Enter the population at risk and the new cases, the members of the primary cases’ households, and the deaths among cases. The calculator returns the attack rate, the secondary attack rate and the case fatality rate, each with a 95% confidence interval.
The attack rate is the share of the population at risk that became ill during an outbreak. Despite the name it is a proportion, not a rate over time, because the outbreak period is short and fixed. The secondary attack rate looks only inside closed groups such as households, hostels or barracks: of the people exposed to a primary case, how many became ill one incubation period later. Comparing the two shows whether illness is spreading person to person or coming from a common source. The case fatality rate is the share of cases that died, a measure of how severe the illness is among those who have it.
| Measure | Formula |
|---|---|
| Attack rate (AR) | New cases ÷ population at risk × 100 |
| Secondary attack rate (SAR) | Secondary cases ÷ (household members − primary cases) × 100 |
| Case fatality rate (CFR) | Deaths among cases ÷ cases × 100 |
| 95% confidence interval | Wilson score interval: (p + z²/2n ± z·√(p(1−p)/n + z²/4n²)) ÷ (1 + z²/n), with z = 1.96 |
The definitions follow CDC, Principles of Epidemiology, Lesson 3: Morbidity frequency measures for attack rate and secondary attack rate, and CDC, Lesson 3: Mortality frequency measures for case fatality rate. CDC notes that the denominator for a secondary attack rate is often the total population of the primary cases’ households minus the primary cases, which is what this calculator uses. The Wilson interval is used instead of the simple ± 1.96 × standard error because it stays inside 0–100% and behaves well when counts are small or zero, which is common in early outbreak data.
These figures are made up to show the arithmetic. A village of 2,000 people reports 80 cases of acute diarrhoeal disease in one week, so the attack rate is 80 ÷ 2,000 × 100 = 4%. The 40 households with a first case hold 160 people, including those 40 primary cases, so 120 contacts were exposed at home. One incubation period later, 18 of them fall ill: a secondary attack rate of 18 ÷ 120 × 100 = 15%. One of the 80 cases dies, a case fatality rate of 1.25%. A household rate well above the village rate points the team towards person-to-person spread and household hygiene, alongside the search for a common source. Because only one death was seen, the CFR interval is wide (roughly 0.2% to 6.8%), a reminder not to over-read small numbers.
This tool is for surveillance and outbreak investigation teams and for students learning field epidemiology. It is not medical advice, and it does not replace the case definitions, thresholds or response protocols of your surveillance programme; confirm them with the official source and your epidemiologists.
Working out an attack rate by hand is easy once someone has noticed the cluster; the hard part is noticing it early. A disease surveillance dashboard such as HealthWatch compares cases in each block with that block’s seasonal baseline every day, raises clusters with their evidence and assigns each one to a district owner, so the investigation that needs these numbers starts sooner. Read how disease cluster detection works, and the monsoon disease surveillance playbook for district teams.
Attack rate = number of new cases during the outbreak ÷ population at risk at the start × 100. It is a proportion of people who became ill, usually expressed as a percentage.
Divide the number of cases among contacts of primary cases by the number of contacts, then multiply by 100. For households, the contacts are usually all household members minus the primary cases.
Attack rate is the proportion of a population at risk that becomes ill over a short, fixed outbreak period. Incidence rate puts person-time in the denominator, so it is used for longer follow-up where people are observed for different lengths of time.
No. Case fatality rate divides deaths by the number of cases, so it measures severity among the ill. Mortality rate divides deaths by the whole population, so it measures the burden on everyone.
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