Environmental viral DNA produced many false-positive mpox PCR results

Design

Multi-site observational study with Bayesian latent class model and serological validation

Population

2,724 people with suspected mpox at four sites in DR Congo, 2024–2026

Primary outcome

Proportion of PCR positives attributable to environmental viral DNA

Effect

35% (95% CrI 31–39) at Ct <40; 18% at Ct <37; 5% at Ct <34

Investigators collected cycle threshold (Ct) values from 2,724 people with suspected mpox at treatment centres in four locations in DR Congo between May 2024 and April 2026, and swabbed clinic and laboratory surfaces at two sites. A Bayesian model separated true infections from positives consistent with environmental viral DNA, and was checked against later serology.

About 35% (95% credible interval 31–39%) of PCR results with Ct under 40 were estimated to be false positives. Among those with serology, 31 of 35 classed as contamination had no evidence of orthopoxvirus infection. Lowering the positivity cut-off to Ct under 37 reduced the false-positive share to 18%, and under 34 to 5%, with only small losses in sensitivity.

Highly sensitive PCR for a DNA virus is vulnerable to contamination where many infected patients are seen. A weakly positive result in a patient without a typical rash or exposure deserves repetition and clinical correlation before it drives isolation, contact tracing or vaccination decisions.

• Treat a high-Ct mpox PCR result with caution in a clinic that sees many cases.
• Repeat the test and check the clinical picture and exposure history before acting on a weak positive.
• Ask your laboratory what Ct cut-off it uses and whether it reports the Ct value.
• Decontaminate examination areas and sampling surfaces regularly where mpox is common.
• Serology can help confirm or refute an uncertain case where it is available.

Why it matters

Outbreak counts, isolation and vaccine allocation all rest on PCR positivity, and this suggests a large share of positives may be contamination.

Don't overread it

The false-positive estimates come from a statistical model in very high-transmission clinics; they do not apply directly to low-incidence settings.

The statistics, in plain English

A credible interval is the Bayesian equivalent of a confidence interval: the model is 95% sure the true false-positive share lies between 31% and 39%. Lower Ct values mean more viral DNA, so a lower cut-off accepts only stronger signals.

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