Viral interference with SARS-CoV-2 during the COVID-19 pandemic: An individual participant data meta-analysis.
Emma S E M Hauser-van Westrhenen, Marieke L A De Hoog, Angelique M A M Winkel et al.
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In 30 seconds
This individual participant data meta-analysis examined whether SARS-CoV-2 co-occurred with other respiratory viruses in ten cohort studies conducted during 2020–2024. The primary analysis used symptom-independent testing from six cohorts (1,023 participants); co-detection was less frequent than expected under no interference, but the estimate was not statistically significant (OR 0.72; 95% CI 0.40-1.25). In a secondary analysis restricted to symptom-based testing, the association was stronger (OR 0.16; 95% CI 0.10-0.25). The authors suggest selection bias may explain some of this difference.
Key findings
- In symptom-independent testing, SARS-CoV-2 co-detection with another respiratory virus had an OR of 0.72 (95% CI: 0.40-1.25).
- Among symptom-tested samples, the OR of SARS-CoV-2 detection with another virus was 0.16 (95% CI: 0.10-0.25).
- The primary analysis included 205 SARS-CoV-2-positive samples among 2 465 samples (8.3%); the secondary analysis included 506 infections among 2 088 symptomatic samples (24.2%).
Why it matters
Estimates of viral interference may depend substantially on how participants are tested. Symptom-based testing can select for particular infection patterns and produce stronger apparent associations than symptom-independent sampling. This distinction matters when interpreting co-infection data and comparing studies of respiratory viruses during the pandemic.
What to keep in mind
The primary analysis drew on six cohorts and 1,023 participants, and its estimate was non-significant. The secondary analysis used symptom-based testing and may be affected by selection bias.