Lydia Bourouiba

Upon radial liquid sheet expansion, a bounding rim forms, with a thickness and stability governed, in part, by the liquid influx from the unsteady connected sheet. We examine how the thickness and fragmentation of such a radially expanding rim change upon its severance from its sheet, absent of liquid influx. To do so, we design an experiment enabling the study of rims pre- and post-severance by vaporising the thin neck connecting the rim. No vaporisation occurs of the bulk rim itself. We confirm that the severed rim follows a ballistic motion, with a radial velocity inherited from the sheet at severance time. We identify that the severed rim undergoes fragmentation in two types of junctions: the base of inherited, pre-severance, ligaments and the junction between nascent rim corrugations, with no significant distinction between the two associated time scales. The number of ligaments and fragments formed is captured well by the theoretical prediction of rim corrugation and ligament wavenumbers established for unsteady expanding sheets upon droplet impact on surfaces of comparable size to the droplet. Our findings are robust to changes in impacting laser energy and initial droplet size. Finally, we report and analyse the re-formation of the rim on the expanding sheet and propose a prediction for its characteristic corrugation time scale. Our findings highlight the fundamental mechanisms governing interfacial destabilisation of connected fluid-fed expanding rims that become severed, thereby clarifying destabilisation of freely radially expanding toroidal fluid structures absent of fluid influx.

(Mtb) passes from infected to susceptible hosts, yet the environmental, biophysical and microbial factors governing this process remain poorly understood. In the early twentieth century, Perla and Lurie used guinea pigs to demonstrate natural airborne transmission of Mtb, but such studies have not been revisited in the modern biosafety era. Here, we developed an aerodynamically-optimized guinea pig housing system that models natural, airborne, animal-to-animal Mtb transmission under biosafety level 3 (BSL-3) containment. Iterative engineering and particle transport experiments revealed that airflow is a critical determinant of transmission efficiency. Static housing and excessive unidirectional ventilation both eliminated transmission, whereas controlled, low-velocity airflow enabled aerosol particle retention and exposure of naïve animals. Under these optimized conditions, recipient guinea pigs converted their tuberculin skin tests above a defined positive threshold, developed Mtb-specific antibody responses, and exhibited pulmonary inflammation consistent with infection. These findings demonstrate that flow rates govern natural transmission of Mtb and provide a reproducible small-animal model for studying bacterial, host, and environmental factors that drive infectious spread. By reviving a century-old experimental paradigm with modern physics, engineering and immunologic tools, this work establishes a platform to dissect the mechanisms underlying airborne transmission of tuberculosis.

(Mtb) particles expelled from an infected individual are inhaled by a susceptible person. To study the adaptation of Mtb during transition between hosts, we developed a transmission simulation system (TSS) that combines controlled pathogen aerosolization and measurement of bioaerosol particle characteristics with in-flight sampling of Mtb and infection of mice by nose-only exposure. Using scattered-light spectrometry, we demonstrated that Mtb aerosol concentrations generated by the TSS better represented human cough than the aerosol concentrations produced by a full-body inhalation exposure system commonly used for Mtb infection of mice. Additionally, the TSS deposited clinically relevant low doses of Mtb into murine lungs with greater precision than the full-body inhalation exposure systems. The TSS revealed a linear correlation between Mtb inoculum concentration and pathogen deposition in murine lungs up to 200 colony-forming units. Higher inoculum concentrations led to a reduction in total particle number, which resulted in disproportionately lower pulmonary infection doses. Importantly, the particle size distributions of Mtb-laden aerosols produced by the TSS mirrored those of tuberculosis patient coughs, with 90% of culturable Mtb found in particles with aerodynamic diameters below 3.3 µm. In conclusion, the TSS represents a novel effective and precise translational platform enabling detailed biophysical and molecular studies of Mtb transmission. IMPORTANCE: (Mtb)-laden microdroplets of an infected individual are inhaled by a susceptible person. Historically, studies on Mtb transmission have focused mainly on epidemiology due to the technical challenges in replicating the transmission process effectively in a laboratory setting. In this study, we introduce a transmission simulation system (TSS) that integrates controlled Mtb aerosolization, biophysical aerosol particle measurements, in-flight Mtb sampling, and aerosol infection of mice. The TSS generated Mtb bioaerosol concentrations comparable to those produced by human coughs. These pathogen droplets were accurately deposited in mouse lungs at low Mtb doses relevant to human transmission. Notably, the distribution of Mtb among aerosol particles of various sizes closely mirrored that found in the coughs of tuberculosis patients. In summary, the TSS represents a novel tool for conducting molecular studies of Mtb transmission through the air.

The canonical susceptible–infected–recovered (SIR) epidemic model is ubiquitous in assessing severity to guide interventions. It is typically applied to hierarchically aggregated data from distinct sub-regions. The introduced heterogeneity can lead to significant errors in estimated epidemic severity. We develop three analytical methods to extract SIR parameters from data, focusing on the reproduction number <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" id="u1" overflow="scroll"> <mml:mstyle displaystyle="true" scriptlevel="0"> <mml:mrow> <mml:msub> <mml:mi>R</mml:mi> <mml:mrow> <mml:mn>0</mml:mn> </mml:mrow> </mml:msub> </mml:mrow> </mml:mstyle> </mml:math> that quantifies epidemic wave severity/strength. The estimation methods are applied to synthetically aggregated incidence data formulated by summing two independent SIR solutions of distinct <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" id="u2" overflow="scroll"> <mml:mstyle displaystyle="true" scriptlevel="0"> <mml:mrow> <mml:msub> <mml:mi>R</mml:mi> <mml:mrow> <mml:mn>0</mml:mn> </mml:mrow> </mml:msub> </mml:mrow> </mml:mstyle> </mml:math> and separated by an onset delay, i.e. temporal offset. When applying the SIR model, we find that <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" id="u3" overflow="scroll"> <mml:mstyle displaystyle="true" scriptlevel="0"> <mml:mrow> <mml:msub> <mml:mi>R</mml:mi> <mml:mrow> <mml:mn>0</mml:mn> </mml:mrow> </mml:msub> </mml:mrow> </mml:mstyle> </mml:math> estimates from the aggregated data can underestimate or overestimate the constituent epidemic waves’ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" id="u4" overflow="scroll"> <mml:msub> <mml:mi>R</mml:mi> <mml:mn>0</mml:mn> </mml:msub> </mml:math> even when the prediction appears to agree well with the incidence data, resulting in an erroneous unimodal epidemic dynamics. We find that for two epidemic waves, the stronger the trailing wave, the longer the temporal offset that maintains apparent erroneous unimodal aggregated data. In the special case of two equivalent epidemic strengths, however, the weaker the waves, the longer the offset that maintains apparent unimodal aggregated data. We provide sensitivity analyses with respect to noise perturbation of the data and illustrate our approach using historical influenza data.

Outbreaks are typically investigated using approaches that aim to identify place- and context-dependent causative factors. As the focus is on understanding the basis of a specific outbreak, the resulting narratives are rarely suitable for forecasting risk or developing generalizable predictive and preventative measures. This Perspective article proposes applying a case-control framework as an outbreak epidemiological study design to promote evidence-based decision-making for prevention and response to outbreaks. The approach involves identifying counterfactuals, with case-control comparisons drawn to test hypotheses about conditions that manifest outbreaks. First, a framework is described for iterative multidisciplinary interrogation to elucidate and identify minimally sufficient sets of factors that lead to disease outbreaks. Next, example case-control comparison frameworks are discussed, centered on pathogen(s), influential contributor(s), or landscape(s), illustrated with examples focused on pathogen transmission. Fefferman et al. propose applying a case-control framework as an outbreak epidemiological study design to promote evidence-based decision-making for prevention and response to outbreaks. They describe their framework and discuss case-control examples of how it can be applied.

(Mtb), a leading cause of death from infection, completes its life cycle entirely in humans except for transmission through the air. To begin to understand how Mtb survives aerosolization, we mimicked liquid and atmospheric conditions experienced by Mtb before and after exhalation using a model aerosol fluid (MAF) based on the water-soluble, lipidic, and cellular constituents of necrotic tuberculosis lesions. MAF induced drug tolerance in Mtb, remodeled its transcriptome, and protected Mtb from dying in microdroplets desiccating in air. Yet survival was not passive: Mtb appeared to rely on hundreds of genes to survive conditions associated with transmission. Essential genes subserving proteostasis offered most protection. A large number of conventionally nonessential genes appeared to contribute as well, including genes encoding proteins that resemble antidesiccants. The candidate transmission survival genome of Mtb may offer opportunities to reduce transmission of tuberculosis.

Abstract Mycobacterium tuberculosis (Mtb), a leading cause of death from infection, completes its life cycle entirely in humans except for transmission through the air. To begin to understand how Mtb survives aerosolization, we mimicked liquid and atmospheric conditions experienced by Mtb before and after exhalation using a model aerosol fluid (MAF) based on the water-soluble, lipidic and cellular constituents of necrotic tuberculosis lesions. MAF induced drug tolerance in Mtb, remodeled its transcriptome and protected Mtb from dying in microdroplets desiccating in air. Yet survival was not passive: Mtb appeared to rely on hundreds of genes to survive conditions associated with transmission. Essential genes subserving proteostasis offered most protection. A large number of conventionally nonessential genes appeared to contribute as well, including genes encoding proteins that resemble anti-desiccants. The candidate transmission survival genome of Mtb may offer opportunities to reduce transmission of tuberculosis. Significance Statement Mycobacterium tuberculosis (Mtb) travels from the lungs of one person through the air to the lungs of another and survives multiple stresses en route, including changes in temperature and in concentrations of oxygen, carbon dioxide, hydrogen ions, salts and organic solutes. Here we present a genetically tractable model of transmission to begin the identification of the transmission survival genome of Mtb. We devised a fluid that mimics TB lesions, found that it protects Mtb from transmission-related stresses, associated this with the structure of the droplets as they dry and their ability to retain water, and used it to query the potential contribution of each of Mtb’s genes to Mtb’s survival in models of three sequential stages of transmission.

Splashes from impacts of drops on liquid pools are ubiquitous and generate secondary droplets important for a range of applications in healthcare, agriculture and industry. The physics of splash continues to comprise central unresolved questions. Combining experiments and theory, here we study the sequence of topological changes from drop impact on a deep, inviscid liquid pool, with a focus on the regime of crown splash with developing air cavity below the interface and crown sheet above it. We develop coupled evolution equations for the cavity–crown system, leveraging asymptotic theory for the cavity and conservation laws for the crown. Using the key coupling of sheet and cavity, we derive similarity solutions for the sheet velocity and thickness profiles, and asymptotic prediction of the crown height evolution. Unlike the cavity whose expansion is opposed by gravitational effects, the axial crown rise is mostly opposed by surface tension effects. Moreover, both the maximum crown height and the time of its occurrence scale as ${\textit {We}}^{5/7}$ . We find our analytical results to be in good agreement with our experimental measurements. The cavity–crown coupling achieved enables us to obtain explicit estimates of the crown splash spatio-temporal unsteady dynamics, paving the way to deciphering ultimate splash fragmentation.

Fragmentation of a fluid body into droplets underlies many contamination and disease transmission processes where pathogens are transported in a liquid phase. An important class of such processes involves formation of a fluid ligament and its destabilization into droplets. Inertial detachment (Gilet &amp; Bourouiba, J. R. Soc. Interface , vol. 12, 2015, 20141092) is one of these modes: upon impact on a sufficiently compliant substrate, the substrate's motion can transfer its impulse to a contaminated sessile drop residing on it. The fragmentation of the sessile drop is efficient at producing contaminated ejected droplets with little dilution. Inertial detachment, particularly from substrates of intermediate wetting, is also interesting as a fundamental fragmentation process on its own merit, involving the asymmetric stretching of the sessile drop under impulsive axial forcing with one-sided pinning due to the substrate's intermediate wetting. Our experiments show that the radius, $R_{tip}$ , of the tip drop ejected become insensitive to the Bond number value for $Bo&gt;1$ . Here, $Bo$ quantifies the inertial effects via the relative axial impulsive acceleration compared with capillarity. The time, $t_{tip}$ , of tip-drop breakup is also insensitive to $Bo$ . Combining experiments, theory and validated numerics, we decipher the selection of $R_{tip}$ and its sensitivity to the surface-wetting and substrate foot dynamics. Using asymptotic theory in the large $Bo$ limit for which the thin-film/slender-jet approximations hold, we derive a reduced physical model that predicts $R_{tip}$ consistent with our experiments. Finally, we discuss how pathogen physical properties (e.g. wetting and buoyancy) within the sessile drop determine their distribution in the tip and secondary fragmentation droplets.

When discussing model ensembling or ensemble modeling, a term arises across numerous disciplines, what is meant by it can vary drastically. The very meaning of 'ensemble' - a collection together - conjures different ideas even within disciplines when approaching phenomena. For example, one might think of a set of descriptions of a phenomenon in the world, perhaps a time series or a snapshot of multivariate space, and perhaps that set is comprised of data-independent descriptions, or perhaps it is quite intentionally fit *to* data, or even a suite of data sets with a common theme or intention. Recently, ensemble models have appeared widely across applications, for disease forecasting, environmental suitability modeling, and more. In this piece, we present a typology of the scope of potential perspectives across disciplines to disambiguate terms, concepts, and processes associated with 'ensembles' and 'ensembling'. We do not provide an exhaustive review nor do we recommend that all disciplines must adopt a common suite of terms, but instead focus on facilitating communication, awareness, identification of gaps, and adoption of tools to avoid independent efforts to reinvent the wheel across disciplines. To anchor our discussion, we provide a Shiny App to contain the typology, with a living collection, or compendium, of example publications about ensembles.

The 2022 FIFA World Cup was the first major multi-continental sporting Mass Gathering Event (MGE) of the post COVID-19 era to allow foreign spectators. Such large-scale MGEs can potentially lead to outbreaks of infectious disease and contribute to the global dissemination of such pathogens. Here we adapt previous work and create a generalisable model framework for assessing the use of disease control strategies at such events, in terms of reducing infections and hospitalisations. This framework utilises a combination of meta-populations based on clusters of people and their vaccination status, Ordinary Differential Equation integration between fixed time events, and Latin Hypercube sampling. We use the FIFA 2022 World Cup as a case study for this framework (modelling each match as independent 7 day MGEs). Pre-travel screenings of visitors were found to have little effect in reducing COVID-19 infections and hospitalisations. With pre-match screenings of spectators and match staff being more effective. Rapid Antigen (RA) screenings 0.5 days before match day performed similarly to RT-PCR screenings 1.5 days before match day. Combinations of pre-travel and pre-match testing led to improvements. However, a policy of ensuring that all visitors had a COVID-19 vaccination (second or booster dose) within a few months before departure proved to be much more efficacious. The State of Qatar abandoned all COVID-19 related travel testing and vaccination requirements over the period of the World Cup. Our work suggests that the State of Qatar may have been correct in abandoning the pre-travel testing of visitors. However, there was a spike in COVID-19 cases and hospitalisations within Qatar over the World Cup. Given our findings and the spike in cases, we suggest a policy requiring visitors to have had a recent COVID-19 vaccination should have been in place to reduce cases and hospitalisations.

Indoor ventilation is underutilized for the control of exposure to infectious pathogens. Occupancy restrictions during the pandemic showed the acute need to control detailed airflow patterns, particularly in heavily occupied spaces, such as lecture halls or offices, and not just to focus on air changes. Displacement ventilation is increasingly considered a viable energy efficient approach. However, control of airflow patterns from displacement ventilation requires us to understand them first. The challenge in doing so is that, on the one hand, detailed numerical simulations – such as direct numerical simulations (DNSs) – enable the most accurate assessment of the flow, but they are computationally prohibitively costly, thus impractical. On the other hand, large eddy simulations (LES) use parametrizations instead of explicitly capturing small-scale flow processes critical to capturing the inhomogeneous mixing and fluid–boundary interactions. Moreover, their use for generalizable insights requires extensive validation against experiments or already validated gold-standard DNSs. In this study, we start to address this challenge by employing efficient monotonically integrated LES (MILES) to simulate airflows in large-scale geometries and benchmark against relevant gold-standard DNSs. We discuss the validity and limitations of MILES. Via its application to a lecture hall, we showcase its emerging potential as an assessment tool for indoor air mixing heterogeneity.

Purpose of Review: Preparing for pandemics requires a degree of interdisciplinary work that is challenging under the current paradigm. This review summarizes the challenges faced by the field of pandemic science and proposes how to address them. Recent Findings: The structure of current siloed systems of research organizations hinders effective interdisciplinary pandemic research. Moreover, effective pandemic preparedness requires stakeholders in public policy and health to interact and integrate new findings rapidly, relying on a robust, responsive, and productive research domain. Neither of these requirements are well supported under the current system. Summary: We propose a new paradigm for pandemic preparedness wherein interdisciplinary research and close collaboration with public policy and health practitioners can improve our ability to prevent, detect, and treat pandemics through tighter integration among domains, rapid and accurate integration, and translation of science to public policy, outreach and education, and improved venues and incentives for sustainable and robust interdisciplinary work.

Investigations of infectious disease outbreaks often focus on identifying place- and context-dependent factors responsible for emergence and spread, resulting in phenomenological narratives ill-suited to developing generalizable predictive and preventive measures. We contend that case-control hypothesis testing is a more powerful framework for epidemiological investigation. The approach, widely used in medical research, involves identifying counterfactuals, with case-control comparisons drawn to test hypotheses about the conditions that manifest outbreaks. Here we outline the merits of applying a case-control framework as epidemiological study design. We first describe a framework for iterative multidisciplinary interrogation to discover minimally sufficient sets of factors that can lead to disease outbreaks. We then lay out how case-control comparisons can respectively center on pathogen(s), factor(s), or landscape(s) with vignettes focusing on pathogen transmission. Finally, we consider how adopting case-control approaches can promote evidence-based decision making for responding to and preventing outbreaks.

Shear instabilities at the interface of two fluids, such as classical Kelvin-Helmholtz instability (KHI), is the precursor of interface destabilization, leading to fluid fragmentation critical in a wide range of applications. While many insights into such instabilities are derived for steady background forcing flow, unsteady impulse flows are ubiquitous in environmental and physiological processes. Yet, little is understood on how unsteadiness shapes the initial interface amplification necessary for the onset of its topological change enabling subsequent fragmentation. In this combined theoretical, numerical and experimental study, we focus on an air-on-liquid interface exposed to canonical unsteady shear flow profiles. Evolution of the perturbed interface is formulated theoretically as an impulse-driven initial value problem using both linearized potential flow and nonlinear boundary integral methods. We show that the unsteady airflow forcing can amplify the interface's inherent gravity-capillary wave, up to wave-breaking transition, even if the configuration is classically KH stable. For impulses much shorter than the gravity-capillary wave period, it is the cumulative action, akin to total energy, that determines amplification, independent of the details of the impulse profile. However, for longer impulses, the details of the impulse profile become important. In this limit, akin to a resonance, it is the entangled history of the interaction of the forcing, i.e. the impulse, that changes rapidly in amplitude, and the response of the oscillating interface that matters. The insights gained are discussed and experimentally illustrated in the context of interface distortion and destabilization relevant for upper respiratory mucosalivary fluid fragmentation in violent exhalations.

PURPOSE The resident deaths among Long Term Care Home (LTCH) accounted for more than 65% of total deaths in the province of Ontario, Canada, during March 29 to June 3, 2020, yet not all LTCHs were severely affected. METHODS We carried out a retrospective cohort study, with case control for questions for which data allowed, with LTCH COVID-19 databases obtained from Ontario's Ministry of Long Term Care. We performed a combined temporal and spatial data analysis of COVID-19 cases and deaths among LTCH residents, identified trends, contributing factors, and early markers of LTCH outbreak severity. RESULTS Our analysis shows that for-profit LTCHs had higher death-to-bed ratio, also with an average rate of increase of death-to-bed ratio higher for for-profit homes than other types of management. We find from uni- and multi-variable analyses (linear and nonlinear) that staff infection has the strongest association with death-to-bed ratio from among the descriptor variables considered, reflecting the risk of the disease in the health region/community. We also identify a delay of up to 8 days between the trends in fatalities among individuals outside LTCHs and that of LTCH residents. We did find an association between policy change to single LTCH/staff and reduction in weekly LTCH resident death, albeit with an expected time delay of about 7-10 days. CONCLUSIONS The association between the risk of COVID-19 in the health region and the deaths among LTCH residents, and the delay between fatality among individuals residing outside and inside LTCHs suggests that fatality in a health region could be a predictor of outbreak in LTCHs within the same health region.

We present the results of a combined experimental and theoretical investigation of sheet evolution, expansion and retraction, under unsteady fragmentation upon drop impact on a surface of comparable size to that of the drop. We quantify and model the effect of the continuous time-varying – unsteady – shedding of droplets from the sheet via its bounding rim. We present and validate especially developed advanced image processing algorithms that quantify, with high accuracy, the key quantities involved in such unsteady fragmentation, from sheet, to rim, to ligaments, to droplet properties. With these high precision measurements, we show the important effect of continuous unsteady droplet shedding on the sheet dynamics. We combine experiments and theory to derive and validate governing equations of the sheet that incorporate such continuous shedding – associated with continuous loss of momentum and mass – from unsteady fragmentation. Combining this theory with the universal unsteady rim dynamics discovered in Wang et al. ( Phys. Rev. Lett. , vol. 120, 2018, 204503), we show that the governing equation of the sheet can be reduced to a continuous-shedding, non-Galilean Taylor–Culick law, from which we deduce new analytical expressions for the time evolution of the sheet radius. We show the robustness of the predictions to changes of fluid properties, including surface tension and moderate fluid viscosity and elasticity, including use of physiological mucosalivary fluid. We also reconcile prior literature's inconsistent experimental results on the sheet dynamics upon drop impact.

Abstract The 2022 FIFA World Cup was the first major multi-continental sporting Mass Gathering Event (MGE) of the post COVID-19 era to allow foreign spectators. Such large-scale MGEs can potentially lead to outbreaks of infectious disease and contribute to the global dissemination of such pathogens. Here we adapt previous work and create a generalisable model framework for assessing the use of disease control strategies at such events, in terms of reducing infections and hospitalisations. This framework utilises a combination of meta-populations based on clusters of people and their vaccination status, Ordinary Differential Equation integration between fixed time events, and Latin Hypercube sampling. We use the FIFA 2022 World Cup as a case study for this framework. Pre-travel screenings of visitors were found to have little effect in reducing COVID-19 infections and hospitalisations. With pre-match screenings of spectators and match staff being more effective. Rapid Antigen (RA) screenings 0.5 days before match day outperformed RT-PCR screenings 1.5 days before match day. A combination of pre-travel RT-PCR and pre-match RA testing proved to be the most successful screening-based regime. However, a policy of ensuring that all visitors had a COVID-19 vaccination (second or booster dose) within a few months before departure proved to be much more efficacious. The State of Qatar abandoned all COVID-19 related travel testing and vaccination requirements over the period of the World Cup. Our work suggests that the State of Qatar may have been correct in abandoning the pre-travel testing of visitors. However, there was a spike in COVID-19 cases and hospitalisations within Qatar over the World Cup. The research outlined here suggests a policy requiring visitors to have had a recent COVID-19 vaccination may have prevented the increase in COVID-19 cases and hospitalisations during the world cup. Author summary Mass Gathering Events (MGEs) can potentially lead to outbreaks of infectious disease and facilitate the dissemination of such pathogens. We have adapted previous work to create a framework for simulating disease transmission and mitigation at such MGEs. We use the 2022 FIFA World Cup as a test case for this framework. A policy of Pre-travel screenings of visitors was found to have little effect in reducing COVID-19 cases and hospitalisations. Pre-match screenings of spectators and match staff was found to be more effective. The most effective policy was to ensure that all visitors had a COVID-19 vaccination (second or booster dose) within a few months before departure. Qatar abandoned all COVID-19 related travel testing and vaccination requirements over the period of the World Cup. Our work suggests that the State of Qatar may have been correct in abandoning the pre-travel testing of visitors. However, there was a spike in COVID-19 cases and hospitalisations within Qatar over the World Cup. Given our findings, we suggest a policy requiring visitors to have had a recent COVID-19 vaccination may have prevented the increase in COVID-19 cases and hospitalisations during the world cup.