A quanta-independent approach for the assessment of strategies to reduce the risk of airborne infection.

The Wells-Riley model is extensively used for retrospective and prospective modelling of the risk of airborne transmission of infection in indoor spaces. It is also used when examining the efficacy of various removal and deactivation methods for airborne infectious aerosols in the indoor environment, which is crucial when selecting the most effective infection control technologies. The problem is that the large variation in viral load between individuals makes the Wells-Riley model output very sensitive to the input parameters and may yield a flawed prediction of risk. The absolute infection risk estimated with this model can range from nearly 0 % to 100 % depending on the viral load, even when all other factors, such as removal mechanisms and room geometry, remain unchanged. We therefore propose a novel method that removes this sensitivity to viral load. We define a quanta-independent maximum absolute before-after difference in infection risk that is independent of quanta factors like viral load, physical activity, or the dose-response relationships. The input data needed for a non-steady-state calculation are just the removal rates, room volume, and occupancy duration. Under steady-state conditions the approach provides an elegant solution that is only dependent on removal mechanisms before and after applying infection control measures. We applied this method to compare the impact of relative humidity, ventilation rate and its effectiveness, filtering efficiency, and the use of ultraviolet germicidal irradiation on the infection risk. The results demonstrate that the method provides a comprehensive understanding of the impact of infection control strategies on the risk of airborne infection, enabling rational decisions to be made regarding the most effective strategies in a specific context. The proposed method thus provides a practical tool for mitigation of airborne infection risk.

Does the exponential Wells-Riley model provide a good fit for human coronavirus and rhinovirus? A comparison of four dose-response models based on human challenge data.

The risk assessments during the COVID-19 pandemic were primarily based on dose-response models derived from the pooled datasets for infection of animals susceptible to SARS-CoV. Despite similarities, differences in susceptibility between animals and humans exist for respiratory viruses. The two most commonly used dose-response models for calculating the infection risk of respiratory viruses are the exponential and the Stirling approximated ß-Poisson (BP) models. The modified version of the one-parameter exponential model or the Wells-Riley model was almost solely used for infection risk assessments during the pandemic. Still, the two-parameter (α and ß) Stirling approximated BP model is often recommended compared to the exponential dose-response model due to its flexibility. However, the Stirling approximation restricts this model to the general rules of ߠ≫ 1 and α â‰ª ß, and these conditions are very often violated. To refrain from these requirements, we tested a novel BP model by using the Laplace approximation of the Kummer hypergeometric function instead of the conservative Stirling approximation. The datasets of human respiratory airborne viruses available in the literature for human coronavirus (HCoV-229E) and human rhinovirus (HRV-16 and HRV-39) are used to compare the four dose-response models. Based on goodness-of-fit criteria, the exponential model was the best fitting model for the HCoV-229E (k = 0.054) and for HRV-39 datasets (k = 1.0), whereas the Laplace approximated BP model followed by the exact and Stirling approximated BP models are preferred for both the HRV-16 (α = 0.152 and ß = 0.021 for Laplace BP) and the HRV-16 and HRV-39 pooled datasets (α = 0.2247 and ß = 0.0215 for Laplace BP).

pH-dependent endocytosis mechanisms for influenza A and SARS-coronavirus.

The ongoing SARS-CoV-2 pandemic and the influenza epidemics have revived the interest in understanding how these highly contagious enveloped viruses respond to alterations in the physicochemical properties of their microenvironment. By understanding the mechanisms and conditions by which viruses exploit the pH environment of the host cell during endocytosis, we can gain a better understanding of how they respond to pH-regulated anti-viral therapies but also pH-induced changes in extracellular environments. This review provides a detailed explanation of the pH-dependent viral structural changes preceding and initiating viral disassembly during endocytosis for influenza A (IAV) and SARS coronaviruses. Drawing upon extensive literature from the last few decades and latest research, I analyze and compare the circumstances in which IAV and SARS-coronavirus can undertake endocytotic pathways that are pH-dependent. While there are similarities in the pH-regulated patterns leading to fusion, the mechanisms and pH activation differ. In terms of fusion activity, the measured activation pH values for IAV, across all subtypes and species, vary between approximately 5.0 to 6.0, while SARS-coronavirus necessitates a lower pH of 6.0 or less. The main difference between the pH-dependent endocytic pathways is that the SARS-coronavirus, unlike IAV, require the presence of specific pH-sensitive enzymes (cathepsin L) during endosomal transport. Conversely, the conformational changes in the IAV virus under acidic conditions in endosomes occur due to the specific envelope glycoprotein residues and envelope protein ion channels (viroporins) getting protonated by H+ ions. Despite extensive research over several decades, comprehending the pH-triggered conformational alterations of viruses still poses a significant challenge. The precise mechanisms of protonation mechanisms of certain during endosomal transport for both viruses remain incompletely understood. In absence of evidence, further research is needed.

New dose-response model and SARS-CoV-2 quanta emission rates for calculating the long-range airborne infection risk.

Predictive models for airborne infection risk have been extensively used during the pandemic, but there is yet still no consensus on a common approach, which may create misinterpretation of results among public health experts and engineers designing building ventilation. In this study we applied the latest data on viral load, aerosol droplet sizes and removal mechanisms to improve the Wells Riley model by introducing the following novelties i) a new model to calculate the total volume of respiratory fluid exhaled per unit time ii) developing a novel viral dose-based generation rate model for dehydrated droplets after expiration iii) deriving a novel quanta-RNA relationship for various strains of SARS-CoV-2 iv) proposing a method to account for the incomplete mixing conditions. These new approaches considerably changed previous estimates and allowed to determine more accurate average quanta emission rates including omicron variant. These quanta values for the original strain of 0.13 and 3.8 quanta/h for breathing and speaking and the virus variant multipliers may be used for simple hand calculations of probability of infection or with developed model operating with six size ranges of aerosol droplets to calculate the effect of ventilation and other removal mechanisms. The model developed is made available as an open-source tool.

Zonal modeling of air distribution impact on the long-range airborne transmission risk of SARS-CoV-2.

A widely used analytical model to quantitatively assess airborne infection risk is the Wells-Riley model which is limited to complete air mixing in a single zone. However, this assumption tends not to be feasible (or reality) for many situations. This study aimed to extend the Wells-Riley model so that the infection risk can be calculated in spaces where complete mixing is not present. Some more advanced ventilation concepts create either two horizontally divided air zones in spaces as displacement ventilation or the space may be divided into two vertical zones by downward plane jet as in protective-zone ventilation systems. This is done by evaluating the time-dependent distribution of infectious quanta in each zone and by solving the coupled system of differential equations based on the zonal quanta concentrations. This model introduces a novel approach by estimating the interzonal mixing factor based on previous experimental data for three types of ventilation systems: incomplete mixing ventilation, displacement ventilation, and protective zone ventilation. The modeling approach is applied to a room with one infected and one susceptible person present. The results show that using the Wells-Riley model based on the assumption of completely air mixing may considerably overestimate or underestimate the long-range airborne infection risk in rooms where air distribution is different than complete mixing, such as displacement ventilation, protected zone ventilation, warm air supplied from the ceiling, etc. Therefore, in spaces with non-uniform air distribution, a zonal modeling approach should be preferred in analytical models compared to the conventional single-zone Wells-Riley models when assessing long-range airborne transmission risk of infectious respiratory diseases.

Modeling the impact of indoor relative humidity on the infection risk of five respiratory airborne viruses.

With a modified version of the Wells-Riley model, we simulated the size distribution and dynamics of five airborne viruses (measles, influenza, SARS-CoV-2, human rhinovirus, and adenovirus) emitted from a speaking person in a typical residential setting over a relative humidity (RH) range of 20-80% and air temperature of 20-25 °C. Besides the size transformation of virus-containing droplets due to evaporation, respiratory absorption, and then removal by gravitational settling, the modified model also considered the removal mechanism by ventilation. The trend and magnitude of RH impact depended on the respiratory virus. For rhinovirus and adenovirus humidifying the indoor air from 20/30 to 50% will be increasing the relative infection risk, however, this relative infection risk increase will be negligible for rhinovirus and weak for adenovirus. Humidification will have a potential benefit in decreasing the infection risk only for influenza when there is a large infection risk decrease for humidifying from 20 to 50%. Regardless of the dry solution composition, humidification will overall increase the infection risk via long-range airborne transmission of SARS-CoV-2. Compared to humidification at a constant ventilation rate, increasing the ventilation rate to moderate levels 0.5 → 2.0 h-1 will have a more beneficial infection risk decrease for all viruses except for influenza. Increasing the ventilation rate from low values of 0.5 h-1 to higher levels of 6 h-1 will have a dominating effect on reducing the infection risk regardless of virus type.

Experimental study on the exposure level of surgical staff to SARS-CoV-2 in operating rooms with mixing ventilation under negative pressure.

The purpose of this study was to reveal the exposure level of surgical staff to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) from the patient's nose and wound during operations on COVID-19 patients. The tracer gas N2O is used to simulate SARS-CoV-2 from the patient's nose and wound. In this study, concentration levels of tracer gas were measured in the breathing zones of these surgical staff in the operating room under three pressure difference conditions: -5 pa-15 pa and -25 pa compared to the adjunction room. These influencing factors on exposure level are analyzed in terms of ventilation efficiency and the thermal plume distribution characteristics of the patient. The results show that the assistant surgeon faces 4 to 12 times higher levels of exposure to SARS-CoV-2 than other surgical staff. Increasing the pressure difference between the OR lab and adjunction room can reduce the level of exposure for the main surgeon and assistant surgeon. Turning on the cooling fan of the endoscope imager may result in a higher exposure level for the assistant surgeon. Surgical nurses outside of the surgical microenvironment are exposed to similar contaminant concentration levels in the breathing zone as in the exhaust. However, the ventilation efficiency is not constant near the surgical patient or in the rest of the room and will vary with a change in pressure difference. This may suggest that the air may not be fully mixed in the surgical microenvironment.

Estimating the impact of indoor relative humidity on SARS-CoV-2 airborne transmission risk using a new modification of the Wells-Riley model.

A novel modified version of the Wells-Riley model was used to estimate the impact of relative humidity (RH) on the removal of respiratory droplets containing the SARS-CoV-2 virus by deposition through gravitational settling and its inactivation by biological decay; the effect of RH on susceptibility to SARS-CoV-2 was not considered. These effects were compared with the removal achieved by increased ventilation rate with outdoor air. Modeling was performed assuming that the infected person talked continuously for 60 and 120 min. The results of modeling showed that the relative impact of RH on the infection risk depended on the ventilation rate and the size range of virus-laden droplets. A ventilation rate of 0.5 ACH, the change of RH between 20% and 53% was predicted to have a small effect on the infection risk, while at a ventilation rate of 6 ACH this change had nearly no effect. On the contrary, increasing the ventilation rate from 0.5 ACH to 6 ACH was predicted to decrease the infection risk by half which is remarkably larger effect compared with that predicted for RH. It is thus concluded that increasing the ventilation rate is more beneficial for reducing the airborne levels of SARS-CoV-2 than changing indoor RH. PRACTICAL IMPLICATIONS: The present results show that humidification to moderate levels of 40%-60% RH should not be expected to provide a significant reduction in infection risk caused by SARS-CoV-2, hence installing and running humidifiers may not be an efficient solution to reduce the risk of COVID-19 disease in indoor spaces. The results do however confirm that ventilation has a key role in controlling SARS-CoV-2 virus concentration in the air providing considerably higher benefits. The modified model developed in the present work can be used by public health experts, engineers, and epidemiologists when selecting different measures to reduce the infection risk from SARS-CoV-2 indoors allowing informed decisions concerning indoor environmental control.

Experimental and simulated evaluations of airborne contaminant exposure in a room with a modified localized laminar airflow system.

The traditional mixing ventilation is not an energy effective approach to remove indoor air pollutants, maintain breath zone air quality, and control the airborne transmission. This study investigated the potential of a localized laminar airflow ventilation system to alleviate human exposure to pollutants. Breathing thermal manikins with sitting posture and supine posture were used to simulate the human. N2O was used as the tracer gas to simulate the indoor pollutant emission. The contaminant exposure index (εexp) and intake fraction index (IF) were used to assess the risk of human pollutant exposure for various supply air velocities given different emission source positions. Enhanced pollutant removal efficiency (Eff) (from the result) showed the qualification and desirability of the localized laminar airflow ventilation system in improving the breath zone air quality. The results showed that the CFD results could fit well with the experimental data and found out the interaction between thermal plume and supply air. The results also indicated a low εexp and IF, with over 90%, all of which were highly correlated with the supply velocity. Human's different breathing methods have little influence on the pollutant exposure so as to the location of the pollution source. This study found that localized laminar airflow ventilation system could efficiently provide fresh air to the breathing zone without sacrificing the thermal environment around human. It can be used for small region air quality control such as that in the bedroom and living room where desired air quality is favored.

Do surgeons and surgical facilities disturb the clean air distribution close to a surgical patient in an orthopedic operating room with laminar airflow?

BACKGROUND: Airflow distribution in the operating room plays an important role in ensuring a clean operating microenvironment and preventing surgical site infections (SSIs) caused by airborne contaminations. The objective of this study was to characterize the airflow distribution in proximity to a patient in an orthopedic operating room. METHODS: Experimental measurements were conducted in a real operating room at St. Olav's Hospital, Norway, with a laminar airflow system. Omnidirectional anemometers were used to investigate the air distribution in the operating zone, and 4 different cases were examined with a real person and a thermal manikin. RESULTS: This study showed that the downward airflow from the laminar airflow system varies in each case with different surgical arrangement, such as the position of the operating lamp. The results indicate that the interaction of thermal plumes from a patient and the downward laminar airflow may dominate the operating microenvironment. CONCLUSIONS: The airflow distribution in proximity to a patient is influenced by both the surgical facility and the presence of medical staff. A thermal manikin may be an economical and practical way to study the interaction of thermal plumes and downward laminar airflow. The provision of higher clean airflow rate in the operating microenvironment may be an effective way to prevent the development of SSIs caused by indoor airborne contamination.