Airborne infection risk during open-air cardiopulmonary resuscitation.

AIM: Cardiopulmonary resuscitation (CPR) is an emergency procedure where interpersonal distance cannot be maintained. There are and will always be outbreaks of infection from airborne diseases. Our objective was to assess the potential risk of airborne virus transmission during CPR in open-air conditions. METHODS: We performed advanced high-fidelity three-dimensional modelling and simulations to predict airborne transmission during out-of-hospital hands-only CPR. The computational model considers complex fluid dynamics and heat transfer phenomena such as aerosol evaporation, breakup, coalescence, turbulence, and local interactions between the aerosol and the surrounding fluid. Furthermore, we incorporated the effects of the wind speed/direction, the air temperature and relative humidity on the transport of contaminated saliva particles emitted from a victim during a resuscitation process based on an Airborne Infection Risk (AIR) Index. RESULTS: The results reveal low-risk conditions that include wind direction and high relative humidity and temperature. High-risk situations include wind directed to the rescuer, low humidity and temperature. Combinations of other conditions have an intermediate AIR Index and risk for the rescue team. CONCLUSIONS: The fluid dynamics, simulation-based AIR Index provides a classification of the risk of contagion by victim's aerosol in the case of hands-only CPR considering environmental factors such as wind speed and direction, relative humidity and temperature. Therefore, we recommend that rescuers perform a quick assessment of their airborne infectious risk before starting CPR in the open air and positioning themselves to avoid wind directed to their faces.

Advancing thermal performance through vortex generators morphing.

The design of rigid vortex generators (RVG) influences the thermal performance of various technologies. We employed Discrete Adjoint-Based Optimization to show the optimal development of vortex generators. Under turbulent flow conditions, different bi-objective functions on the RVG design were examined. Specifically, we aimed at an optimal RVG shape that minimizes the pressure drop and maximizes the local heat transfer in a rectangular channel. We show that an optimal design of an RVG can be obtained using computational fluid dynamics in conjunction with the Pareto Front at a computational cost of the order ~[Formula: see text]. We obtained three essential vortex generator shapes based on the RVG morphing technique. Compared to the baseline geometry of a delta winglet pair DWP, the first morphed design reduced the pressure drop by [Formula: see text], however, at the expense of a [Formula: see text] reduction in the Nusselt number. The second vortex generator design enhanced the heat transfer by [Formula: see text], however, at the cost of a significant increase in pressure drop of about [Formula: see text]. The final morphed design achieved the highest thermal performance factor of 1.28, representing a heat transfer enhancement of [Formula: see text] with a moderate increase in pressure drop of about [Formula: see text] compared to DWP vortex generators. Furthermore, we investigated the effect of introducing different size holes on the mass reduction of vortex generators and their thermal performances. The mass of vortex generators can be reduced by [Formula: see text] and with an increase of [Formula: see text] in thermal performance factor concerning the DWP baseline. The findings of this study will lead to highly efficient lightweight heat exchangers.

The computational fluid dynamics-based epidemic model and the pandemic scenarios.

This study presents a computational fluid dynamics, susceptible-infected-recovered-based epidemic model that relates weather conditions to airborne virus transmission dynamics. The model considers the relationship between weather seasonality, airborne virus transmission, and pandemic outbreaks. We examine multiple scenarios of the COVID-19 fifth wave in London, United Kingdom, showing the potential peak and the period occurring. The study also shows the importance of fluid dynamics and computational modeling in developing more advanced epidemiological models in the future.

Risk assessment of pollen allergy in urban environments.

According to WHO, by 2050, at least one person out of two will suffer from an allergy disorder resulting from the accelerating air pollution associated with toxic gas emissions and climate change. Airborne pollen, and associated allergies, are major public health topics during the pollination season, and their effects are further strengthened due to climate change. Therefore, assessing the airborne pollen allergy risk is essential for improving public health. This study presents a new computational fluid dynamics methodology for risk assessment of local airborne pollen transport in an urban environment. Specifically, we investigate the local airborne pollen transport from trees on a university campus in the north of France. We produce risk assessment maps for pollen allergy for five consecutive days during the pollination season. The proposed methodology could be extended to larger built-up areas for different weather conditions. The risk assessment maps may also be integrated with smart devices, thus leading to decision-aid tools to better guide and protect the public against airborne pollen allergy.

On airborne virus transmission in elevators and confined spaces.

The impact of air ventilation systems on airborne virus transmission (AVT), and aerosols in general, in confined spaces is not yet understood. The recent pandemic has made it crucial to understand the limitations of ventilation systems regarding AVT. We consider an elevator as a prototypical example of a confined space and show how ventilation designs alone, regardless of cooling or heating, contribute to AVT. Air circulation effects are investigated through multiphase computational fluid dynamics, and the performance of an air purifier in an elevator for reducing AVT is assessed. We have investigated three different flow scenarios regarding the position and operation of inlets and outlets in the elevator and a fourth scenario that includes the operation of the air purifier. The position of the inlets and outlets significantly influences the flow circulation and droplet dispersion. An air purifier does not eliminate airborne transmission. The droplet dispersion is reduced when a pair of an inlet and an outlet is implemented. The overall practical conclusion is that the placement and design of the air purifier and ventilation systems significantly affect the droplet dispersion and AVT. Thus, engineering designs of such systems must take into account the flow dynamics in the confined space the systems will be installed.

On pollen and airborne virus transmission.

This study investigates how airborne pollen pellets (or grains) can cause severe respiratory-related problems in humans. Given that pollen pellets can capture ribonucleic acid viruses, we show that airborne pollen grains could transport airborne virus particles such as the airborne coronavirus (CoV) disease (COVID-19) or others. We consider the environmental conditions featuring the highest pollen concentration season and conduct computational multiphysics, multiscale modeling and simulations. The investigation concerns a prototype problem comprising the transport of 104 airborne pollen grains dropped from a mature willow tree at a wind speed of ( U wind = 4 km / h ) . We show how pollen grains can increase the coronavirus (CoV) transmission rate in a group of people, including some infected persons. In the case of high pollen grains concentrations in the air or during pollination in the spring, the social distance of 2 m does not hold as a health safety measure for an outdoor crowd. Thus, the public authorities should revise the social distancing guidelines.

Correcting pandemic data analysis through environmental fluid dynamics.

It is well established that the data reported for the daily number of infected cases during the first wave of the COVID-19 pandemic were inaccurate, primarily due to insufficient tracing across the populations. Due to the uncertainty of the first wave data mixed with the second wave data, the general conclusions drawn could be misleading. We present an uncertainty quantification model for the infected cases of the pandemic's first wave based on fluid dynamics simulations of the weather effects. The model is physics-based and can rectify a first wave data's inadequacy from a second wave data's adequacy in a pandemic curve. The proposed approach combines environmental seasonality-driven virus transmission rate with pandemic multiwave phenomena to improve statistical predictions' data accuracy. For illustration purposes, we apply the new physics-based model to New York City data.

Fluid dynamics and epidemiology: Seasonality and transmission dynamics.

Epidemic models do not account for the effects of climate conditions on the transmission dynamics of viruses. This study presents the vital relationship between weather seasonality, airborne virus transmission, and pandemic outbreaks over a whole year. Using the data obtained from high-fidelity multi-phase, fluid dynamics simulations, we calculate the concentration rate of Coronavirus particles in contaminated saliva droplets and use it to derive a new Airborne Infection Rate (AIR) index. Combining the simplest form of an epidemiological model, the susceptible-infected-recovered, and the AIR index, we show through data evidence how weather seasonality induces two outbreaks per year, as it is observed with the COVID-19 pandemic worldwide. We present the results for the number of cases and transmission rates for three cities, New York, Paris, and Rio de Janeiro. The results suggest that two pandemic outbreaks per year are inevitable because they are directly linked to what we call weather seasonality. The pandemic outbreaks are associated with changes in temperature, relative humidity, and wind speed independently of the particular season. We propose that epidemiological models must incorporate climate effects through the AIR index.

Reducing indoor virus transmission using air purifiers.

Air purifiers are limited to small polluting airborne particles and poor air circulation (fan) for bringing airborne particles inside the device. Thus, the optimal utility of domestic air purifiers (DAPs) for eliminating airborne viruses is still ambiguous. This paper addresses the above limitations using computational fluid dynamics modeling and simulations to investigate the optimal local design of a DAP in an indoor space. We also investigate the integrated fan system and the local transport of airborne viruses. Three different scenarios of using standard DAP equipment ( 144 m 3 / h ) are explored in an indoor space comprising a furnished living room 6 × 6 × 2.5 m 3 . We show that the local positioning of a purifier indoors and the fan system embedded inside it can significantly alter the indoor airborne virus transmission risk. Finally, we propose a new indoor air circulation system that better ensures indoor airborne viruses' local orientation more efficiently than a fan embedded in a standard DAP.

Weather impact on airborne coronavirus survival.

The contribution of this paper toward understanding of airborne coronavirus survival is twofold: We develop new theoretical correlations for the unsteady evaporation of coronavirus (CoV) contaminated saliva droplets. Furthermore, we implement the new correlations in a three-dimensional multiphase Eulerian-Lagrangian computational fluid dynamics solver to study the effects of weather conditions on airborne virus transmission. The new theory introduces a thermal history kernel and provides transient Nusselt (Nu) and Sherwood (Sh) numbers as a function of the Reynolds (Re), Prandtl (Pr), and Schmidt numbers (Sc). For the first time, these new correlations take into account the mixture properties due to the concentration of CoV particles in a saliva droplet. We show that the steady-state relationships induce significant errors and must not be applied in unsteady saliva droplet evaporation. The classical theory introduces substantial deviations in Nu and Sh values when increasing the Reynolds number defined at the droplet scale. The effects of relative humidity, temperature, and wind speed on the transport and viability of CoV in a cloud of airborne saliva droplets are also examined. The results reveal that a significant reduction of virus viability occurs when both high temperature and low relative humidity occur. The droplet cloud's traveled distance and concentration remain significant at any temperature if the relative humidity is high, which is in contradiction with what was previously believed by many epidemiologists. The above could explain the increase in CoV cases in many crowded cities around the middle of July (e.g., Delhi), where both high temperature and high relative humidity values were recorded one month earlier (during June). Moreover, it creates a crucial alert for the possibility of a second wave of the pandemic in the coming autumn and winter seasons when low temperatures and high wind speeds will increase airborne virus survival and transmission.

On coughing and airborne droplet transmission to humans.

Our understanding of the mechanisms of airborne transmission of viruses is incomplete. This paper employs computational multiphase fluid dynamics and heat transfer to investigate transport, dispersion, and evaporation of saliva particles arising from a human cough. An ejection process of saliva droplets in air was applied to mimic the real event of a human cough. We employ an advanced three-dimensional model based on fully coupled Eulerian-Lagrangian techniques that take into account the relative humidity, turbulent dispersion forces, droplet phase-change, evaporation, and breakup in addition to the droplet-droplet and droplet-air interactions. We computationally investigate the effect of wind speed on social distancing. For a mild human cough in air at 20 °C and 50% relative humidity, we found that human saliva-disease-carrier droplets may travel up to unexpected considerable distances depending on the wind speed. When the wind speed was approximately zero, the saliva droplets did not travel 2 m, which is within the social distancing recommendations. However, at wind speeds varying from 4 km/h to 15 km/h, we found that the saliva droplets can travel up to 6 m with a decrease in the concentration and liquid droplet size in the wind direction. Our findings imply that considering the environmental conditions, the 2 m social distance may not be sufficient. Further research is required to quantify the influence of parameters such as the environment's relative humidity and temperature among others.

On respiratory droplets and face masks.

Face mask filters-textile, surgical, or respiratory-are widely used in an effort to limit the spread of airborne viral infections. Our understanding of the droplet dynamics around a face mask filter, including the droplet containment and leakage from and passing through the cover, is incomplete. We present a fluid dynamics study of the transmission of respiratory droplets through and around a face mask filter. By employing multiphase computational fluid dynamics in a fully coupled Eulerian-Lagrangian framework, we investigate the droplet dynamics induced by a mild coughing incident and examine the fluid dynamics phenomena affecting the mask efficiency. The model takes into account turbulent dispersion forces, droplet phase-change, evaporation, and breakup in addition to the droplet-droplet and droplet-air interactions. The model mimics real events by using data, which closely resemble cough experiments. The study shows that the criteria employed for assessing the face mask performance must be modified to take into account the penetration dynamics of airborne droplet transmission, the fluid dynamics leakage around the filter, and reduction of efficiency during cough cycles. A new criterion for calculating more accurately the mask efficiency by taking into account the penetration dynamics is proposed. We show that the use of masks will reduce the airborne droplet transmission and will also protect the wearer from the droplets expelled from other subjects. However, many droplets still spread around and away from the cover, cumulatively, during cough cycles. Therefore, the use of a mask does not provide complete protection, and social distancing remains important during a pandemic. The implications of the reduced mask efficiency and respiratory droplet transmission away from the mask are even more critical for healthcare workers. The results of this study provide evidence of droplet transmission prevention by face masks, which can guide their use and further improvement.