The impact of high background particle concentration on the spatiotemporal distribution of Serratia marcescens bioaerosol.

Airborne transmission is a well-established mode of dissemination for infectious diseases, particularly in closed environments. However, previous research has often overlooked the potential impact of background particle concentration on bioaerosol characteristics. We compared the spatial and temporal distributions of bioaerosols under two levels of background particle concentration: heavily polluted (150-250 µg/m3) and excellent (0-35 µg/m3) in a typical ward. Serratia marcescens bioaerosol was adopted as a bioaerosol tracer, and the bioaerosol concentrations were quantified using six-stage Andersen cascade impactors. The results showed a significant reduction (over at least 62.9%) in bioaerosol concentration under heavily polluted levels compared to excellent levels at all sampling points. The temporal analysis also revealed that the decay rate of bioaerosols was higher (at least 0.654 min-1) under heavily polluted levels compared to excellent levels. These findings suggest that background particles can facilitate bioaerosol removal, contradicting the assumption made in previous research that background particle has no effect on bioaerosol characteristics. Furthermore, we observed differences in the size distribution of bioaerosols between the two levels of background particle concentration. The average bioaerosols size under heavily polluted levels was found to be higher than that under excellent levels, and the average particle size under heavily polluted levels gradually increased with time. In conclusion, these results highlight the importance of considering background particle concentration in future research on bioaerosol characteristics.

Bioaerosol distribution characteristics and potential SARS-CoV-2 infection risk in a multi-compartment dental clinic.

Dental clinics have a potential risk of infection, particularly during the COVID-19 pandemic. Multi-compartment dental clinics are widely used in general hospitals and independent clinics. This study utilised computational fluid dynamics to investigate the bioaerosol distribution characteristics in a multi-compartment dental clinic through spatiotemporal distribution, working area time-varying concentrations, and key surface deposition. The infection probability of SARS-CoV-2 for the dental staff and patients was calculated using the Wells-Riley model. In addition, the accuracy of the numerical model was verified by field measurements of aerosol concentrations performed during a clinical ultrasonic scaling procedure. The results showed that bioaerosols were mainly distributed in the compartments where the patients were treated. The average infection probability was 3.8% for dental staff. The average deposition number per unit area of the treatment chair and table are 28729 pcs/m2 and 7945 pcs/m2, respectively, which creates a possible contact transmission risk. Moreover, there was a certain cross-infection risk in adjacent compartments, and the average infection probability for patients was 0.84%. The bioaerosol concentrations of the working area in each compartment 30 min post-treatment were reduced to 0.07% of those during treatment, and the infection probability was <0.05%. The results will contribute to an in-depth understanding of the infection risk in multi-compartment dental clinics, forming feasible suggestions for management to efficiently support epidemic prevention and control in dental clinics.