How adherence to public health measures shapes epidemic spreading: A temporal network model

The COVID-19 pandemic has laid bare the importance of non-pharmaceutical interventions in the containment of airborne infectious diseases. Social distancing and mask-wearing have been found to contain COVID-19 spreading across a number of observational studies, but a precise understanding of their combined effectiveness is lacking. An underdeveloped area of research entails the quantification of the specific role of each of these measures when they are differentially adopted by the population. Pursuing this research allows for answering several pressing questions like: how many people should follow public health measures for them to be effective for everybody? Is it sufficient to practice social distancing only or just wear a mask? Here, we make a first step in this direction, by establishing a susceptible-exposed-infected-removed epidemic model on a temporal network, evolving according to the activity-driven paradigm. Through analytical and numerical efforts, we study epidemic spreading as a function of the proportion of the population following public health measures, the extent of social distancing, and the efficacy of masks in protecting the wearer and others. Our model demonstrates that social distancing and mask-wearing can be effective in preventing COVID-19 outbreaks if adherence to both measures involves a substantial fraction of the population

High-Resolution Agent-Based Modeling of COVID-19 Spreading in a Small Town

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

Emission lines of Fe XI in the 257--407 A wavelength region observed in solar spectra from EIS/Hinode and SERTS

Theoretical emission-line ratios involving Fe XI transitions in the 257-407 A wavelength range are derived using fully relativistic calculations of radiative rates and electron impact excitation cross sections. These are subsequently compared with both long wavelength channel Extreme-Ultraviolet Imaging Spectrometer (EIS) spectra from the Hinode satellite (covering 245-291 A), and first-order observations (235-449 A) obtained by the Solar Extreme-ultraviolet Research Telescope and Spectrograph (SERTS). The 266.39, 266.60 and 276.36 A lines of Fe XI are detected in two EIS spectra, confirming earlier identifications of these features, and 276.36 A is found to provide an electron density diagnostic when ratioed against the 257.55 A transition. Agreement between theory and observation is found to be generally good for the SERTS data sets, with discrepancies normally being due to known line blends, while the 257.55 A feature is detected for the first time in SERTS spectra. The most useful Fe XI electron density diagnostic is found to be the 308.54/352.67 intensity ratio, which varies by a factor of 8.4 between N_e = 10^8 and 10^11 cm^-3, while showing little temperature sensitivity. However, the 349.04/352.67 ratio potentially provides a superior diagnostic, as it involves lines which are closer in wavelength, and varies by a factor of 14.7 between N_e = 10^8 and 10^11 cm^-3. Unfortunately, the 349.04 A line is relatively weak, and also blended with the second-order Fe X 174.52 A feature, unless the first-order instrument response is enhanced.Comment: 9 pages, 5 figures, 13 tables; MNRAS in pres

A Cellular Potts Model simulating cell migration on and in matrix environments

Cell migration on and through extracellular matrix plays a critical role in a wide variety of physiological and pathological phenomena, and in scaffold-based tissue engineering. Migration is regulated by a number of extracellular matrix- or cell-derived biophysical parameters, such as matrix fiber orientation, gap size, and elasticity, or cell deformation, proteolysis, and adhesion. We here present an extended Cellular Potts Model (CPM) able to qualitatively and quantitatively describe cell migratory phenotype on both two-dimensional substrates and within three-dimensional environments, in a close comparison with experimental evidence. As distinct features of our approach, the cells are represented by compartmentalized discrete objects, differentiated in the nucleus and in the cytosolic region, while the extracellular matrix is composed of a fibrous mesh and of a homogeneous fluid. Our model provides a strong correlation of the directionality of migration with the topological ECM distribution and, further, a biphasic dependence of migration on the matrix density, and in part adhesion, in both two-dimensional and three-dimensional settings. Moreover, we demonstrate that the directional component of cell movement is strongly correlated with the topological distribution of the ECM fibrous network. In the three-dimensional networks, we also investigate the effects of the matrix mechanical microstructure, observing that, at a given distribution of fibers, cell motility has a subtle bimodal relation with the elasticity of the scaffold. Finally, cell locomotion requires deformation of the cell's nucleus and/or cell-derived proteolysis of steric fibrillar obstacles within rather rigid matrices characterized by small pores, not, however, for sufficiently large pores. In conclusion, we here propose a mathematical modeling approach that serves to characterize cell migration as a biological phenomen in health, disease and tissue engineering applications. The research that led to the present paper was partially supported by a grant of the group GNFM of INdA

Squark Flavor Implications from B --> K(*) l+ l-

Recent experimental and theoretical progress regarding B --> K(*) l+ l- decays led to improved bounds on the Wilson coefficients C_9 and C_10 of four-fermion operators of the |Delta B|=|Delta S|=1 effective Hamiltonian. We analyze the resulting implications on squark flavor violation in the MSSM and obtain new constraints on flavor-changing left-right mixing in the up-squark-sector. We find the dimensionless flavor mixing parameter (delta^u_23)_LR, depending on the flavor-diagonal MSSM masses and couplings, to be as low as \lesssim 0.1. This has implications for models based on radiative flavor violation and leads to BR(B_s --> mu+ mu-) \gtrsim 1 x 10^-9. Rare top decays t --> c gamma, t --> c g, t --> c Z have branching ratios predicted to be below \lesssim few times 10^-8, 10^-6 and 10^-7, respectively.Comment: v2: 21 pages, 5 figures; Eq (A.2) and chirality-flipping mass insertion results clarified, references added, conclusions unchange