Model outbreaks with adjustable underreporting and intervals today. Compare incidence and attack rates across groups. Download clean tables for audits, sharing, and decisions fast.
| Reported cases | Population | Days | Multiplier | Attack rate | Incidence per 100,000 | Incidence rate per 100,000 person-days |
|---|---|---|---|---|---|---|
| 120 | 25,000 | 14 | 1.2 | 0.576% | 576.0 | 41.1429 |
| 35 | 5,500 | 7 | 1 | 0.636% | 636.4 | 90.9091 |
| 480 | 80,000 | 21 | 1.5 | 0.900% | 900.0 | 42.8571 |
Attack rate summarizes cumulative risk over the chosen window: adjusted infections divided by the population at risk. It is best for short, well‑defined outbreaks, cohort follow‑up, or event‑based surveillance. Cumulative incidence per 1,000, 10,000, or 100,000 scales the same proportion for easier comparisons across sites, schools, wards, and districts.
Incidence rate uses person‑time to reflect exposure duration. When direct person‑time is unavailable, the calculator approximates it as population multiplied by days, yielding person‑days. Rate outputs help compare groups with different observation lengths, staffing rotations, or changing denominators. Interpret rate as expected infections per scaled person‑time, not as the probability an individual becomes infected.
Reported cases often miss asymptomatic infections, testing delays, and access barriers. The underreporting multiplier converts observed counts into an adjusted estimate. Use a multiplier grounded in serology, capture‑recapture, or retrospective audit data. Sensitivity analysis is recommended: run multiple multipliers to bracket plausible ranges and communicate uncertainty alongside point estimates.
If start and end case counts are provided, the calculator estimates exponential growth rate r using the natural logarithm ratio over time. Positive r implies growth; doubling time follows as ln(2)/r. A simple reproduction number approximation is derived as exp(r×generation interval). These metrics are useful for early signals, but they do not replace full transmission models or nowcasting.
For operational reporting, pair cumulative incidence with incidence rate: the first conveys overall burden, the second standardizes for exposure time. Track both weekly to detect shifts from testing changes, population movement, or control measures. Exported tables support audit trails, reproducible dashboards, and consistent documentation of assumptions, scales, and time windows.
When comparing locations, keep definitions consistent: same case definition, reporting lag, and inclusion rules. If the population at risk changes, prefer a person‑time override derived from occupancy, census updates, or enrollment records. Rates can be stratified by age band, unit, or exposure category by running the estimator separately and presenting results side by side. Where possible, add uncertainty intervals using external statistical tools and cite data sources. Document assumptions for multiplier, interval length, and data completeness clearly.
1) What is the difference between incidence and attack rate?
Attack rate describes cumulative risk during the window. Incidence rate incorporates person‑time and standardizes for different follow‑up durations, making comparisons fairer when exposure time differs across groups.
2) When should I use the person-time override?
Use it when the population at risk is changing or when you directly measured exposure time, such as bed‑days, resident‑days, worker‑shifts, or participant‑hours. It improves rate accuracy.
3) How do I pick an underreporting multiplier?
Choose a value supported by local evidence, such as serology, audit reconciliation, or known testing sensitivity. If uncertain, run several plausible multipliers and report a range instead of one number.
4) Why are growth and R marked as approximate?
They rely on a simplified exponential assumption using only start and end counts. Real outbreaks include delays, changing behavior, and interventions. Use the estimates for quick screening, not definitive inference.
5) Can I compare two outbreaks with different durations?
Yes. Compare incidence rates using person‑time and keep the scale consistent. Also review daily adjusted infections to understand intensity. Ensure case definitions and reporting practices match across settings.
6) Does a high incidence rate imply high individual risk?
Not necessarily. A rate reflects infections per unit of exposure time at the group level. Individual risk depends on contact patterns, susceptibility, protective behaviors, and clustering within the population.
Important Note: All the Calculators listed in this site are for educational purpose only and we do not guarentee the accuracy of results. Please do consult with other sources as well.