Evaluation of Two Cyclonic Bioaerosol Samplers for Hospital Air Monitoring in a Calibrated Test Chamber Integrating Aerodynamics and Biological Endpoints

Indoor air quality (IAQ) monitoring in hospital settings is critical to limit airborne transmission of pathogens to vulnerable patients and healthcare workers. However, bioaerosol sampling remains challenging because of the diversity of devices and methodologies and the very low airborne concentration of pathogens in real‐world settings, especially when infectivity‐based measurements, are required for assessing transmission risk. In the absence of harmonized evaluation procedures, it remains difficult to select sampling strategies that are both reliable and fit for purpose. In this study, we developed a controlled and reproducible experimental framework for the evaluation of bioaerosol samplers under conditions relevant to hospital air monitoring. Two widely used cyclonic bioaerosol samplers, Coriolis+ and Coriolis Compact, were assessed in a calibrated 20 m ³ test chamber generating stable atmospheres containing infectious SARS‐CoV‐2, Staphylococcus aureus , or Aspergillus fumigatus at different concentration levels. Samplers′ performance was evaluated using complementary molecular and viability‐based endpoints and was combined with computational fluid dynamics (CFD) and experimental airflow measurements to characterize airflow dynamics. Our results demonstrated that samplers′ performance strongly depended on the biological endpoint and microorganism considered. For SARS‐CoV‐2, the two devices showed comparable recovery of infectious virus, at intermediate and high concentrations, but neither detected infectious particles at the lowest level. In contrast, Coriolis+ achieved near‐complete recovery of viral genomes, whereas Coriolis Compact recovered only a fraction of the expected signal. Regarding S. aureus and A. fumigatus , Coriolis+ achieved superior recovery of viable microorganisms, whereas Coriolis Compact generally yielded higher genomic recovery at moderate and high concentrations. CFD analyses further showed that local airflow conditions and sampler‐specific flow patterns, particularly for the higher flow Coriolis+, are critical for interpreting biological recovery and for defining appropriate placement and operating modes. Overall, this study demonstrates that bioaerosol sampler evaluation must jointly consider molecular, microbiological, and aerodynamic dimensions. The proposed framework offers a basis for more standardized and reproducible performance assessment of bioaerosol samplers and supports evidence‐based selection of air monitoring strategies in healthcare environments.