Modeling the infection risk and emergency evacuation from bioaerosol leakage around an urban vaccine factory.

Mounting interest in modeling outdoor diffusion and transmission of bioaerosols due to the prevalence of COVID-19 in the urban environment has led to better knowledge of the issues concerning exposure risk and evacuation planning. In this study, the dispersion and deposition dynamics of bioaerosols around a vaccine factory were numerically investigated under various thermal conditions and leakage rates. To assess infection risk at the pedestrian level, the improved Wells-Riley equation was used. To predict the evacuation path, Dijkstra's algorithm, a derived greedy algorithm based on the improved Wells-Riley equation, was applied. The results show that, driven by buoyancy force, the deposition of bioaerosols can reach 80 m on the windward sidewall of high-rise buildings. Compared with stable thermal stratification, the infection risk of unstable thermal stratification in the upstream portion of the study area can increase by 5.53% and 9.92% under a low and high leakage rate, respectively. A greater leakage rate leads to higher infection risk but a similar distribution of high-risk regions. The present work provides a promising approach for infection risk assessment and evacuation planning for the emergency response to urban bioaerosol leakage.

Estimating the restraint of SARS-CoV-2 spread using a conventional medical air-cleaning device: Based on an experiment in a typical dental clinical setting.

OBJECTIVES: Droplets or aerosols loaded with SARS-CoV-2 can be released during breathing, coughing, or sneezing from COVID-19-infected persons. To investigate whether the most commonly applied air-cleaning device in dental clinics, the oral spray suction machine (OSSM), can provide protection to healthcare providers working in clinics against exposure to bioaerosols during dental treatment. METHOD: In this study, we measured and characterized the temporal and spatial variations in bioaerosol concentration and deposition with and without the use of the OSSM using an experimental design in a dental clinic setting. Serratia marcescens (a bacterium) and ΦX174 phage (a virus) were used as tracers. The air sampling points were sampled using an Anderson six-stage sampler, and the surface-deposition sampling points were sampled using the natural sedimentation method. The Computational Fluid Dynamics method was adopted to simulate and visualize the effect of the OSSM on the concentration spatial distribution. RESULTS: During dental treatment, the peak exposure concentration increased by up to 2-3 orders of magnitude (PFU/m3) for healthcare workers. Meanwhile, OSSM could lower the mean bioaerosol exposure concentration from 58.84 PFU/m3 to 4.10 PFU/m3 for a healthcare worker, thereby inhibiting droplet and airborne transmission. In terms of deposition, OSSM significantly reduced the bioaerosol surface concentration from 28.1 PFU/m3 to 2.5 PFU/m3 for a surface, effectively preventing fomite transmission. CONCLUSION: The use of OSSM showed the potential to restraint the spread of bioaerosols in clinical settings. Our study demonstrates that OSSM use in dental clinics can reduce the exposure concentrations of bioaerosols for healthcare workers during dental treatment and is beneficial for minimizing the risk of infectious diseases such as COVID-19.

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.

Droplet aerosols transportation and deposition for three respiratory behaviors in a typical negative pressure isolation ward.

Negative pressure isolation wards could provide safety for health care workers (HCWs) and patients infected with SARS-CoV-2. However, respiratory behavior releases aerosols containing pathogens, resulting in a potential risk of infection for HCWs. In this study, the spatiotemporal distribution of droplet aerosols in a typical negative pressure isolation ward was investigated using a full-scale experiment. In this experiment, artificial saliva was used to simulate the breathing behavior, which can reflect the effect of evaporation on droplet aerosols. Moreover, numerical simulations were used to compare the transport of droplet aerosols released by the three respiratory behaviors (breathing, speaking, and coughing). The results showed that droplet aerosols generated by coughing and speaking can be removed and deposited more quickly. Because reduction in the suspension proportion per unit time was much higher than that in the case of breathing. Under the air supply inlets, there was significant aerosol deposition on the floor, while the breathing area possessed higher aerosol concentrations. The risk of aerosol resuspension and potential infection increased significantly when HCWs moved frequently to these areas. Finally, more than 20% of the droplet aerosols escaped from the ward when the number of suspended aerosols in the aerosol space was 1%.