Far-UVC (222 nm) efficiently inactivates an airborne pathogen in a room-sized chamber.

Many infectious diseases, including COVID-19, are transmitted by airborne pathogens. There is a need for effective environmental control measures which, ideally, are not reliant on human behaviour. One potential solution is Krypton Chloride (KrCl) excimer lamps (often referred to as Far-UVC), which can efficiently inactivate pathogens, such as coronaviruses and influenza, in air. Research demonstrates that when KrCl lamps are filtered to remove longer-wavelength ultraviolet emissions they do not induce acute reactions in the skin or eyes, nor delayed effects such as skin cancer. While there is laboratory evidence for Far-UVC efficacy, there is limited evidence in full-sized rooms. For the first time, we show that Far-UVC deployed in a room-sized chamber effectively inactivates aerosolised Staphylococcus aureus. At a room ventilation rate of 3 air-changes-per-hour (ACH), with 5 filtered-sources the steady-state pathogen load was reduced by 98.4% providing an additional 184 equivalent air changes (eACH). This reduction was achieved using Far-UVC irradiances consistent with current American Conference of Governmental Industrial Hygienists threshold limit values for skin for a continuous 8-h exposure. Our data indicate that Far-UVC is likely to be more effective against common airborne viruses, including SARS-CoV-2, than bacteria and should thus be an effective and "hands-off" technology to reduce airborne disease transmission. The findings provide room-scale data to support the design and development of effective Far-UVC systems.

Modeling fomite-mediated SARS-CoV-2 exposure through personal protective equipment doffing in a hospital environment.

Self-contamination during doffing of personal protective equipment (PPE) is a concern for healthcare workers (HCW) following SARS-CoV-2-positive patient care. Staff may subconsciously become contaminated through improper glove removal; so, quantifying this exposure is critical for safe working procedures. HCW surface contact sequences on a respiratory ward were modeled using a discrete-time Markov chain for: IV-drip care, blood pressure monitoring, and doctors' rounds. Accretion of viral RNA on gloves during care was modeled using a stochastic recurrence relation. In the simulation, the HCW then doffed PPE and contaminated themselves in a fraction of cases based on increasing caseload. A parametric study was conducted to analyze the effect of: (1a) increasing patient numbers on the ward, (1b) the proportion of COVID-19 cases, (2) the length of a shift, and (3) the probability of touching contaminated PPE. The driving factors for the exposure were surface contamination and the number of surface contacts. The results simulate generally low viral exposures in most of the scenarios considered including on 100% COVID-19 positive wards, although this is where the highest self-inoculated dose is likely to occur with median 0.0305 viruses (95% CI =0-0.6 viruses). Dose correlates highly with surface contamination showing that this can be a determining factor for the exposure. The infection risk resulting from the exposure is challenging to estimate, as it will be influenced by the factors such as virus variant and vaccination rates.