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Mathematical Modeling and Computational Methods for Structured Populations

Author : Mingtao Xia
Publisher :
Page : 0 pages
File Size : 34,62 MB
Release : 2023
Category :
ISBN :

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Structured population models are fundamental in the fields of biology, ecology, and social sciences, as they provide both theoretical insights and practical applications. Different structured population models range from modeling cellular population proliferation and population dynamics to simulating disease spread on social networks. However, there has been little work on modeling populations across different scales that could link individual behavior to population dynamics. Additionally, for existing mathematical models on structured populations, several computational challenges arise as how to develop efficient numerical solvers to simulate those models and to control the dynamics of those models. Overall, my dissertation covers three related topics: modeling structured populations, developing efficient numerical solvers to simulate these models, and developing control algorithms to control population dynamics. Specifically, my dissertation focuses on modeling and devising algorithms for two types of structured populations: i) age, size, or added size-structured cell population for describing cellular proliferation and ii) the structured infected-time- or number-of-contact-based human population for describing disease spread. Regarding the structured cellular population, we derive mathematical models at both the macroscopic population dynamics level and microscopic individual behavior level, leading to structured partial differential equation (PDE) models for cellular proliferation with different structure variables such as cellular age, size, or added size. Next, we develop an efficient adaptive spectral method for numerically solving spatiotemporal PDEs, which was inspired by simulating the blowup behavior in the unbounded-domain PDE model for cellular populations. In addition to the structured population models, the adaptive spectral method proves efficient and accurate in solving a wide range of spatiotemporal PDEs in unbounded domains such as the Schr dinger equations in quantum mechanics. Regarding the structured human population, we introduce an infected-time-structured PDE model and a number-of-contact-structured ODE model for simulating disease spread, e.g., COVID-19, in the population. Then, for the number-of-contact-structured ODE model, we develop classic Pontryagin-maximum-principle-based and reinforcement-learning-based optimal control algorithms. These two algorithms can effectively mitigate the spread of disease by appropriately allocating limited test kits or vaccination resources.

Data-driven Modelling of Structured Populations

Author : Stephen P. Ellner
Publisher : Springer
Page : 339 pages
File Size : 13,71 MB
Release : 2016-05-13
Category : Mathematics
ISBN : 3319288938

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This book is a “How To” guide for modeling population dynamics using Integral Projection Models (IPM) starting from observational data. It is written by a leading research team in this area and includes code in the R language (in the text and online) to carry out all computations. The intended audience are ecologists, evolutionary biologists, and mathematical biologists interested in developing data-driven models for animal and plant populations. IPMs may seem hard as they involve integrals. The aim of this book is to demystify IPMs, so they become the model of choice for populations structured by size or other continuously varying traits. The book uses real examples of increasing complexity to show how the life-cycle of the study organism naturally leads to the appropriate statistical analysis, which leads directly to the IPM itself. A wide range of model types and analyses are presented, including model construction, computational methods, and the underlying theory, with the more technical material in Boxes and Appendices. Self-contained R code which replicates all of the figures and calculations within the text is available to readers on GitHub. Stephen P. Ellner is Horace White Professor of Ecology and Evolutionary Biology at Cornell University, USA; Dylan Z. Childs is Lecturer and NERC Postdoctoral Fellow in the Department of Animal and Plant Sciences at The University of Sheffield, UK; Mark Rees is Professor in the Department of Animal and Plant Sciences at The University of Sheffield, UK.

Gender-structured Population Modeling

Author : M. Iannelli
Publisher : SIAM
Page : 186 pages
File Size : 17,12 MB
Release : 2005-04-01
Category : Mathematics
ISBN : 0898715776

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This book gives a unified presentation of, and mathematical framework for, modeling population growth by couple formation, summarizing both past and present modeling results. It provides results on model analysis, gives an up-to-date review of mathematical demography, discusses numerical methods, and puts deterministic modeling of human populations into historical perspective.

The Basic Approach to Age-Structured Population Dynamics

Author : Mimmo Iannelli
Publisher : Springer
Page : 357 pages
File Size : 40,39 MB
Release : 2017-08-27
Category : Mathematics
ISBN : 9402411461

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This book provides an introduction to age-structured population modeling which emphasizes the connection between mathematical theory and underlying biological assumptions. Through the rigorous development of the linear theory and the nonlinear theory alongside numerics, the authors explore classical equations that describe the dynamics of certain ecological systems. Modeling aspects are discussed to show how relevant problems in the fields of demography, ecology and epidemiology can be formulated and treated within the theory. In particular, the book presents extensions of age-structured modeling to the spread of diseases and epidemics while also addressing the issue of regularity of solutions, the asymptotic behavior of solutions, and numerical approximation. With sections on transmission models, non-autonomous models and global dynamics, this book fills a gap in the literature on theoretical population dynamics. The Basic Approach to Age-Structured Population Dynamics will appeal to graduate students and researchers in mathematical biology, epidemiology and demography who are interested in the systematic presentation of relevant models and mathematical methods.

Spaces of Measures and their Applications to Structured Population Models

Author : Christian Düll
Publisher : Cambridge University Press
Page : 322 pages
File Size : 12,10 MB
Release : 2021-10-07
Category : Mathematics
ISBN : 1009020471

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Structured population models are transport-type equations often applied to describe evolution of heterogeneous populations of biological cells, animals or humans, including phenomena such as crowd dynamics or pedestrian flows. This book introduces the mathematical underpinnings of these applications, providing a comprehensive analytical framework for structured population models in spaces of Radon measures. The unified approach allows for the study of transport processes on structures that are not vector spaces (such as traffic flow on graphs) and enables the analysis of the numerical algorithms used in applications. Presenting a coherent account of over a decade of research in the area, the text includes appendices outlining the necessary background material and discusses current trends in the theory, enabling graduate students to jump quickly into research.

Computational and Mathematical Modeling in the Social Sciences

Author : Scott de Marchi
Publisher : Cambridge University Press
Page : 232 pages
File Size : 15,52 MB
Release : 2005-08-15
Category : Business & Economics
ISBN : 9780521853620

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Offers an overview of mathematical modeling concentrating on game theory, statistics and computational modeling.

Computational Statistics and Mathematical Modeling Methods in Intelligent Systems

Author : Radek Silhavy
Publisher : Springer Nature
Page : 424 pages
File Size : 37,77 MB
Release : 2019-09-19
Category : Technology & Engineering
ISBN : 303031362X

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This book presents real-world problems and exploratory research in computational statistics, mathematical modeling, artificial intelligence and software engineering in the context of the intelligent systems. This book constitutes the refereed proceedings of the 3rd Computational Methods in Systems and Software 2019 (CoMeSySo 2019), a groundbreaking online conference that provides an international forum for discussing the latest high-quality research results.

An Introduction to Mathematical Modeling

Author : Edward A. Bender
Publisher : Courier Corporation
Page : 273 pages
File Size : 29,69 MB
Release : 2012-05-23
Category : Mathematics
ISBN : 0486137120

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Employing a practical, "learn by doing" approach, this first-rate text fosters the development of the skills beyond the pure mathematics needed to set up and manipulate mathematical models. The author draws on a diversity of fields — including science, engineering, and operations research — to provide over 100 reality-based examples. Students learn from the examples by applying mathematical methods to formulate, analyze, and criticize models. Extensive documentation, consisting of over 150 references, supplements the models, encouraging further research on models of particular interest. The lively and accessible text requires only minimal scientific background. Designed for senior college or beginning graduate-level students, it assumes only elementary calculus and basic probability theory for the first part, and ordinary differential equations and continuous probability for the second section. All problems require students to study and create models, encouraging their active participation rather than a mechanical approach. Beyond the classroom, this volume will prove interesting and rewarding to anyone concerned with the development of mathematical models or the application of modeling to problem solving in a wide array of applications.

Mathematical Modeling of Biological Systems, Volume II

Author : Andreas Deutsch
Publisher : Springer Science & Business Media
Page : 383 pages
File Size : 48,74 MB
Release : 2007-10-12
Category : Mathematics
ISBN : 081764556X

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Volume II of this two-volume, interdisciplinary work is a unified presentation of a broad range of state-of-the-art topics in the rapidly growing field of mathematical modeling in the biological sciences. Highlighted throughout are mathematical and computational apporaches to examine central problems in the life sciences, ranging from the organization principles of individual cells to the dynamics of large populations. The chapters are thematically organized into the following main areas: epidemiology, evolution and ecology, immunology, neural systems and the brain, and innovative mathematical methods and education. The work will be an excellent reference text for a broad audience of researchers, practitioners, and advanced students in this rapidly growing field at the intersection of applied mathematics, experimental biology and medicine, computational biology, biochemistry, computer science, and physics.

An Introduction to Structured Population Dynamics

Author : J. M. Cushing
Publisher : SIAM
Page : 106 pages
File Size : 43,36 MB
Release : 1998-01-01
Category : Science
ISBN : 9781611970005

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Interest in the temporal fluctuations of biological populations can be traced to the dawn of civilization. How can mathematics be used to gain an understanding of population dynamics? This monograph introduces the theory of structured population dynamics and its applications, focusing on the asymptotic dynamics of deterministic models. This theory bridges the gap between the characteristics of individual organisms in a population and the dynamics of the total population as a whole. In this monograph, many applications that illustrate both the theory and a wide variety of biological issues are given, along with an interdisciplinary case study that illustrates the connection of models with the data and the experimental documentation of model predictions. The author also discusses the use of discrete and continuous models and presents a general modeling theory for structured population dynamics. Cushing begins with an obvious point: individuals in biological populations differ with regard to their physical and behavioral characteristics and therefore in the way they interact with their environment. Studying this point effectively requires the use of structured models. Specific examples cited throughout support the valuable use of structured models. Included among these are important applications chosen to illustrate both the mathematical theories and biological problems that have received attention in recent literature.