Case Fatality Rate (CFR) & Infection Fatality Rate (IFR) Calculator
Calculate the naive case fatality rate, the delay-adjusted CFR using cases from an earlier date, the infection fatality rate from seroprevalence or an ascertainment ratio, the 95% confidence interval, and how testing coverage and reporting lag bias each measure during an outbreak.
How it works
CFR = deaths ÷ confirmed cases; lag-adjusted CFR = deaths ÷ cases as of (onset-to-death interval) earlier; resolved CFR = deaths ÷ (deaths + recovered); IFR = deaths ÷ estimated infections (population × seroprevalence, or cases × ascertainment ratio)
The case fatality rate — deaths among confirmed cases — is the most quoted and most misread outbreak statistic. Early in a wave it is biased low because people who will die have not yet died, and it is biased high because testing finds the severe cases first; dividing today's deaths by the cases counted one onset-to-death interval earlier corrects the first problem, and comparing with the resolved-case ratio brackets the truth. The infection fatality rate divides by all infections, including the mild and asymptomatic ones revealed by antibody surveys, and is therefore much lower and the better measure of how dangerous a pathogen is to someone who catches it — though it varies enormously with age, which is why crude comparisons between countries mislead.
Worked example
320 deaths among 24,000 confirmed cases is a naive CFR of 1.33% (95% CI 1.19–1.48%); against the 15,000 cases known three weeks earlier it is 2.13%, and among resolved cases 2.60%. An 8% seroprevalence in a population of 2 million implies 160,000 infections, so the IFR is about 0.20% — roughly one-seventh of the CFR — and the population has lost 16 per 100,000.
Frequently asked questions
Which is right, the CFR or the IFR?
They answer different questions: CFR is the risk of death for a diagnosed patient (useful for clinicians and for comparing care), IFR the risk for anyone infected (useful for policy and personal risk). Both are legitimate if labelled.
Why did the CFR fall over time in most outbreaks?
Testing widened to milder cases, treatment improved, and the most vulnerable were infected — or protected — early. Falling CFR therefore does not by itself show a milder pathogen.
Related calculators
Standard epidemiological formulas (CDC Principles of Epidemiology, Rothman) with simple large-sample confidence intervals. Results depend on case definitions, ascertainment and study design; they inform, and do not replace, formal analysis by an epidemiologist or public-health authority.