Evaluating the efficacy of a rotating upper-room UVC-LED irradiation device in inactivating aerosolized Escherichia coli under different disinfection ranges, air mixing, and irradiation conditions

Cost-effective and safe air disinfection methods are urgently needed in various environmental public settings. A novel UVC-based disinfection system was designed and tested to provide a promising solution because of its effective inactivation of indoor bioaerosols at a low cost. UVC light-emitting diodes (UVC-LEDs) were utilized as the irradiation source. This system has the unique feature of rotating the UVC-LEDs to generate a "scanning irradiation" zone. Escherichia coli was aerosolized into an experimental chamber, exposed to UVC-LEDs, and sampled using an impactor. Effects of air mixing (well-mixed vs. poorly-mixed), transmission range (short vs. long), and irradiation mode (stationary vs. rotating) were evaluated. The system performs significantly well under the poorly-mixed condition. The results obtained from the short disinfection range indicate that the rotating UVC was approximately 70.5 % more effective than the stationary UVC for the poorly-mixed case. Further, we evaluated the performance of the long disinfection range under a poorly-mixed situation, and the disinfection efficacy was 84.6 % higher for the rotating irradiation than that of the stationary. About 0.59-1.34 J/m² UV dose can be used to obtain one-log inactivation of E. coli. In conclusion, the novel rotating upper-room UVC-LED system is effective in reducing indoor pathogen transmission, and our findings are highly significant to a growing field where LEDs are applied for disinfection.

Mobile human ad hoc networks: A communication engineering viewpoint on interhuman airborne pathogen transmission

A number of transmission models for airborne pathogens transmission, as required to understand airborne infectious diseases such as COVID-19, have been proposed independently from each other, at different scales, and by researchers from various disciplines. We propose a communication engineering approach that blends different disciplines such as epidemiology, biology, medicine, and fluid dynamics. The aim is to present a unified framework using communication engineering, and to highlight future research directions for modeling the spread of infectious diseases through airborne transmission. We introduce the concept of mobile human ad hoc networks (MoHANETs), which exploits the similarity of airborne transmission-driven human groups with mobile ad hoc networks and uses molecular communication as the enabling paradigm. In the MoHANET architecture, a layered structure is employed where the infectious human emitting pathogen-laden droplets and the exposed human to these droplets are considered as the transmitter and receiver, respectively. Our proof-of-concept results, which we validated using empirical COVID-19 data, clearly demonstrate the ability of our MoHANET architecture to predict the dynamics of infectious diseases by considering the propagation of pathogen-laden droplets, their reception and mobility of humans.

A simplified tempo-spatial model to predict airborne pathogen release risk in enclosed spaces: An Eulerian-Lagrangian CFD approach

COVID19 pathogens are primarily transmitted via airborne respiratory droplets expelled from infected bio-sources. However, there is a lack of simplified accurate source models that can represent the airborne release to be utilized in the safe-social distancing measures and ventilation design of buildings. Although computational fluid dynamics (CFD) can provide accurate models of airborne disease transmissions, they are computationally expensive. Thus, this study proposes an innovative framework that benefits from a series of relatively accurate CFD simulations to first generate a dataset of respiratory events and then to develop a simplified source model. The dataset has been generated based on key clinical parameters (i.e., the velocity of droplet release) and environmental factors (i.e., room temperature and relative humidity) in the droplet release modes. An Eulerian CFD model is first validated against experimental data and then interlinked with a Lagrangian CFD model to simulate trajectory and evaporation of numerous droplets in various sizes (0.1 μm-700 μm). A risk assessment model previously developed by the authors is then applied to the simulation cases to identify the horizontal and vertical spread lengths (risk cloud) of viruses in each case within an exposure time. Eventually, an artificial neural network-based model is fitted to the spread lengths to develop the simplified predictive source model. The results identify three main regimes of risk clouds, which can be fairly predicted by the ANN model.

CFD modeling of airborne pathogen transmission of COVID-19 in confined spaces under different ventilation strategies

Airborne transmission is an important route of spread of viral diseases (e.g., COVID-19) inside the confined spaces. In this respect, computational fluid dynamics (CFD) emerged as a reliable and fast tool to understand the complex flow patterns in such spaces. Most of the recent studies, nonetheless, focused on the spatial distribution of airborne pathogens to identify the infection probability without considering the exposure time. This research proposes a framework to evaluate the infection probability related to both spatial and temporal parameters. A validated Eulerian-Lagrangian CFD model of exhaled droplets is first developed and then evaluated with an office case study impacted by different ventilation strategies (i.e., cross- (CV), single- (SV), mechanical- (MV) and no-ventilation (NV)). CFD results were analyzed in a bespoke code to calculate the tempo-spatial distribution of accumulated airborne pathogens. Furthermore, two indices of local and general infection risks were used to evaluate the infection probability of the ventilation scenarios. The results suggest that SV has the highest infection probability while SV and NO result in higher dispersions of airborne pathogens inside the room. Eventually, the time history of indices reveals that the efficiency of CV and MV can be poor in certain regions of the room.

Role of mechanical ventilation in the airborne transmission of infectious agents in buildings

Infectious disease outbreaks and epidemics such as those due to SARS, influenza, measles, tuberculosis, and Middle East respiratory syndrome coronavirus have raised concern about the airborne transmission of pathogens in indoor environments. Significant gaps in knowledge still exist regarding the role of mechanical ventilation in airborne pathogen transmission. This review, prepared by a multidisciplinary group of researchers, focuses on summarizing the strengths and limitations of epidemiologic studies that specifically addressed the association of at least one heating, ventilating and/or air-conditioning (HVAC) system-related parameter with airborne disease transmission in buildings. The purpose of this literature review was to assess the quality and quantity of available data and to identify research needs. This review suggests that there is a need for well-designed observational and intervention studies in buildings with better HVAC system characterization and measurements of both airborne exposures and disease outcomes. Studies should also be designed so that they may be used in future quantitative meta-analyses.