Result statuses

Before any prevalence math happens, PrevIQ classifies each raw result cell into one of four statuses. This is what guarantees that "not tested" and "invalid" results never quietly distort a rate.

The four statuses

Status	Meaning	Counts in denominator?	Counts as detection?
Positive	Organism was detected	✅ Yes	✅ Yes
Negative	Tested, not detected	✅ Yes	❌ No
Skip	Not tested for this specimen	❌ No	❌ No
Exclude	Invalid / indeterminate result	❌ No	❌ No

How raw values map

PrevIQ recognizes the exact set of values produced by laboratory exports:

Positive

Detected
Detected-High      ← quantification preserved as metadata
Detected-Med
Detected-Low

Negative

Not-Detected

Skip (not tested)

N/A

Exclude (invalid)

IND   ← indeterminate
INV   ← invalid
RER   ← repeat error / re-run

Note

Quantification levels (High / Med / Low) are stored as metadata, but prevalence is computed on the binary collapse — detected vs. not. A "Detected-Low" still counts as a detection.

Why Skip and Exclude leave the math entirely

Both Skip and Exclude are removed from the numerator and the denominator:

• Skip (N/A) — the organism wasn't tested on this specimen, so it shouldn't lower the rate (it would if we left it in the denominator as a non-detection).
• Exclude (IND / INV / RER) — the result is unreliable, so including it either way would introduce noise.

Important

This is why you can trust that a PrevIQ rate reflects only specimens that were genuinely tested and produced a valid result. A specimen that was never tested for an organism has zero effect on that organism's rate.

Unknown values

If an export contains a result value PrevIQ doesn't recognize, the ingestion run is flagged with UNKNOWN_RESULT so it can be reviewed rather than silently mishandled. See Data & freshness.

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