts in a vaccinated and an unvaccinated group, the standard approach used to report results from randomized vaccine trials and observational studies. It first computes each group's attack rate -- cases divided by total group size -- then vaccine efficacy as VE = 1 - (attack rate vaccinated / attack rate unvaccinated), expressed as a percentage. A VE of 95% means the vaccinated group's disease rate was 5% of the unvaccinated group's rate, not that 95% of vaccinated people are immune.

The calculator also reports relative risk (the same attack-rate ratio VE is built from, without the "1 minus" framing), absolute risk reduction (the raw percentage-point difference between the two attack rates, which behaves very differently from VE when baseline disease risk is low), and number needed to vaccinate (NNV, the inverse of absolute risk reduction) -- how many people must be vaccinated to prevent one additional case. An approximate 95% confidence interval is computed using the Katz log method -- introduced by Katz, Baptista, Azen, and Pike in 1978 as a log-relative-risk approach with a delta-method variance estimate for cohort-study risk ratios, and since adopted as the standard method for vaccine-efficacy confidence intervals -- giving a sense of how much statistical uncertainty surrounds the point estimate, which shrinks as group sizes and case counts grow. This calculator does NOT distinguish between efficacy (measured in a controlled trial) and effectiveness (measured in real-world use, typically somewhat lower), does not adjust for confounding factors like age or comorbidity differences between the two groups, and treats the input case counts as if drawn from equal-length follow-up periods.

Inputs

Results

Vaccine efficacy (%)

75%

Relative risk0.25
Absolute risk reduction (%)0.6%
Number needed to vaccinate167
95% CI lower (%)59.22%
95% CI upper (%)84.67%

Figures current as of 1978. Source: Katz D, Baptista J, Azen SP, Pike MC. Obtaining confidence intervals for the risk ratio in cohort studies. Biometrics. 1978;34(3):469-474.

How to Use This Calculator
  1. Enter cases and total group size for the vaccinated group.
  2. Enter cases and total group size for the unvaccinated (comparison) group.
  3. Review vaccine efficacy (%), the primary result, along with its approximate 95% confidence interval.
  4. Use relative risk, absolute risk reduction, and number needed to vaccinate for a fuller picture of the vaccine's real-world impact.

How the result changes with Total vaccinated

Total vaccinatedVaccine efficacy (%)
5,00050%
7,50066.67%
15,00083.33%
25,00090%

What each input means

Cases in vaccinated group
Number of disease cases among vaccinated individuals.
Total vaccinated
Total number of vaccinated individuals in the study.
Cases in unvaccinated group
Number of disease cases among unvaccinated individuals.
Total unvaccinated
Total number of unvaccinated individuals in the study.

What each result means

Vaccine efficacy (%)
Percentage reduction in disease risk among vaccinated vs unvaccinated.
Relative risk
Risk ratio of vaccinated vs unvaccinated (lower = better protection).
Absolute risk reduction (%)
Absolute difference in attack rates.
Number needed to vaccinate
People to vaccinate to prevent one case.
95% CI lower (%)
Lower bound of 95% confidence interval for VE.
95% CI upper (%)
Upper bound of 95% confidence interval for VE.

How this is calculated

Worked example, using the default values

  1. Identify Input Parameters
    4 parameters
    Cases in vaccinated group = 20, Total vaccinated = 10000, Cases in unvaccinated group = 80, Total unvaccinated = 10000 = 4 input(s) provided
  2. Calculate Vaccine efficacy
    Vaccine efficacy = attackRateUnvacc > 0
    75 = 75%
  3. Calculate Relative risk
    Relative risk
    0.25 = 0.25
  4. Calculate Absolute risk reduction
    Absolute risk reduction
    0.6 = 0.6%

Figures and sources

Engine last updated . Checked against 2 independently-derived tests — how we verify calculators. Built by Paul Gunder, a software engineer, not a licensed financial, medical, or legal professional.

Frequently Asked Questions

Why does increasing cases in the vaccinated group lower vaccine efficacy while increasing cases in the unvaccinated group raises it?

Vaccine efficacy is built from the ratio of the two groups' attack rates, so more cases among the vaccinated (holding group size fixed) pushes that ratio toward 1 -- meaning vaccination looks less protective -- and lowers VE. More cases among the unvaccinated has the opposite effect: it makes the unvaccinated group's baseline risk look worse by comparison, which mathematically raises the calculated efficacy of the vaccine even though nothing about the vaccinated group changed.

What's the difference between vaccine efficacy and absolute risk reduction?

Vaccine efficacy is a relative measure -- the percentage reduction in risk compared to the unvaccinated group's own baseline -- while absolute risk reduction is the raw percentage-point gap between the two attack rates. A vaccine can post a high relative efficacy (say 90%) while still representing a small absolute risk reduction if the disease is rare to begin with, which is exactly why number needed to vaccinate is reported alongside both: it translates the absolute reduction into a concrete "how many people" figure.

Why does a larger vaccinated group size increase the calculated vaccine efficacy?

A larger total vaccinated denominator, holding the case count fixed, lowers the vaccinated group's attack rate (fewer cases per person), which shrinks the ratio against the unvaccinated group's attack rate and therefore raises the calculated VE. This is a purely arithmetic relationship between group size and attack rate, not evidence that adding more vaccinated people to a study makes the vaccine itself more effective.

How wide is the 95% confidence interval typically compared to the point estimate?

It depends heavily on how many cases occurred, not just group size -- a trial with very few total cases, even across large groups, tends to produce a wide confidence interval because the case counts driving the variance estimate are small, while a trial with more cases in both arms narrows the interval considerably around the point estimate for vaccine efficacy.

The questions that sit next to this one — chosen by subject, including calculators filed under a different category.

More in Medical & Clinical.