Amid the ongoing COVID‐19 pandemic, public health authorities and the general population are striving to achieve a balance between safety and normalcy. Ever changing conditions call for the development of theory and simulation tools to finely describe multiple strata of society while supporting the evaluation of “what‐if” scenarios. Particularly important is to assess the effectiveness of potential testing approaches and vaccination strategies. Here, an agent‐based modeling platform is proposed to simulate the spreading of COVID‐19 in small towns and cities, with a single‐individual resolution. The platform is validated on real data from New Rochelle, NY—one of the first outbreaks registered in the United States. Supported by expert knowledge and informed by reported data, the model incorporates detailed elements of the spreading within a statistically realistic population. Along with pertinent functionality such as testing, treatment, and vaccination options, the model accounts for the burden of other illnesses with symptoms similar to COVID‐19. Unique to the model is the possibility to explore different testing approaches—in hospitals or drive‐through facilities—and vaccination strategies that could prioritize vulnerable groups. Decision‐making by public authorities could benefit from the model, for its fine‐grain resolution, open‐source nature, and wide range of features.
As COVID-19 vaccine is being rolled out in the US, public health authorities are gradually reopening the economy. To date, there is no consensus on a common approach among local authorities. Here, a high-resolution agent-based model is proposed to examine the interplay between the increased immunity afforded by the vaccine roll-out and the transmission risks associated with reopening efforts. The model faithfully reproduces the demographics, spatial layout, and mobility patterns of the town of New Rochelle, NY -representative of the urban fabric of the US. Model predictions warrant caution in the reopening under the current rate at which people are being vaccinated, whereby increasing access to social gatherings in leisure locations and households at a 1% daily rate can lead to a 28% increase in the fatality rate within the next three months. The vaccine roll-out plays a crucial role on the safety of reopening: doubling the current vaccination rate is predicted to be sufficient for safe, rapid reopening.
The potential waning of the vaccination immunity to COVID-19 could pose threats to public health, as it is tenable that the timing of such waning would synchronize with the near-complete restoration of normalcy. Should also testing be relaxed, a resurgent COVID-19 wave in winter 2021/2022 might be witnessed. In response to this risk, an additional vaccine dose, the booster shot, is being administered worldwide. A projected study with an outlook of 6 months explores the interplay between the rate at which boosters are distributed and the extent to which testing practices are implemented, using a highly granular agent-based model tuned on a medium-sized US town. Theoretical projections indicate that the administration of boosters at the rate at which the vaccine is currently administered could yield a severe resurgence of the pandemic. Projections suggest that the peak levels of mid-spring 2021 in the vaccination rate may prevent such a scenario to occur, although exact agreement between observations and projections should not be expected due to the continuously evolving nature of the pandemic. This study highlights the importance of testing, especially to detect asymptomatic individuals in the near future, as the release of the booster reaches full speed.
Ionic polymer-metal composites (IPMCs) constitute a promising class of soft, active materials with potentially ubiquitous use in science and engineering. Realizing the full potential of IPMCs calls for a deeper understanding of the mechanisms underpinning their most intriguing characteristics: the ability to deform under an electric field and the generation of a voltage upon mechanical deformation. These behaviours are tightly linked to physical phenomena at the level of atoms, including rearrangements of ions and molecules, along with the formation of sub-nanometre thick double layers on the surface of the metal electrodes. Several continuum theories have been developed to describe these phenomena, but their experimental and theoretical validation remains incomplete. IPMC modelling at the atomistic scale could beget valuable support for these efforts, by affording granular analysis of individual atoms. Here, we present a simplified atomistic model of IPMCs based on classical molecular dynamics. The three-dimensional IPMC membrane is constrained by two smooth walls, a simplified analogue of metal electrodes, impermeable only to counterions. The electric field is applied as an additional force acting on all the atoms. We demonstrate the feasibility of simulating counterions’ migration and pile-up upon the application of an electric field, similar to experimental observations. By analysing the spatial configuration of atoms and stress distribution, we identify two mechanisms for stress generation. The presented model offers new insight into the physical underpinnings of actuation and sensing in IPMCs. This article is part of the theme issue ‘Progress in mesoscale methods for fluid dynamics simulation’.
Obstruction of fluid flow by stationary bubbles in a microchannel hemodialyzer decreases filtration performance and increases damage to blood cells through flow maldistribution. A polyethylene oxide (PEO)-polybutadiene (PB)-polyethylene oxide surface modification, previously shown to reduce protein fouling and water/air contact angle in polycarbonate microchannel hemodialyzers, can improve microchannel wettability and may reduce bubble stagnation by lessening the resistive forces that compete with fluid flow. In this study, the effect of the PEO-PB-PEO coating on bubble retention in a microchannel array was investigated. Polycarbonate microchannel surfaces were coated with PEO-PB-PEO triblock polymer via radiolytic grafting. Channel obstruction was measured for coated and uncoated microchannels after injecting a short stream of air bubbles into the device under average nominal water velocities of 0.9 to 7.2 cm/s in the channels. The presence of the PEO coating reduced obstruction of microchannels by stationary bubbles within the range of 1.8 to 3.6 cm/s, average nominal velocity. Numerical simulations based on the lattice Boltzmann method indicate that beneficial effects may be due to the maintenance of a lubricating, thin liquid film around the bubble. The determined effective range of the PEO coating for bubble management serves as an important design constraint. These findings serve to validate the multiutility of the PEO-PB-PEO coating (bubble lubrication, biocompatibility, and therapeutic loading). © 2015 Wiley Periodicals, Inc. J Biomed Mater Res Part B: Appl Biomater, 104B: 941-948, 2016.
We present a method for solving the Boltzmann transport equation (BTE) for phonons by modifying the neutron transport code Rattlesnake which provides a numerically efficient method for solving the BTE in its self-adjoint angular flux (SAAF) form. Using this approach, we have computed the reduction in thermal conductivity of uranium dioxide (UO2) due to the presence of a nanoscale xenon bubble across a range of temperatures. For these simulations, the values of group velocity and phonon mean free path in the UO2 were determined from a combination of experimental heat conduction data and first principles calculations. The same properties for the Xe under the high pressure conditions in the nanoscale bubble were computed using classical molecular dynamics (MD). We compare our approach to the other modern phonon transport calculations, and discuss the benefits of this multiscale approach for thermal conductivity in nuclear fuels under irradiation.
The ongoing pandemic is laying bare dramatic differences in the spread of COVID-19 across seemingly similar urban environments. Identifying the urban determinants that underlie these differences is an open research question, which can contribute to more epidemiologically resilient cities, optimized testing and detection strategies, and effective immunization efforts. Here, we perform a computational analysis of COVID-19 spread in three cities of similar size in New York State (Colonie, New Rochelle, and Utica) aiming to isolate urban determinants of infections and deaths. We develop detailed digital representations of the cities and simulate COVID-19 spread using a complex agent-based model, taking into account differences in spatial layout, mobility, demographics, and occupational structure of the population. By critically comparing pandemic outcomes across the three cities under equivalent initial conditions, we provide compelling evidence in favor of the central role of hospitals. Specifically, with highly efficacious testing and detection, the number and capacity of hospitals, as well as the extent of vaccination of hospital employees are key determinants of COVID-19 spread. The modulating role of these determinants is reduced at lower efficacy of testing and detection, so that the pandemic outcome becomes equivalent across the three cities. Electronic supplementary material The online version of this article (10.1007/s11524-022-00623-9) contains supplementary material, which is available to authorized users.
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