Downloads
Calculator
Example Data Table
| Date | Total tests | Positive | Negative | Invalid | Pending | Positivity (Valid %) |
|---|---|---|---|---|---|---|
| 2026-02-25 | 1400 | 76 | 1295 | 20 | 9 | 5.54% |
| 2026-02-26 | 1520 | 88 | 1400 | 22 | 10 | 5.91% |
| 2026-02-27 | 1605 | 91 | 1479 | 25 | 10 | 5.80% |
| 2026-02-28 | 1490 | 80 | 1378 | 22 | 10 | 5.49% |
| 2026-03-01 | 1710 | 103 | 1572 | 25 | 10 | 6.15% |
Formula Used
Positivity (%) is calculated as:
positivity = (positives ÷ denominator) × 100
- Valid tests: positives + negatives
- Completed tests: positives + negatives + invalid/inconclusive
- Total tests: completed tests + pending
The 95% confidence interval uses the Wilson score interval. If sensitivity and specificity are supplied, an approximate adjustment uses the Rogan–Gladen correction.
How to Use This Calculator
- Select whether you are working with tests or people.
- Enter positives and the related counts (negative, invalid, pending).
- Choose a denominator option that matches your reporting standard.
- Optionally add population, sensitivity, and specificity for context.
- Press Calculate to see results and download reports.
FAQs
1) What is the test positivity rate?
It is the percentage of tests that return positive results, calculated as positives divided by a chosen denominator, then multiplied by 100.
2) Which denominator should I use?
Use “valid tests” for positives plus negatives. Use “completed tests” if invalid results are counted as completed. Use “total” if pending tests are included in reporting.
3) Why include invalid or inconclusive results?
Some reporting systems track invalid results as part of completed testing volume. Including them can lower positivity and helps compare operations that retest frequently.
4) What does “by people” mean?
It estimates positivity among individuals tested, not test events. This helps when repeat testing is common and you want a people-based view.
5) What is the 95% confidence interval?
It gives a plausible range for the true positivity proportion, considering sampling uncertainty. Wider intervals happen with smaller denominators or very low/high positivity.
6) How do sensitivity and specificity affect positivity?
Imperfect tests can inflate or deflate observed positivity. If you enter sensitivity and specificity, the calculator shows an approximate adjusted value using a standard correction.
7) Can positivity be high even if case counts are low?
Yes. If testing is limited to higher-risk groups, the denominator shrinks and positivity can rise. Pair positivity with testing volume for interpretation.
8) Are the downloads safe to share?
The downloads include only the values you enter and the built-in example table. Avoid adding personal identifiers if you plan to share files externally.