Flow physics plays a key role in nearly every facet of the COVID-19 pandemic. This includes the generation and aerosolization of virus-laden respiratory droplets from a host, its airborne dispersion and deposition on surfaces, as well as the subsequent inhalation of these bioaerosols by unsuspecting recipients. Fluid dynamics is also key to preventative measures such as the use of face masks, hand-washing, ventilation of indoor environments, and even social distancing. This article summarizes what we know, and more importantly, what we need to learn about the science underlying these issues so that we are better prepared to tackle the next outbreak of COVID-19 or a similar disease.

Flow Physics of COVID-19

Total shutdowns, targeted restrictions, or individual responsibility: How to promote social distancing in the COVID-19 Era?

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9095433

Crowd dynamics research in the era of Covid-19 pandemic: Challenges and opportunities

Air exchange between people has emerged in the COVID-19 pandemic as the important vector for transmission of the SARS-CoV-2 virus. We study the airflow and exchange between two unmasked individuals conversing face-to-face at short range, which can potentially transfer a high dose of a pathogen, because the dilution is small when compared to long-range airborne transmission. We conduct flow visualization experiments and direct numerical simulations of colliding respiratory jets mimicking the initial phase of a conversation. The evolution and dynamics of the jets are affected by the vertical offset between the mouths of the speakers. At low offsets the head-on collision of jets results in a `blocking effect', temporarily shielding the susceptible speaker from the pathogen carrying jet, although, the lateral spread of the jets is enhanced. Sufficiently large offsets prevent the interaction of the jets. At intermediate offsets (8-10 cm for 1 m separation), jet entrainment and the inhaled breath assist the transport of the pathogen-loaded saliva droplets towards the susceptible speaker's mouth. Air exchange is expected, in spite of the blocking effect arising from the interaction of the respiratory jets from the two speakers.

Colliding respiratory jets as a mechanism of air exchange and pathogen transport during conversations

Preventive measures to reduce infection are needed to combat the COVID-19 pandemic and prepare for a possible endemic phase. Current prophylactic vaccines are highly effective to prevent disease but lose their ability to reduce viral transmission as viral evolution leads to increasing immune escape. Long-term proactive public health policies must therefore complement vaccination with available nonpharmaceutical interventions aiming to reduce the viral transmission risk in public spaces. Here, we revisit the quantitative assessment of airborne transmission risk, considering asymptotic limits that considerably simplify its expression. We show that the aerosol transmission risk is the product of three factors: a biological factor that depends on the viral strain, a hydrodynamical factor defined as the ratio of concentration in viral particles between inhaled and exhaled air, and a face mask filtering factor. The short-range contribution to the risk, present both indoors and outdoors, is related to the turbulent dispersion of exhaled aerosols by air drafts and by convection (indoors), or by the wind (outdoors). We show experimentally that airborne droplets and CO2 molecules present the same dispersion. As a consequence, the dilution factor, and therefore the risk, can be measured quantitatively using the CO2 concentration, regardless of the room volume, the flow rate of fresh air, and the occupancy. We show that the dispersion cone leads to a concentration in viral particles, and therefore a short-range transmission risk, inversely proportional to the squared distance to an infected person and to the flow velocity. The aerosolization criterion derived as an intermediate result, which compares the Stokes relaxation time to the Lagrangian time-scale, may find application for a broad class of aerosol-borne pathogens and pollutants. 

/pdf/risk-assessment-for-long-and-short-range-airborne-6k50imgn.pdf

Risk assessment for long- and short-range airborne transmission of SARS-CoV-2, indoors and outdoors

This work aims to assess the risks of Covid-19 disease spread in diverse daily-life situations (referred to as scenarios) involving crowds of unmasked pedestrians, mostly outdoors. More concretely, we develop a method to infer the global number of new infections from patchy observations of pedestrians. The method relies on ad hoc spatially resolved models for disease transmission via virus-laden respiratory droplets, which are fit to existing exposure studies about Covid-19. The approach is applied to the detailed field data about pedestrian trajectories and orientations that we acquired during the pandemic. This allows us to rank the investigated scenarios by the transmission risks that they present; importantly, the obtained hierarchy of risks is conserved across all our transmission models (except the most pessimistic ones): Street cafes present the largest average rate of new infections caused by an attendant, followed by busy outdoor markets, and then metro and train stations, whereas the risks incurred while walking on fairly busy streets (average density around 0.1 person/m^2) are comparatively quite low. Models that assume isotropic transmission of the virus fail to reproduce these results. In scenarios with a moving crowd, we find that density is the main factor influencing the estimated infection rate. Finally, our study explores the efficiency of street and venue redesigns in mitigating the viral spread: While the benefits of enforcing one-way foot traffic in (wide) walkways are unclear, changing the geometry of queues substantially affects disease transmission risks.

Assessment of the risks of viral transmission in non-confined crowds

https://hal.archives-ouvertes.fr/hal-03060324/document

Model-based assessment of the risks of viral transmission in non-confined crowds.

Short‐range exposure to airborne virus‐laden respiratory droplets is an effective transmission route of respiratory diseases, as exemplified by Coronavirus Disease 2019 (COVID‐19). In order to assess the risks associated with this pathway in daily‐life settings involving tens to hundreds of individuals, the chasm needs to be bridged between fluid dynamical simulations and population‐scale epidemiological models. This is achieved by simulating droplet trajectories at the microscale in numerous ambient flows, coarse‐graining their results into spatio‐temporal maps of viral concentration around the emitter, and coupling these maps to field‐data about pedestrian crowds in different scenarios (streets, train stations, markets, queues, and street cafés). At the individual scale, the results highlight the paramount importance of the velocity of the ambient air flow relative to the emitter's motion. This aerodynamic effect, which disperses infectious aerosols, prevails over all other environmental variables. At the crowd's scale, the method yields a ranking of the scenarios by the risks of new infections, dominated by the street cafés and then the outdoor market. While the effect of light winds on the qualitative ranking is fairly marginal, even the most modest air flows dramatically lower the quantitative rates of new infections.

https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/advs.202205255

From Microscopic Droplets to Macroscopic Crowds: Crossing the Scales in Models of Short‐Range Respiratory Disease Transmission, with Application to COVID‐19

This work aims to assess the risks of Covid-19 disease spread in diverse daily-life situations (referred to as scenarios) involving crowds of maskless pedestrians, mostly outdoors. More concretely, we develop a method to infer the global number of new infections from patchyobservations of pedestrians. The method relies on ad hoc spatially resolved models for disease transmissionvia virus-laden respiratory droplets, which are fit to existing exposure studies about Covid-19. The approach is applied to the detailed field data about pedestrian trajectories and orientations that we acquired during the pandemic. This allows us to rank the investigated scenarios by the infection risks that they present; importantly, the obtained hierarchy of risks is conserved across all our transmission models (except the most pessimistic ones): Street caf{\'e}s present the largest average rate of new infections caused by an attendant, followed by busy outdoor markets, and then metro and train stations, whereas the risks incurred while walking on fairly busy streets (average density around 0.1 person/m${}^2$) are comparatively quite low. While none of our ad hoc models can claim accuracy, their converging predictions lend credence to these findings.} In scenarios with a moving crowd, we find that density is the main factor influencing the estimated infection rate. Finally, our study explores the efficiency of street and venue redesigns in mitigating the viral spread: While the benefits of enforcing one-way foot traffic in (wide) walkways are unclear, changing the geometry of queues substantially affects disease transmission risks.

Willy Garcia

Papers

Assessment of the risks of viral transmission in non-confined crowds

Model-based assessment of the risks of viral transmission in non-confined crowds.

From Microscopic Droplets to Macroscopic Crowds: Crossing the Scales in Models of Short‐Range Respiratory Disease Transmission, with Application to COVID‐19

Model-based assessment of the risks of viral transmission in non-confined crowds.