Objective: Patients with chronic kidney disease suffer from immune dysfunction, increasing susceptibility to infections. The aim of the study was to investigate air contamination with respiratory viruses in a dialysis unit at a quaternary hospital using molecular detection techniques and to analyze airflow dynamics through computational fluid dynamics (CFD) simulations for a comprehensive assessment of air transmission risks.

Methods: We conducted dialysis unit air sampling using AerosolSense™ samplers. Air and clinical sampling occurred during three periods in 2022: winter, early, and late fall. A technical team maintained the dialysis unit's ventilation system during mid fall. Ventilation system capacity and airflow rates were measured. CFD simulations were used to evaluate airflow dynamics.

Results: The investigation collected 144 air samples, revealing heterogeneous virus detection rates across locations and study periods. Virus positivity correlated with the presence of patients and the effectiveness of the ventilation system. The ratio of virus air positivity to virus patient positivity was 1.84 and 3.35 during the first and the second periods, respectively, and collapsed to 0.64 after maintenance. Airflow rate measurements highlighted a ninefold discrepancy between actual and theoretical airflow (393 m/h 3530 m/h), which was rectified by maintenance actions. Airflow dynamics and particle dispersion visualization through CFD simulations contributed to a better understanding of transmission risks.

Conclusions: Detection of viruses in the air, combined with CFD, revealed deficiencies in air renewal. Maintenance interventions significantly improved airflow dynamics and particle dispersion, reducing airborne virus spread.

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Source
http://dx.doi.org/10.1017/ice.2024.217DOI Listing

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