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Swetaprovo Chaudhuri Person1 #717032 Swetaprovo is an Associate Professor in the Institute for Aerospace Studies in the Faculty of Applied Science and Engineering at the University of Toronto. | - Professor Chaudhuri is an expert in turbulent reacting flows and propulsion and known for his original contributions on turbulent flame stabilization, propagation and structure using experiments, theory and computations. After his Bachelors from Jadavpur University (2006), he earned his PhD from University of Connecticut in 2010.
- He worked at Princeton University as a research staff (2010-13) and then at Indian Institute of Science, as an Assistant/Associate Professor. In 2019, he joined University of Toronto Institute for Aerospace Studies as a tenured Associate Professor. Prof. Chaudhuri has authored/co-authored over hundred articles in top journals, conferences and books, and has been honored by ASME, UConn, INSA, IAS, UTIAS. He is an elected Associate Fellow of AIAA and a member of its Propellants and Combustion technical committee.
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+Citations (11) - CitationsAjouter une citationList by: CiterankMapLink[2] Modeling the role of respiratory droplets in Covid-19 type pandemics
En citant: Swetaprovo Chaudhuri, Saptarshi Basu, Prasenjit Kabi, Vishnu R. Unni, Abhishek Saha Publication date: 30 June 2020 Publication info: Physics of Fluids 32, 063309 (2020) Cité par: David Price 12:10 PM 23 January 2024 GMT Citerank: (2) 701037MfPH – Publications144B5ACA0, 704045Covid-19859FDEF6 URL: DOI: https://doi.org/10.1063/5.0015984
| Extrait - [Physics of Fluids, 30 June 2020]
In this paper, we develop a first principles model that connects respiratory droplet physics with the evolution of a pandemic such as the ongoing Covid-19. The model has two parts. First, we model the growth rate of the infected population based on a reaction mechanism. The advantage of modeling the pandemic using the reaction mechanism is that the rate constants have sound physical interpretation. The infection rate constant is derived using collision rate theory and shown to be a function of the respiratory droplet lifetime. In the second part, we have emulated the respiratory droplets responsible for disease transmission as salt solution droplets and computed their evaporation time, accounting for droplet cooling, heat and mass transfer, and finally, crystallization of the dissolved salt. The model output favourably compares with the experimentally obtained evaporation characteristics of levitated droplets of pure water and salt solution, respectively, ensuring fidelity of the model. The droplet evaporation/desiccation time is, indeed, dependent on ambient temperature and is also a strong function of relative humidity. The multi-scale model thus developed and the firm theoretical underpinning that connects the two scales—macro-scale pandemic dynamics and micro-scale droplet physics—thus could emerge as a powerful tool in elucidating the role of environmental factors on infection spread through respiratory droplets. |
Link[4] Analyzing the dominant SARS-CoV-2 transmission routes toward an ab initio disease spread model
En citant: Swetaprovo Chaudhuri, Saptarshi Basu, Abhishek Saha Publication date: 4 December 2020 Publication info: Physics of Fluids 32, 123306 (2020) Cité par: David Price 7:36 PM 24 January 2024 GMT Citerank: (2) 701037MfPH – Publications144B5ACA0, 704045Covid-19859FDEF6 URL: DOI: https://doi.org/10.1063/5.0034032
| Extrait - [Physics of Fluids, 4 December 2020]
Identifying the relative importance of the different transmission routes of the SARS-CoV-2 virus is an urgent research priority. To that end, the different transmission routes and their role in determining the evolution of the Covid-19 pandemic are analyzed in this work. The probability of infection caused by inhaling virus-laden droplets (initial ejection diameters between 0.5 µm and 750 µm, therefore including both airborne and ballistic droplets) and the corresponding desiccated nuclei that mostly encapsulate the virions post droplet evaporation are individually calculated. At typical, air-conditioned yet quiescent indoor space, for average viral loading, cough droplets of initial diameter between 10 µm and 50 µm are found to have the highest infection probability. However, by the time they are inhaled, the diameters reduce to about 1/6th of their initial diameters. While the initially near unity infection probability due to droplets rapidly decays within the first 25 s, the small yet persistent infection probability of desiccated nuclei decays appreciably only by O (1000s) , assuming that the virus sustains equally well within the dried droplet nuclei as in the droplets. Combined with molecular collision theory adapted to calculate the frequency of contact between the susceptible population and the droplet/nuclei cloud, infection rate constants are derived ab initio, leading to a susceptible-exposed-infectious-recovered-deceased model applicable for any respiratory event–vector combination. The viral load, minimum infectious dose, sensitivity of the virus half-life to the phase of its vector, and dilution of the respiratory jet/puff by the entraining air are shown to mechanistically determine specific physical modes of transmission and variation in the basic reproduction number from first-principles calculations. |
Link[5] Effect of wetness on penetration dynamics of droplets impacted on facemasks
En citant: Abhishek Saha, Sombuddha Bagchi, Saptarshi Basu, Swetaprovo Chaudhuri Publication date: 21 November 2021 Publication info: 74th Annual Meeting of the APS Division of Fluid Dynamics, Volume 66, Number 17 Cité par: David Price 7:54 PM 24 January 2024 GMT Citerank: (3) 701037MfPH – Publications144B5ACA0, 704045Covid-19859FDEF6, 715328Nonpharmaceutical Interventions (NPIs)859FDEF6 URL:
| Extrait - [APS Division of Fluid Dynamics, 21 November 2021]
Properly designed facemasks can limit the spread of ballistic droplets and aerosol particles coming out of oral and nasal cavities during respiratory events, such as sneezing, coughing, singing, talking etc. Furthermore, it can also protect the user from inhaling small droplets, droplet nuclei, or aerosol particles. Thus, proper usage of facemasks can prevent the transmission of many diseases, including Covid19, influenza, measles, and the common cold. Although N95 masks are particularly designed to provide the best protection, various types of facemask became popular during the Covid19 pandemic due to a shortage of supply and high demand. In our recent study (Sharma et al. Sc. Adv. (2021) 7, eabf0452), we reported the fate of a respiratory droplet impacting on a dry facemask to show that larger droplets can penetrate the mask layers and undergo secondary atomizations leading to multiple smaller droplets. In this work, we focus on the effect of the wetness of the mask matrix on this atomization process. Indeed, due to the condensation process, longtime use renders the masks wet, and hence, its influence on the efficacy in blocking the droplet is worth investigating. We will present a regime map to show the penetration probability with impact velocity and wetness for two different types of masks. We will also present a scaling argument to explain the observed effects of wetness on penetration. |
Link[6] An exposition of facemask efficacy against large size cough droplets
En citant: Shubham Sharma, Roven Pinto, Abhishek Saha, Swetaprovo Chaudhuri, Saptarshi Basu Publication date: 21 November 2021 Publication info: 74th Annual Meeting of the APS Division of Fluid Dynamics, Volume 66, Number 17, Sunday–Tuesday, November 21–23, 2021 Cité par: David Price 4:58 PM 25 January 2024 GMT Citerank: (3) 701037MfPH – Publications144B5ACA0, 704045Covid-19859FDEF6, 715328Nonpharmaceutical Interventions (NPIs)859FDEF6 URL: | Extrait - [74th Annual Meeting of the APS Division of Fluid Dynamics, 21 November 2021]
The usage of facemasks has been ubiquitously recommended worldwide as a physical barrier to the ejected droplet during respiratory events. This is an effective strategy for restricting various droplet-based disease transmission, as in the case of COVID-19. Although the N95 facemask has high efficacy against respiratory droplets, its accessibility/affordability for the general population is still deprived. As a possible solution, using a makeshift facemask (surgical or cotton facemasks) is generally advised by policymakers. Although such endorsement could be economical and accessible, quantitative analysis on the effectiveness of such facemasks is still lacking. Using a large-sized surrogate cough droplet, we identified an additional route of disease transmission, which involves atomization of large-sized cough droplets into numerous daughter droplets. It is shown that most of such atomized droplets are of sizes which is critical for aerosolization1. This suggested that the amount of aerosol generated (thereby the risk of infection) through this mechanism is higher than the earlier predictions based on mask filtration efficiencies alone. A scaling argument based on the energy balance of impact dynamics was obtained and verified using experiments to identify a criterion for droplet penetration through a mask layer. The parametric analysis was also carried, which involves droplet impact velocities (corresponding to different respiratory events), impact angles (corresponding to different mask orientations), mask fabrics (surgical and cotton facemasks), and different washing cycles. The obtained results are discussed in detail, and a recommendation of the most suitable fabric for making homemade facemasks is presented. |
Link[7] On secondary atomization and blockage of surrogate cough droplets in single- and multilayer face masks
En citant: Shubham Sharma, Roven Pinto, Abhishek Saha, Swetaprovo Chaudhuri, Saptarshi Basu Publication date: 5 March 2021 Publication info: Science Advances, 7 (10), eabf0452 Cité par: David Price 8:43 PM 25 January 2024 GMT Citerank: (3) 701037MfPH – Publications144B5ACA0, 704045Covid-19859FDEF6, 715328Nonpharmaceutical Interventions (NPIs)859FDEF6 URL: DOI: https://doi.org/10.1126/sciadv.abf0452
| Extrait - [Science Advances, 5 March 2021]
Face masks prevent transmission of infectious respiratory diseases by blocking large droplets and aerosols during exhalation or inhalation. While three-layer masks are generally advised, many commonly available or makeshift masks contain single or double layers. Using carefully designed experiments involving high-speed imaging along with physics-based analysis, we show that high-momentum, large-sized (>250 micrometer) surrogate cough droplets can penetrate single- or double-layer mask material to a significant extent. The penetrated droplets can atomize into numerous much smaller (<100 micrometer) droplets, which could remain airborne for a significant time. The possibility of secondary atomization of high-momentum cough droplets by hydrodynamic focusing and extrusion through the microscale pores in the fibrous network of the single/double-layer mask material needs to be considered in determining mask efficacy. Three-layer masks can effectively block these droplets and thus could be ubiquitously used as a key tool against COVID-19 or similar respiratory diseases. |
Link[8] An opinion on the multiscale nature of Covid-19 type disease spread
En citant: Swetaprovo Chaudhuri, Abhishek Saha, Saptarshi Basu Publication date: 1 May 2021 Publication info: Current Opinion in Colloid & Interface Science, 01 May 2021, 54:101462, PMID: 33967585 PMCID: PMC8088079 Cité par: David Price 11:34 PM 25 January 2024 GMT Citerank: (3) 701037MfPH – Publications144B5ACA0, 704045Covid-19859FDEF6, 715328Nonpharmaceutical Interventions (NPIs)859FDEF6 URL: DOI: https://doi.org/10.1016/j.cocis.2021.101462
| Extrait - [Current Opinion in Colloid & Interface Science, 1 May 2021]
Recognizing the multiscale, interdisciplinary nature of the Covid-19 transmission dynamics, we discuss some recent developments concerning an attempt to construct a disease spread model from the flow physics of infectious droplets and aerosols and the frequency of contact between susceptible individuals with the infectious aerosol cloud. Such an approach begins with the exhalation event–specific, respiratory droplet size distribution (both airborne/aerosolized and ballistic droplets), followed by tracking its evolution in the exhaled air to estimate the probability of infection and the rate constants of the disease spread model. The basic formulations and structure of submodels, experiments involved to validate those submodels, are discussed. Finally, in the context of preventive measures, respiratory droplet–face mask interactions are described. |
Link[9] Two-dimensional mathematical framework for evaporation dynamics of respiratory droplets
En citant: Sreeparna Majee, Abhishek Saha, Swetaprovo Chaudhuri, Dipshikha Chakravortty, Saptarshi Basu Publication date: 1 October 2021 Publication info: Physics of Fluids, 33, 103302 (2021) Cité par: David Price 11:40 PM 25 January 2024 GMT Citerank: (2) 701037MfPH – Publications144B5ACA0, 704045Covid-19859FDEF6 URL: DOI: https://doi.org/10.1063/5.0064635
| Extrait - [Physics of Fluids, 1 October 2021]
In majority of pandemics in human history, respiratory bio-aerosol is the most common route of transmission of diseases. These tiny droplets ejected through mouth and nose from an infected person during exhalation process like coughing, sneezing, speaking, and breathing consist of pathogens and a complex mixture of volatile and nonvolatile substances. A cloud of droplets ejected in such an event gets transmitted in the air, causing a series of coupled thermo-physical processes. Contemplating an individual airborne droplet in the cloud, boundary layers and wakes develop due to relative motion between the droplet and the ambient air. The complex phenomenon of the droplet's dynamics, such as shear-driven internal circulation of the liquid phase and Stefan flow due to vaporization or condensation, comes into effect. In this study, we present a mathematical description of the coupled subprocesses, including droplet aerodynamics, heat, and mass transfer, which were identified and subsequently solved. The presented two-dimensional model gives a complete analysis encompassing the gas phase coupled with the liquid phase responsible for the airborne droplet kinetics in the ambient environment. The transient inhomogeneity of temperature and concentration distribution in the liquid phase caused due to the convective and diffusive transports are captured in the 2D model. The evaporation time and distance traveled by droplets prior to nuclei or aerosol formation are computed for major geographical locations around the globe for nominal-windy conditions. The model presented can be used for determining the evaporation timescale of any viral or bacterial laden respiratory droplets across any geographical location. |
Link[10] Analysis of overdispersion in airborne transmission of COVID-19
En citant: Swetaprovo Chaudhuri, Prasad Kasibhatla, Arnab Mukherjee, William Pan, Glenn Morrison, Sharmistha Mishra, Vijaya Kumar Murty Publication date: 31 May 2022 Publication info: Physics of Fluids 34, 051914 (2022) Cité par: David Price 0:05 AM 26 January 2024 GMT Citerank: (3) 679893Kumar MurtyProfessor Kumar Murty is in the Department of Mathematics at the University of Toronto. His research fields are Analytic Number Theory, Algebraic Number Theory, Arithmetic Algebraic Geometry and Information Security. He is the founder of the GANITA lab, co-founder of Prata Technologies and PerfectCloud. His interest in mathematics ranges from the pure study of the subject to its applications in data and information security.10019D3ABAB, 701037MfPH – Publications144B5ACA0, 704045Covid-19859FDEF6 URL: DOI: https://doi.org/10.1063/5.0089347
| Extrait - [Physics of Fluids, 31 May 2022]
Superspreading events and overdispersion are hallmarks of the COVID-19 pandemic. However, the specific roles and influence of established viral and physical factors related to the mechanisms of transmission, on overdispersion, remain unresolved. We, therefore, conducted mechanistic modeling of SARS-CoV-2 point-source transmission by infectious aerosols using real-world occupancy data from more than 100 000 social contact settings in ten US metropolises. We found that 80% of secondary infections are predicted to arise from approximately 4% of index cases, which show up as a stretched tail in the probability density function of secondary infections per infectious case. Individual-level variability in viral load emerges as the dominant driver of overdispersion, followed by occupancy. We then derived an analytical function, which replicates the simulated overdispersion, and with which we demonstrate the effectiveness of potential mitigation strategies. Our analysis, connecting the mechanistic understanding of SARS-CoV-2 transmission by aerosols with observed large-scale epidemiological characteristics of COVID-19 outbreaks, adds an important dimension to the mounting body of evidence with regard to airborne transmission of SARS-CoV-2 and thereby emerges as a powerful tool toward assessing the probability of outbreaks and the potential impact of mitigation strategies on large scale disease dynamics. |
Link[11] Analysing the distribution of SARS-CoV-2 infections in schools: integrating model predictions with real world observations
En citant: Arnab Mukherjee, Sharmistha Mishra, Vijay Kumar Murty, Swetaprovo Chaudhuri Publication date: 21 December 2023 Publication info: bioRxiv, 21 December 2023 Cité par: David Price 0:22 AM 26 January 2024 GMT Citerank: (6) 679880Sharmistha MishraSharmistha Mishra is an infectious disease physician and mathematical modeler and holds a Tier 2 Canadian Research Chair in Mathematical Modeling and Program Science.10019D3ABAB, 679893Kumar MurtyProfessor Kumar Murty is in the Department of Mathematics at the University of Toronto. His research fields are Analytic Number Theory, Algebraic Number Theory, Arithmetic Algebraic Geometry and Information Security. He is the founder of the GANITA lab, co-founder of Prata Technologies and PerfectCloud. His interest in mathematics ranges from the pure study of the subject to its applications in data and information security.10019D3ABAB, 701037MfPH – Publications144B5ACA0, 704045Covid-19859FDEF6, 715328Nonpharmaceutical Interventions (NPIs)859FDEF6, 715617Schools859FDEF6 URL: DOI: https://doi.org/10.1101/2023.12.21.572736; t
| Extrait - [bioRxiv, 21 December 2023]
School closures were used as strategies to mitigate transmission in the COVID-19 pandemic. Understanding the nature of SARS-CoV-2 outbreaks and the distribution of infections in classrooms could help inform targeted or ‘precision’ preventive measures and outbreak management in schools, in response to future pandemics. In this work, we derive an analytical model of Probability Density Function (PDF) of SARS-CoV-2 secondary infections and compare the model with infection data from all public schools in Ontario, Canada between September-December, 2021. The model accounts for major sources of variability in airborne transmission like viral load and dose-response (i.e., the human body’s response to pathogen exposure), air change rate, room dimension, and classroom occupancy. Comparisons between reported cases and the modeled PDF demonstrated the intrinsic overdispersed nature of the real-world and modeled distributions, but uncovered deviations stemming from an assumption of homogeneous spread within a classroom. The inclusion of near-field transmission effects resolved the discrepancy with improved quantitative agreement between the data and modeled distributions. This study provides a practical tool for predicting the size of outbreaks from one index infection, in closed spaces such as schools, and could be applied to inform more focused mitigation measures. |
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