Turn study efficacy into real-world impact estimates now. Adjust coverage, risk, and variant reduction factors. See prevented cases, hospital loads, and lives saved quickly.
| Population | Attack rate | Coverage | Efficacy | Adjusted efficacy | Cases averted | Hospitalizations averted | Deaths averted |
|---|---|---|---|---|---|---|---|
| 100,000 | 10% | 70% | 85% | 57.8% | 4,043 | 40.4 | 4.04 |
This calculator translates trial or surveillance efficacy into population impact. It combines baseline attack rate, vaccine coverage, and adjusted efficacy to estimate prevented infections, severe outcomes, and direct costs. Outputs are scenario estimates, so document the sources, dates, and denominators used for each input.
Absolute reductions scale with exposure. If attack rate rises from 5% to 15% in a 100,000 population, expected infections triple. With unchanged coverage and efficacy, averted cases also roughly triple, which can shift staffing and bed needs. When risk is low, the same efficacy produces smaller absolute gains, even though relative protection is similar.
Coverage partitions the population into vaccinated and unvaccinated groups. At 70% coverage, most infections may still occur in the unvaccinated group when baseline risk is high. Raising coverage from 60% to 80% can reduce expected cases materially even if efficacy is unchanged. Use coverage aligned to the same period as the attack rate, especially during rollouts.
Immune escape and waning reduce observed protection. The model applies multiplicative reductions, so an 85% study efficacy with 20% immune escape and 15% waning becomes about 57.8% effective. Small changes in these modifiers can alter NNV and workload projections. If booster doses are planned, test alternative waning values to compare timing options.
Clinical rates translate infections into severe outcomes, hospitalizations, and deaths. For example, a 1% hospitalization rate means 100 admissions per 10,000 infections. When cases fall, downstream events fall proportionally, supporting scenario planning for oxygen, ICU, and follow-up capacity. Use local age mix when available because outcome rates can vary widely by cohort.
Direct costs are estimated as cases plus hospitalizations times your unit costs. If average cost per case is 15 and per hospitalization is 800, preventing 4,000 cases and 40 admissions yields roughly 92,000 in avoided direct costs. Use consistent currency and document assumptions. Costs here exclude program delivery and productivity impacts, so treat results as a conservative accounting view. Export the CSV to compare multiple scenarios side by side in one worksheet.
It is the study efficacy reduced by immune escape and waning modifiers. The calculator multiplies these reductions to approximate real-world protection during your selected period.
If baseline attack rate is high or coverage is modest, many people remain exposed. Absolute case counts depend on risk and coverage, not efficacy alone.
NNV is the number of vaccinations needed to prevent one infection among vaccinated people. Lower values indicate higher absolute benefit under the assumed baseline risk.
No. Outcome rates are applied to estimated infections to convert them into events. If you have separate efficacy against severe disease, model it by lowering the severe, hospitalization, or death rates for the vaccinated group externally.
Use published effectiveness updates, local sequencing information, and time-since-dose distributions. Run best-case and worst-case scenarios to understand sensitivity.
It is a static scenario tool. It does not simulate transmission, indirect protection, clustering, behavior changes, or competing risks. Treat outputs as planning ranges, not predictions.
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.