COVID-19 patient variables associated with the detection of airborne SARS-CoV-2.

BACKGROUND

Understanding the COVID-19 patient characteristics that impact environmental SARS-CoV-2 load is essential for improving infection risk management. In this study, we analyzed the influence of patient variables on airborne SARS-CoV-2 genome detection.

METHODS

Sixty-nine COVID-19 patients were recruited across three independent studies with airborne SARS-CoV-2 genome assessed in individual hospital rooms using droplet digital PCR.

RESULTS

In the bivariate analysis, the odds of airborne SARS-CoV-2 detection were significantly higher for patients with obesity, chronic respiratory diseases, pneumonia at admission, sampling, and discharge, and lower lymphocytes count. No significant associations were found between airborne SARS-CoV-2 detection and symptoms presence or duration, nor with the results of the most recent positive nasopharyngeal PCR test prior to air sampling. In the multivariate analysis, the best-fit model included patient age, type of admission, and symptoms duration. Patient age significantly contributed to the risk of airborne SARS-CoV-2 detection in the multivariate analysis.

CONCLUSIONS

Our findings highlight the variability in individual responses to SARS-CoV-2 infection and suggest that factors linked to COVID-19 severity, symptomatology, and immunocompetence influence the airborne SARS-CoV-2 detection. Our results may support the development of more precise preventive measures in healthcare settings.