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Repeat Test Person Denominator

Count unique explicitly identified persons among included tests while reporting repeat tests separately.

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Description

Count included tests, distinct people and repeat tests beyond one per person.

Epidemiological reporting depends on case-definition versions, observation windows, censoring, person/test denominators and time-bin boundaries. Missing and indeterminate results differ, while multiple tests can belong to one person. Local record arithmetic does not diagnose infection, establish transmission or select a public-health rule.

Count included tests, distinct people and repeat tests beyond one per person.

When to use this tool

Use Repeat Test Person Denominator when checking the stated benign surveillance record, time, exposure or denominator convention.

How to use the tool and how it works

  1. Enter personIds, included. Follow any array-alignment requirements below. Use the units and conventions below.
  2. Run the tool. Correct any format, range, or cross-field input error before interpreting the output.
  3. Read includedTests, distinctPersons, repeatTests. Use the output convention below.

Require aligned nonempty person IDs and inclusion flags. Filter included rows, count distinct IDs and report included tests minus distinct persons as repeatTests.1

Input fieldMeaning and unitsAccepted input
personIdsPerson IdsRequired. Array of text; maximum UTF-16 length 8192; maximum items 256.
includedIncludedRequired. Array of boolean; maximum items 256.
Output fieldInterpretationReturned shape
includedTestsIncluded TestsRequired. Safe integer.
distinctPersonsDistinct PersonsRequired. Safe integer.
repeatTestsExtra included test records beyond one per distinct supplied person ID, not people with repeated tests.Required. Safe integer.
json
{
  "input": {
    "personIds": [
      "P1",
      "P1",
      "P2"
    ],
    "included": [
      true,
      true,
      true
    ]
  },
  "output": {
    "includedTests": 3,
    "distinctPersons": 2,
    "repeatTests": 1
  }
}

Limitations and assumptions

  • Extra included occurrences are counted, not the number of people tested repeatedly; identity, test validity and disease frequency are not inferred.
  • Inputs must satisfy both the field types and the cross-field conditions above. Invalid input causes an error; a successful false flag or documented placeholder is a different result.

Alternative or Complementary methods

Use verified source records, current authoritative definitions and appropriate complete epidemiological/statistical methods with qualified public-health interpretation for actual decisions.

References

  1. Calculation and input contract: epidemiology/repeat-test-person-denominator — tool.io

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