Enter the number of deaths caused by a disease and the total number of confirmed cases to calculate the case fatality rate (CFR). Switch tabs to compare two CFRs as a ratio or to back-calculate missing values.
Case Fatality Rate Formula
The case fatality rate (CFR) is calculated using the following formula:
CFR = (D / C) \times 100
Variables:
- CFR is the case fatality rate, expressed as a percentage
- D is the total number of deaths attributed to a specific disease in a defined period
- C is the total number of confirmed (diagnosed) cases of that disease in the same period
The numerator (D) must be a subset of the denominator (C). Every death counted must belong to the pool of confirmed cases. This constraint distinguishes the CFR from the crude mortality rate, where the denominator is the entire population at risk rather than diagnosed individuals alone.
What Is the Case Fatality Rate?
The case fatality rate is a measure of disease severity used in epidemiology. It quantifies the proportion of diagnosed individuals who die from a given disease within a specified timeframe. Unlike a mortality rate, which divides deaths by the total population at risk, the CFR restricts its denominator to people who have already been diagnosed. This makes it a measure of lethality among known cases rather than a measure of population-level death risk.
CFR is most useful for acute infectious diseases where the interval between diagnosis and outcome (recovery or death) is relatively short. For chronic diseases such as diabetes or heart failure, case fatality becomes harder to define because the window between diagnosis and death can span decades, and intervening causes of death complicate attribution.
CFR vs. IFR vs. Mortality Rate
Three mortality metrics are commonly confused. Each uses a different denominator, which changes the interpretation.
| Metric | Numerator | Denominator | Measures |
|---|---|---|---|
| Case Fatality Rate (CFR) | Deaths from disease | Confirmed/diagnosed cases | Lethality among diagnosed patients |
| Infection Fatality Rate (IFR) | Deaths from disease | All infected (including undiagnosed and asymptomatic) | Lethality among all infections |
| Crude Mortality Rate | Deaths from disease | Total population at risk | Population-level death risk |
The IFR is always less than or equal to the CFR because it adds undiagnosed infections to the denominator while keeping the same numerator. During COVID-19, for example, early naive CFR estimates hovered around 2 to 3%, while large-scale seroprevalence studies placed the global IFR closer to 0.5 to 1.0%. The gap between CFR and IFR reflects the proportion of infections that escape clinical detection, a quantity known as the ascertainment rate.
Case Fatality Rates by Disease
The following table lists approximate CFRs for notable infectious diseases. Values can vary significantly by region, access to healthcare, vaccination status, and time period.
| Disease | Approximate CFR | Notes |
|---|---|---|
| Rabies (untreated) | >99% | Nearly 100% fatal once symptomatic; post-exposure prophylaxis is effective if given early |
| Ebola virus disease | 25 to 90% | Varies by outbreak and species; 2014 West Africa outbreak averaged roughly 40% |
| MERS-CoV | ~34% | High CFR partly due to detection bias toward severe hospitalized cases |
| Smallpox (Variola major) | ~30% | Eradicated in 1980; Variola minor had a CFR of about 1% |
| Yellow fever (severe) | 20 to 50% | Overall CFR ~5 to 6% because most infections are mild or subclinical |
| Cholera (untreated) | 25 to 50% | With oral rehydration therapy, CFR drops below 1% |
| SARS-CoV-1 (2003) | ~11% | 8,096 cases globally; rapid containment limited total case count |
| COVID-19 (all strains) | ~0.9 to 2% | Naive CFR varied by variant and healthcare capacity; IFR substantially lower |
| Influenza (seasonal) | ~0.1% | 1918 pandemic CFR was roughly 2 to 3%; varies by strain and age |
| Measles (industrialized) | 0.1 to 0.3% | In low-income settings without vaccination, CFR can reach 3 to 6% |
| Plague (pneumonic, untreated) | ~100% | Bubonic plague 30 to 60% untreated; antibiotics reduce it to under 10% |
Biases That Distort CFR Estimates
A raw CFR figure should never be taken at face value without understanding the biases embedded in its calculation. Four systematic biases are especially common.
Ascertainment bias inflates CFR when only the most severe cases are tested and diagnosed. During early COVID-19, testing was reserved for hospitalized patients in many countries, so mild and asymptomatic infections were excluded from the denominator. This made the virus appear deadlier than subsequent seroprevalence data later confirmed.
Time-lag bias suppresses CFR early in an epidemic. The naive formula (cumulative deaths divided by cumulative cases at a single point) counts unresolved cases in the denominator. Because death takes time, many of those cases will eventually die but are counted as alive at the moment of calculation. Adjusting for the interval between symptom onset and death corrects for this.
Reporting and attribution bias affects both numerator and denominator. Under-reporting of deaths (common in settings with limited autopsy or death certificate infrastructure) lowers the numerator. Meanwhile, deaths caused by comorbidities may be misattributed to the disease, raising the numerator. These opposing pressures can partially cancel out, but not reliably.
Population composition effects arise when the age, comorbidity profile, or healthcare access of the diagnosed population differs from the general infected population. A CFR calculated from a young, healthy cohort will understate the lethality experienced by elderly or immunocompromised groups, and vice versa. Age-stratified CFRs are more informative than aggregate figures for public health decision-making.
Case Fatality Ratio vs. Case Fatality Rate
The terms “case fatality rate” and “case fatality ratio” are sometimes used interchangeably, but they can describe different quantities. The case fatality rate is the simple proportion: deaths divided by cases. The case fatality ratio, in its more precise usage, compares two case fatality rates. For example, if Disease A has a CFR of 15% and Disease B has a CFR of 3%, the case fatality ratio of A to B is 15/3 = 5.0, meaning Disease A is five times as lethal per diagnosed case. This ratio is useful for comparing the severity of two diseases or evaluating how much an intervention reduced lethality before versus after deployment. The calculator above supports both uses: Tab 1 calculates the CFR as a percentage, and Tab 2 computes the ratio between two CFRs.
Practical Applications of CFR
Public health authorities use the CFR to triage resource allocation during outbreaks. A disease with a high CFR but low transmissibility (such as Ebola) demands intensive case isolation and contact tracing, while a disease with a lower CFR but extremely high transmissibility (such as influenza) may cause more total deaths and require mass vaccination campaigns instead. The CFR also serves as a benchmark to evaluate clinical interventions. If a new antiviral reduces the CFR of a disease from 10% to 4%, that 60% relative reduction provides direct evidence of treatment efficacy at the population level. Regulatory agencies and hospital systems track these shifts to make formulary and protocol decisions.