scholarly journals Data suggest COVID-19 affected numbers greatly exceeded detected numbers, in four European countries, as per a delayed SEIQR model

2020 ◽  
Author(s):  
Sankalp Tiwari ◽  
C. P. Vyasarayani ◽  
Anindya Chatterjee
Keyword(s):  
Mathematical Model ◽  
Disease Progression ◽  
Continuum Model ◽  
Pareto Distribution ◽  
Infected Individual ◽  
European Countries ◽  
Single Node ◽  
Long Tail ◽  
The Mean ◽  
The Continuum

Abstract People in many countries are now infected with COVID-19. By now, it is clear that the number of people infected is much more than the number of reported cases. To estimate the infected but undetected/unreported cases using a mathematical model, we can use a parameter called the probability of quarantining an infected individual. This parameter exists in the time-delayed SEIQR model (Scientific Reports, article number: 3505). Two limiting cases of a network of such models are used to estimate the undetected population. The first limit corresponds to the network collapsing onto a single node and is referred to as the mean-$\beta$ model. In the second case, the number of nodes in the network is infinite and results in a continuum model, treating the infectivity as statistically distributed. We use a shifted Pareto distribution to model the infectivity. This distribution has a long tail and incorporates the presence of super-spreaders that contribute to the disease progression. While both the models capture the {\em detected} numbers equally well, the predictions of {\em affected} numbers from the continuum model are more realistic. Results suggest that affected people outnumber detected people by one to two orders of magnitude in Spain, UK, Italy, and Germany.

scholarly journals Data suggest COVID-19 affected numbers greatly exceeded detected numbers, in four European countries, as per a delayed SEIQR model

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Sankalp Tiwari ◽  
C. P. Vyasarayani ◽  
Anindya Chatterjee
Keyword(s):  
Continuum Model ◽  
Pareto Distribution ◽  
Infected Individual ◽  
Generalized Pareto Distribution ◽  
Single Node ◽  
Generalized Pareto ◽  
Serological Studies ◽  
The Mean ◽  
The Uk ◽  
The Continuum

AbstractPeople in many countries are now infected with COVID-19. By now, it is clear that the number of people infected is much greater than the number of reported cases. To estimate the infected but undetected/unreported cases using a mathematical model, we can use a parameter called the probability of quarantining an infected individual. This parameter exists in the time-delayed SEIQR model (Scientific Reports, article number: 3505). Here, two limiting cases of a network of such models are used to estimate the undetected population. The first limit corresponds to the network collapsing onto a single node and is referred to as the mean-$$\beta$$ β model. In the second case, the number of nodes in the network is infinite and results in a continuum model wherein the infectivity is statistically distributed. We use a generalized Pareto distribution to model the infectivity. This distribution has a fat tail and models the presence of super-spreaders that contribute to the disease progression. While both models capture the detected numbers well, the predictions of affected numbers from the continuum model are more realistic. Our results suggest that affected people outnumber detected people by one to two orders of magnitude in Spain, the UK, Italy, and Germany. Our results are consistent with corresponding trends obtained from published serological studies in Spain, the UK and Italy. The match with limited studies in Germany is poor, possibly because Germany’s partial lockdown approach requires different modeling.

Photo-electric Hβ and uvby photometry

1966 ◽  
Vol 24 ◽  
pp. 170-180
Author(s):  
D. L. Crawford
Keyword(s):  
Narrow Band ◽  
Line Strength ◽  
Interference Filter ◽  
B Stars ◽  
Relative Line ◽  
The Mean ◽  
F Stars ◽  
Two Parameters ◽  
Filter Photometry ◽  
The Continuum

Early in the 1950's Strömgren (1, 2, 3, 4, 5) introduced medium to narrow-band interference filter photometry at the McDonald Observatory. He used six interference filters to obtain two parameters of astrophysical interest. These parameters he calledlandc, for line and continuum hydrogen absorption. The first measured empirically the absorption line strength of Hβby means of a filter of half width 35Å centered on Hβand compared to the mean of two filters situated in the continuum near Hβ. The second index measured empirically the Balmer discontinuity by means of a filter situated below the Balmer discontinuity and two above it. He showed that these two indices could accurately predict the spectral type and luminosity of both B stars and A and F stars. He later derived (6) an indexmfrom the same filters. This index was a measure of the relative line blanketing near 4100Å compared to two filters above 4500Å. These three indices confirmed earlier work by many people, including Lindblad and Becker. References to this earlier work and to the systems discussed today can be found in Strömgren's article inBasic Astronomical Data(7).

Batch Crystallization with Crystals Attrition

1993 ◽  
Vol 58 (8) ◽  
pp. 1855-1860 ◽  
Author(s):  
Jaroslav Nývlt ◽  
Stanislav Žáček
Keyword(s):  
Mathematical Model ◽  
Calcium Sulfate ◽  
Crystal Size ◽  
Theoretical Description ◽  
Secondary Nucleation ◽  
Batch Crystallization ◽  
Batch Time ◽  
The Mean

The dependence of the mean crystal size of the products from batch crystallizers on the batch time occasionally exhibits a maximum, which can be explained by secondary nucleation due to the attrition of crystals. A kinetic equatation of nucleation, comprising a term for crystal attrition, can be used for the theoretical description of such behaviour. A mathematical model of a batch crystallizer with crystal attrition has been verified on the calcium sulfate precipitation.

scholarly journals Hierarchical modeling of mechano-chemical dynamics of epithelial sheets across cells and tissue

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yoshifumi Asakura ◽  
Yohei Kondo ◽  
Kazuhiro Aoki ◽  
Honda Naoki
Keyword(s):  
Wound Healing ◽  
Cell Migration ◽  
Continuum Model ◽  
Tissue Level ◽  
Chemical Signals ◽  
Cellular Level ◽  
Mathematical Framework ◽  
Collective Cell Migration ◽  
The Continuum ◽  
Cell Cell

AbstractCollective cell migration is a fundamental process in embryonic development and tissue homeostasis. This is a macroscopic population-level phenomenon that emerges across hierarchy from microscopic cell-cell interactions; however, the underlying mechanism remains unclear. Here, we addressed this issue by focusing on epithelial collective cell migration, driven by the mechanical force regulated by chemical signals of traveling ERK activation waves, observed in wound healing. We propose a hierarchical mathematical framework for understanding how cells are orchestrated through mechanochemical cell-cell interaction. In this framework, we mathematically transformed a particle-based model at the cellular level into a continuum model at the tissue level. The continuum model described relationships between cell migration and mechanochemical variables, namely, ERK activity gradients, cell density, and velocity field, which could be compared with live-cell imaging data. Through numerical simulations, the continuum model recapitulated the ERK wave-induced collective cell migration in wound healing. We also numerically confirmed a consistency between these two models. Thus, our hierarchical approach offers a new theoretical platform to reveal a causality between macroscopic tissue-level and microscopic cellular-level phenomena. Furthermore, our model is also capable of deriving a theoretical insight on both of mechanical and chemical signals, in the causality of tissue and cellular dynamics.

scholarly journals A Mathematical Model of Contact Tracing during the 2014–2016 West African Ebola Outbreak

Mathematics ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 608
Author(s):  
Danielle Burton ◽  
Suzanne Lenhart ◽  
Christina J. Edholm ◽  
Benjamin Levy ◽  
Michael L. Washington ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Disease Management ◽  
Ebola Virus ◽  
Virus Disease ◽  
Infected Individual ◽  
Vital Role ◽  
West African ◽  
Contact Tracing ◽  
The Novel ◽  
Using Data

The 2014–2016 West African outbreak of Ebola Virus Disease (EVD) was the largest and most deadly to date. Contact tracing, following up those who may have been infected through contact with an infected individual to prevent secondary spread, plays a vital role in controlling such outbreaks. Our aim in this work was to mechanistically represent the contact tracing process to illustrate potential areas of improvement in managing contact tracing efforts. We also explored the role contact tracing played in eventually ending the outbreak. We present a system of ordinary differential equations to model contact tracing in Sierra Leonne during the outbreak. Using data on cumulative cases and deaths, we estimate most of the parameters in our model. We include the novel features of counting the total number of people being traced and tying this directly to the number of tracers doing this work. Our work highlights the importance of incorporating changing behavior into one’s model as needed when indicated by the data and reported trends. Our results show that a larger contact tracing program would have reduced the death toll of the outbreak. Counting the total number of people being traced and including changes in behavior in our model led to better understanding of disease management.

Coupled dynamics of populations supported by discrete sites and their continuum limit

2010 ◽  
Vol 466 (2121) ◽  
pp. 2561-2586 ◽  
Author(s):  
Timothy R. Field ◽  
Robert J. A. Tough
Keyword(s):  
Evolution Equation ◽  
Closed Form ◽  
Generating Function ◽  
Rate Equation ◽  
Continuum Limit ◽  
Infinite Chain ◽  
Migration Process ◽  
The Mean ◽  
The Continuum ◽  
Birth Death

The illumination of single population behaviour subject to the processes of birth, death and immigration has provided a basis for the discussion of the non-Gaussian statistical and temporal correlation properties of scattered radiation. As a first step towards the modelling of its spatial correlations, we consider the populations supported by an infinite chain of discrete sites, each subject to birth, death and immigration and coupled by migration between adjacent sites. To provide some motivation, and illustrate the techniques we will use, the migration process for a single particle on an infinite chain of sites is introduced and its diffusion dynamics derived. A certain continuum limit is identified and its properties studied via asymptotic analysis. This forms the basis of the multi-particle model of a coupled population subject to single site birth, death and immigration processes, in addition to inter-site migration. A discrete rate equation is formulated and its generating function dynamics derived. This facilitates derivation of the equations of motion for the first- and second-order cumulants, thus generalizing the earlier results of Bailey through the incorporation of immigration at each site. We present a novel matrix formalism operating in the time domain that enables solution of these equations yielding the mean occupancy and inter-site variances in the closed form. The results for the first two moments at a single time are used to derive expressions for the asymptotic time-delayed correlation functions, which relates to Glauber’s analysis of an Ising model. The paper concludes with an analysis of the continuum limit of the birth–death–immigration–migration process in terms of a path integral formalism. The continuum rate equation and evolution equation for the generating function are developed, from which the evolution equation of the mean occupancy is derived, in this limit. Its solution is provided in closed form.

Validation of New Mathematical Model of Flank Wear by Different Methods

2012 ◽  
Vol 729 ◽  
pp. 169-174 ◽  
Author(s):  
Zoltán Pálmai ◽  
Márton Takács ◽  
Balázs Zsolt Farkas
Keyword(s):  
Activation Energy ◽  
Mathematical Model ◽  
Flank Wear ◽  
Technological Parameters ◽  
Wear Process ◽  
Oxidation Processes ◽  
Industrial Manufacturing ◽  
Thermally Activated ◽  
Optical Electron ◽  
The Mean

Having reviewed the literature on cutting and based on the optical, electron-optical and morphological examinations of wear processes we have reached the conclusion that it is possible to describe the abrasive, adhesive and thermally activated diffusion, oxidation processes in a single mathematical model. The model is a non-linear autonomous differential equation, which can be solved by simple numerical methods. The complex wear equation was validated by the results of the cutting tests performed with P20 carbide on C45 carbon steel. If we have this data, we can calculate the activation energy of the process determining the nature of the wear process. The apparent activation energy of wear is Q=151,7kJ/mol. The model can even be used with changing technological parameters, and the data necessary for the constants of the wear equation may as well be determined even by measurements performed on the tool during industrial manufacturing. By the mean of this data, we can calculate the activation energy determining the nature of the wear process.

scholarly journals Formulation of 2D Graphene Deformation Based on Chiral-Tube Base Vectors

2010 ◽  
Vol 2010 ◽  
pp. 1-7
Author(s):  
Bohua Sun
Keyword(s):  
Molecular Dynamics ◽  
Shell Model ◽  
Continuum Model ◽  
Real Space ◽  
Honeycomb Lattice ◽  
Mechanical Behaviors ◽  
Future Studies ◽  
Physical Components ◽  
Intrinsic Feature ◽  
The Continuum

The intrinsic feature of graphene honeycomb lattice is defined by its chiral index (n,m), which can be taken into account when using molecular dynamics. However, how to introduce the index into the continuum model of graphene is still an open problem. The present manuscript adopts the continuum shell model with single director to describe the mechanical behaviors of graphene. In order to consider the intrinsic features of the graphene honeycomb lattice—chiral index (n,m), the chiral-tube vectors of graphene in real space have been used for construction of reference unit base vectors of the shell model; therefore, the formulations will contain the chiral index automatically, or in an explicit form in physical components. The results are quite useful for future studies of graphene mechanics.

Non-invasive determination of the systolic peak-to-peak gradient in children with aortic stenosis: validation of a mathematical model

2000 ◽  
Vol 10 (2) ◽  
pp. 115-119 ◽  
Author(s):  
Valter C. Lima ◽  
Evan Zahn ◽  
Christine Houde ◽  
Jeffrey Smallhorn ◽  
Robert M. Freedom ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Pulse Pressure ◽  
Linear Regression Analysis ◽  
Systolic Pressure ◽  
Pressure Gradients ◽  
Non Invasive ◽  
The Mean ◽  
Congenital Aortic Valvar Stenosis ◽  
Peak Gradient

AbstractDoppler derived systolic pressure gradients have become widely applied as noninvasively obtained estimates of the severity of aortic valvar stenosis. There is little correlation, however, between the Doppler derived peak instantaneous gradient and the peak-to-peak gradient obtained at catheterisation, the latter being the most applied variable to determine severity in children. The purpose of this study was to validate a mathematical model based on data from catheterisation which estimates the peak-to-peak gradient from variables which can be obtained by noninvasive means (Doppler derived mean gradient and pulse pressure), according to the formula: peak-to-peak systolic gradient=6.02+1.49*(mean gradient)−0.44*(pulse pressure). Simultaneous cardiac catheterization and Doppler studies were performed on 10 patients with congenital aortic valvar stenosis. Correlations between the gradients measured at catheter measured, and those derived by Doppler, were performed using linear regression analysis. The mean gradients correlated well (y=0.67 × + 11.11, r=0.87, SEE=6 mm Hg, p=0.001). The gradients predicted by the formula also correlated well with the peak-to-peak gradients measured at catheter (y=0.66 × + 14.44, r=0.84, SEE=9 mm Hg, p=O.002). The data support the application of the model, allowing noninvasive prediction of the peak-to-peak gradient across the aortic valvar stenosis.

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