SARS-CoV-2 Droplet and Airborne Transmission Heterogeneity

Analysis of SARS-CoV-2 transmission in a university classroom based on real human close contact behaviors

Due to high-population density, frequent close contact, possible poor ventilation, university classrooms are vulnerable for transmission of respiratory infectious diseases. Close contact and long-range airborne are possibly main routes for SARS-CoV-2 transmission. In this study, taking a university classroom in Beijing for example, close contact behaviors of students were collected through a depth-detection device, which could detect depth to each pixel of the image, based on semi-supervised learning. Finally, >23 h of video data were obtained. Using Computational Fluid Dynamics, the relationship between viral exposure and close contact behaviors (e.g. interpersonal distance, relative facial orientations, and relative positions) was established. A multi-route transmission model (short-range airborne, mucous deposition, and long-range airborne) of infectious diseases considering real close contact behaviors was developed. In the case of Omicron, the risk of infection in university classrooms and the efficacy of different interventions were assessed based on dose-response model. The average interpersonal distance in university classrooms is 0.9 m (95 % CI, 0.5 m-1.4 m), with the highest proportion of face-to-back contact at 87.0 %. The risk of infection of susceptible students per 45-min lesson was 1 %. The relative contributions of short-range airborne and long-range airborne transmission were 40.5 % and 59.5 %, respectively, and the mucous deposition was basically negligible. When all students are wearing N95 respirators, the infection risk could be reduced by 96 %, the relative contribution of long-range airborne transmission increases to 95.6 %. When the fresh air per capita in the classroom is 24 m3/h/person, the virus exposure could be decreased by 81.1 % compared to the real situation with 1.02 m3/h/person. In a classroom with an occupancy rate of 50 %, after optimized arrangement of student distribution, the infection risk could be decreased by 62 %.

Quantitative assessment of aerosol contamination generated during tooth grinding with a speed-increasing handpiece

OBJECTIVES

Tooth grinding produces a significant amount of aerosol particles. The aim of this study was to quantitatively assess particle contamination produced from tooth grinding with a speed-increasing handpiece across a real-world clinical setting.

METHODS

All molar crowns were pretreated into cylinders with a uniform size. A novel computer-assisted numerical control system was used to parametrically study the bur speed: from 20,000 (20 K) to 200 K rpm at 20 K rpm intervals. 5-minute tooth grinding was performed in triplicate at each speed setting. Three online real-time particle counters (ORPC; TR-8301, TongrenCo.) were placed at 3 positions (0.5, 1, and 1.5 m) to evaluate particle production. All experimental instruments were controlled remotely. The data obtained were statistically analyzed using descriptive statistics and non-parametric tests (Scheirer-Ray-Hare and Kruskal-Wallis/ Dunn-Bonferroni tests, p < 0.05).

RESULTS

The concentration level of aerosol particles production during the grinding experiment was elevated above the control group for all conditions, and increased with bur speed at any location (the maximum peak, reaching 5.59 × 107 particles/m3, at 200 K and 1 m), with differences between conditions. The effect of speed on the increment of particles across different channels compared to the control group was statistically significant among locations (p < 0.001).

CONCLUSIONS

Statistically significant particle contamination was produced using a speed-increasing handpiece, but the contamination level for each experimental condition was reduced to baseline within 30 min, and most particles with a diameter greater than 1üm produced at low speeds (80 K or lower) tended to settle within 1 m.

CLINICAL RELEVANCE

Our study suggested that the use of a speed-increasing handpiece below 80 K and 30 min of fallow time may lead to an adequate reduction in the health effects of particle contamination.

Identify the Virus-like Models for COVID-19 as Bio-Threats: Combining Phage Display, Spectral Detection and Algorithms Analysis

The rapid identification and recognition of COVID-19 have been challenging since its outbreak. Multiple methods were developed to realize fast monitoring early to prevent and control the pandemic. In addition, it is difficult and unrealistic to apply the actual virus to study and research because of the highly infectious and pathogenic SARS-CoV-2. In this study, the virus-like models were designed and produced to replace the original virus as bio-threats. Three-dimensional excitation-emission matrix fluorescence and Raman spectroscopy were employed for differentiation and recognition among the produced bio-threats and other viruses, proteins, and bacteria. Combined with PCA and LDA analysis, the identification of the models for SARS-CoV-2 was achieved, reaching a correction of 88.9% and 96.3% after cross-validation, respectively. This idea might provide a possible pattern for detecting and controlling SARS-CoV-2 from the perspective of combining optics and algorithms, which could be applied in the early-warning system against COVID-19 or other bio-threats in the future.

The Control of Metabolic CO2 in Public Transport as a Strategy to Reduce the Transmission of Respiratory Infectious Diseases

The global acceptance of the SARS-CoV-2 airborne transmission led to prevention measures based on quality control and air renewal. Among them, carbon dioxide (CO2) measurement has positioned itself as a cost-efficiency, reliable, and straightforward method to assess indoor air renewal indirectly. Through the control of CO2, it is possible to implement and validate the effectiveness of prevention measures to reduce the risk of contagion of respiratory diseases by aerosols. Thanks to the method scalability, CO2 measurement has become the gold standard for diagnosing air quality in shared spaces. Even though collective transport is considered one of the environments with the highest rate of COVID-19 propagation, little research has been done where the air inside vehicles is analyzed. This work explores the generation and accumulation of metabolic CO2 in a tramway (Zaragoza, Spain) operation. Importantly, we propose to use the indicator ppm/person as a basis for comparing environments under different conditions. Our study concludes with an experimental evaluation of the benefit of modifying some parameters of the Heating-Ventilation-Air conditioning (HVAC) system. The study of the particle retention efficiency of the implemented filters shows a poor air cleaning performance that, at present, can be counteracted by opening windows. Seeking a post-pandemic scenario, it will be crucial to seek strategies to improve air quality in public transport to prevent the transmission of infectious diseases.