Prediction and control of aerosol transmission of SARS-CoV-2 in ventilated context: from source to receptor.

Global spread of COVID-19 has seriously threatened human life and health. The aerosol transmission route of SARS-CoV-2 is observed often associated with infection clusters under poorly ventilated environment. In the context of COVID-19 pandemic, significant transformation and optimization of traditional ventilation systems are needed. This paper is aimed to offer better understanding and insights into effective ventilation design to maximize its ability in airborne risk control, for particularly the COVID-19. Comprehensive reviews of each phase of aerosol transmission of SARS-CoV-2 from source to receptor are conducted, so as to provide a theoretical basis for risk prediction and control. Infection risk models and their key parameters for risk assessment of SARS-CoV-2 are analyzed. Special focus is given on the efficacy of different ventilation strategies in mitigating airborne transmission. Ventilation interventions are found mainly impacting on the dispersion and inhalation phases of aerosol transmission. The airflow patterns become a key factor in controlling the aerosol diffusion and distribution. Novel and personalized ventilation design, effective integration with other environmental control techniques and resilient HVAC system design to adapt both common and epidemic conditions are still remaining challenging, which need to be solved with the aid of multidisciplinary research and intelligent technologies.

Exploring the potentials of personalized ventilation in mitigating airborne infection risk for two closely ranged occupants with different risk assessment models.

In the context of COVID-19, new requirements are occurring in ventilation systems to mitigate airborne transmission risk in indoor environment. Personalized ventilation (PV) which directly delivers clean air to the occupant's breathing zone is considered as a promising solution. To explore the potentials of PV in preventing the spread of infectious aerosols between closely ranged occupants, experiments were conducted with two breathing thermal manikins with three different relative orientations. Nebulized aerosols were used to mimic exhaled droplets transmitted between the occupants. Four risk assessment models were applied to evaluate the exposure or infection risk affected by PV with different operation modes. Results show that PV was effective in reducing the user's infection risk compared with mixing ventilation alone. Relative orientations and operation modes of PV significantly affected its performance in airborne risk control. The infection risk of SARS-CoV-2 was reduced by 65% with PV of 9 L/s after an exposure duration of 2 h back-to-back as assessed by the dose-response model, indicating effective protection effect of PV against airborne transmission. While the side-by-side orientation was found to be the most critical condition for PV in airborne risk control as it would accelerate diffusion of infectious droplets in lateral diffusion to occupants by side. Optimal designs of PV for closely ranged occupants were hereby discussed. The four risk assessment models were compared and validated by experiments with PV, implying basically consistent rules of the predicted risk with PV among the four models. The relevance and applicability of these models were discussed to provide a basis for risk assessment with non-uniformly distributed pathogens indoor.

Effects of personalized ventilation interventions on airborne infection risk and transmission between occupants.

The role of personalized ventilation (PV) in protecting against airborne disease transmission between occupants was evaluated by considering two scenarios with different PV alignments. The possibility that PV may facilitate the transport of exhaled pathogens was explored by performing experiments with droplets and applying PV to a source or/and a target manikin. The risk of direct and indirect exposure to droplets in the inhalation zone of the target was estimated, with these exposure types defined according to their different origins. The infection risk of influenza A, a typical disease transmitted via air, was predicted based on a dose-response model. Results showed that the flow interactions between PV and the infectious exhaled flow would facilitate airborne transmission between occupants in two ways. First, application of PV to the source caused more than 90% of indirect exposure of the target. Second, entrainment of the PV jet directly from the infectious exhalation increased direct exposure of the target by more than 50%. Thus, these scenarios for different PV application modes indicated that continuous exposure to exhaled influenza A virus particles for 2 h would correspond with an infection probability ranging from 0.28 to 0.85. These results imply that PV may protect against infection only when it is maintained with a high ventilation efficiency at the inhalation zone, which can be realized by reduced entrainment of infectious flow and higher clean air volume. Improved PV design methods that could maximize the positive effects of PV on disease control in the human microenvironment are discussed.

Human exhalation characterization with the aid of schlieren imaging technique.

The purpose of this paper is to determine the dispersion and distribution characteristics of exhaled airflow for accurate prediction of disease transmission. The development of airflow dynamics of human exhalation was characterized using nonhazardous schlieren photography technique, providing a visualization and quantification of turbulent exhaled airflow from 18 healthy human subjects whilst standing and lying. The flow shape of each breathing pattern was characterized by two angles and averaged values of 18 subjects. Two exhaled air velocities, u m and u p , were measured and compared. The mean peak centerline velocity, u m was found to decay correspondingly with increasing horizontal distance x in a form of power function. The mean propagation velocity, u p was found to correlate with physiological parameters of human subjects. This was always lower than u m at the mouth/nose opening, due to a vortex like airflow in front of a single exhalation cycle. When examining the talking and breathing process between two persons, the potential infectious risk was found to depend on their breathing patterns and spatial distribution of their exhaled air. Our study when combined with information on generation and distributions of pathogens could provide a prediction method and control strategy to minimize infection risk between persons in indoor environments.