Modeling and Simulation in the Medical and Health Sciences

An introduction to state-of-the-art modeling and simulation approaches for social and economic determinants of population health New Horizons in Modeling and Simulation for Social Epidemiology and Public Health offers a comprehensive introduction to modeling and simulation that addresses the many complex research questions in social epidemiology and public health. This book highlights a variety of practical applications and illustrative examples with a focus on modeling and simulation approaches for the social and economic determinants of population health. The book contains classic case examples in agent-based modeling (ABM) as well as essential information on ABM applications to public health including for infectious disease modeling, obesity, and tobacco control. This book also surveys applications of microsimulation (MSM) including of tax-benefit policies to project impacts of the social determinants of health. Specifically, this book: Provides an overview of the social determinants of health and the public health significance of addressing the social determinants of health Gives a conceptual foundation for the application of ABM and MSM to study the social determinants of health Offers methodological introductions to both ABM and MSM approaches with illustrative examples Includes cutting-edge systematic reviews of empirical applications of ABM and MSM in the social sciences, social epidemiology, and public health Discusses future directions for empirical research using ABM and MSM, including integrating aspects of both ABM and MSM and implications for public health policies Written for a broad audience of policy analysts, public planners, and researchers and practitioners in public health and public policy including social epidemiologists, New Horizons in Modeling and Simulation for Social Epidemiology and Public Health offers a fundamental guide to the social determinants of health and state-of-the-art applications of ABM and MSM to studying the social and economic determinants of population health.

Simulation is the art of using tools – physical or conceptual models, or computer hardware and software, to attempt to create the illusion of reality. The discipline has in recent years expanded to include the modelling of systems that rely on human factors and therefore possess a large proportion of uncertainty, such as social, economic or commercial systems. These new applications make the discipline of modelling and simulation a field of dynamic growth and new research. Stanislaw Raczynski outlines the considerable and promising research that is being conducted to counter the problems of uncertainty surrounding the methods used to approach these new applications. It aims to stimulate the reader into seeking out new tools for modelling and simulation. Examines the state-of-the-art in recent research into methods of approaching new applications in the field of modelling and simulation Provides an introduction to new modelling tools such as differential inclusions, metric structures in the space of models, semi-discrete events, and use of simulation in parallel optimization techniques Discusses recently developed practical applications: for example the PASION simulation system, stock market simulation, a new fluid dynamics tool, manufacturing simulation and the simulation of social structures Illustrated throughout with a series of case studies Modelling and Simulation: The Computer Science of Illusion will appeal to academics, postgraduate students, researchers and practitioners in the modelling and simulation of industrial computer systems. It will also be of interest to those using simulation as an auxiliary tool.

The definite guide to the theory, knowledge, technical expertise, and ethical considerations that define the M&S profession From traffic control to disaster management, supply chain analysis to military logistics, healthcare management to new drug discovery, modeling and simulation (M&S) has become an essential tool for solving countless real-world problems. M&S professionals are now indispensable to how things get done across virtually every aspect of modern life. This makes it all the more surprising that, until now, no effort has been made to systematically codify the core theory, knowledge, and technical expertise needed to succeed as an M&S professional. This book brings together contributions from experts at the leading edge of the modeling and simulation profession, worldwide, who share their priceless insights into issues which are fundamental to professional success and career development in this critically important field. Running as a common thread throughout the book is an emphasis on several key aspects of the profession, including the essential body of knowledge underlying the M&S profession; the technical discipline of M&S; the ethical standards that should guide professional conduct; and the economic and commercial challenges today’s M&S professionals face. • Demonstrates applications of M&S tools and techniques in a variety of fields—such as engineering, operations research, and cyber environments—with over 500 types of simulations • Highlights professional and academic aspects of the field, including preferred programming languages, professional academic and certification programs, and key international societies • Shows why M&S professionals must be fully versed in the theory, concepts, and tools needed to address the challenges of cyber environments The Profession of Modeling and Simulation is a valuable resource for M&S practitioners, developers, and researchers working in industry and government. Simulation professionals, including administrators, managers, technologists, faculty members, and scholars within the physical sciences, life sciences, and engineering fields will find it highly useful, as will students planning to pursue a career in the M&S profession. “ …nearly three dozen experts in Modeling and Simulation (M&S) come together to make a compelling case for the recognition of M&S as a profession… Important reading for anyone seeking to elevate the standing of this vital field.” Alfred (Al) Grasso, President & CEO, The MITRE Corporation Andreas Tolk, PhD, is Technology Integrator for the Modeling, Simulation, Experimentation, and Analytics Division of The MITRE Corporation, an adjunct professor in the Department of Engineering Management and Systems Engineering and the Department for Modeling, Simulation, and Visualization Engineering at Old Dominion University, and an SCS fellow. Tuncer ?ren, PhD, is Professor Emeritus of Computer Science at the University of Ottawa. He is an SCS fellow and an inductee to SCS Modeling and Simulation Hall of Fame. His research interests include advancing methodologies, ethics, body of knowledge, and terminology of modeling and simulation.

Network Modeling and Simulation is a practical guide to using modeling and simulation to solve real-life problems. The authors give a comprehensive exposition of the core concepts in modeling and simulation, and then systematically address the many practical considerations faced by developers in modeling complex large-scale systems. The authors provide examples from computer and telecommunication networks and use these to illustrate the process of mapping generic simulation concepts to domain-specific problems in different industries and disciplines. Key features: Provides the tools and strategies needed to build simulation models from the ground up rather than providing solutions to specific problems. Includes a new simulation tool, CASiNO built by the authors. Examines the core concepts of systems simulation and modeling. Presents code examples to illustrate the implementation process of commonly encountered simulation tasks. Offers examples of industry-standard modeling methodology that can be applied in steps to tackle any modeling problem in practice.

This unique book presents simple, easy-to-use, but effective short codes as well as virtual tools that can be used by electrical, electronic, communication, and computer engineers in a broad range of electrical engineering problems Electromagnetic modeling is essential to the design and modeling of antenna, radar, satellite, medical imaging, and other applications. In this book, author Levent Sevgi explains techniques for solving real-time complex physical problems using MATLAB-based short scripts and comprehensive virtual tools. Unique in coverage and tutorial approach, Electromagnetic Modeling and Simulation covers fundamental analytical and numerical models that are widely used in teaching, research, and engineering designs—including mode and ray summation approaches with the canonical 2D nonpenetrable parallel plate waveguide as well as FDTD, MoM, and SSPE scripts. The book also establishes an intelligent balance among the essentials of EM MODSIM: The Problem (the physics), The Theory and Models (mathematical background and analytical solutions), and The Simulations (code developing plus validation, verification, and calibration). Classroom tested in graduate-level and short courses, Electromagnetic Modeling and Simulation: Clarifies concepts through numerous worked problems and quizzes provided throughout the book Features valuable MATLAB-based, user-friendly, effective engineering and research virtual design tools Includes sample scenarios and video clips recorded during characteristic simulations that visually impact learning—available on wiley.com Provides readers with their first steps in EM MODSIM as well as tools for medium and high-level code developers and users Electromagnetic Modeling and Simulation thoroughly covers the physics, mathematical background, analytical solutions, and code development of electromagnetic modeling, making it an ideal resource for electrical engineers and researchers.

A systematic overview of the quickly developing field of bioengineering—with state-of-the-art modeling software! Computational Modeling and Simulation Examples in Bioengineering provides a comprehensive introduction to the emerging field of bioengineering. It provides the theoretical background necessary to simulating pathological conditions in the bones, muscles, cardiovascular tissue, and cancers, as well as lung and vertigo disease. The methodological approaches used for simulations include the finite element, dissipative particle dynamics, and lattice Boltzman. The text includes access to a state-of-the-art software package for simulating the theoretical problems. In this way, the book enhances the reader's learning capabilities in the field of biomedical engineering. The aim of this book is to provide concrete examples of applied modeling in biomedical engineering. Examples in a wide range of areas equip the reader with a foundation of knowledge regarding which problems can be modeled with which numerical methods. With more practical examples and more online software support than any competing text, this book organizes the field of computational bioengineering into an accessible and thorough introduction. Computational Modeling and Simulation Examples in Bioengineering: Includes a state-of-the-art software package enabling readers to engage in hands-on modeling of the examples in the book Provides a background on continuum and discrete modeling, along with equations and derivations for three key numerical methods Considers examples in the modeling of bones, skeletal muscles, cartilage, tissue engineering, blood flow, plaque, and more Explores stent deployment modeling as well as stent design and optimization techniques Generates different examples of fracture fixation with respect to the advantages in medical practice applications Computational Modeling and Simulation Examples in Bioengineering is an excellent textbook for students of bioengineering, as well as a support for basic and clinical research. Medical doctors and other clinical professionals will also benefit from this resource and guide to the latest modeling techniques.

A comprehensive introduction to behavioral and social science research methods in the health sciences Understanding and Conducting Research in the Health Sciences is designed to develop and facilitate the ability to conduct research and understand the practical value of designing, conducting, interpreting, and reporting behavioral and social science research findings in the health science and medical fields. The book provides complete coverage of the process behind these research methods, including information-gathering, decision formation, and results presentation. Examining the application of behavioral and social science research methodologies within the health sciences, the book focuses on implementing and developing relevant research questions, collecting and managing data, and communicating various research perspectives. An essential book for readers looking to possess an understanding of all aspects of conducting research in the health science field, Understanding and Conducting Research in the Health Sciences features: Various research designs that are appropriate for use in the health sciences, including single-participant, multi-group, longitudinal, correlational, and experimental designs Step-by-step coverage of single-factor and multifactor studies as well as single-subject and nonexperimental methods Accessible chapter explanations, real-world examples, and numerous illustrations throughout Guidance regarding how to write about research within the formatting styles of the American Medical Association and the American Psychological Association The book is an excellent educational resource for healthcare and health service practitioners and researchers who are interested in conducting and understanding behavioral and social science research done within the health sciences arena. The book is also a useful resource for students taking courses in the fields of medicine, public health, epidemiology, biostatistics, and the health sciences.

This concise and clear introduction to the topic requires only basic knowledge of calculus and linear algebra – all other concepts and ideas are developed in the course of the book. Lucidly written so as to appeal to undergraduates and practitioners alike, it enables readers to set up simple mathematical models on their own and to interpret their results and those of others critically. To achieve this, many examples have been chosen from various fields, such as biology, ecology, economics, medicine, agricultural, chemical, electrical, mechanical and process engineering, which are subsequently discussed in detail. Based on the author`s modeling and simulation experience in science and engineering and as a consultant, the book answers such basic questions as: What is a mathematical model? What types of models do exist? Which model is appropriate for a particular problem? What are simulation, parameter estimation, and validation? The book relies exclusively upon open-source software which is available to everybody free of charge. The entire book software – including 3D CFD and structural mechanics simulation software – can be used based on a free CAELinux-Live-DVD that is available in the Internet (works on most machines and operating systems).

This book provides clear instructions to researchers on how to apply Structural Equation Models (SEMs) for analyzing the inter relationships between observed and latent variables. Basic and Advanced Bayesian Structural Equation Modeling introduces basic and advanced SEMs for analyzing various kinds of complex data, such as ordered and unordered categorical data, multilevel data, mixture data, longitudinal data, highly non-normal data, as well as some of their combinations. In addition, Bayesian semiparametric SEMs to capture the true distribution of explanatory latent variables are introduced, whilst SEM with a nonparametric structural equation to assess unspecified functional relationships among latent variables are also explored. Statistical methodologies are developed using the Bayesian approach giving reliable results for small samples and allowing the use of prior information leading to better statistical results. Estimates of the parameters and model comparison statistics are obtained via powerful Markov Chain Monte Carlo methods in statistical computing. Introduces the Bayesian approach to SEMs, including discussion on the selection of prior distributions, and data augmentation. Demonstrates how to utilize the recent powerful tools in statistical computing including, but not limited to, the Gibbs sampler, the Metropolis-Hasting algorithm, and path sampling for producing various statistical results such as Bayesian estimates and Bayesian model comparison statistics in the analysis of basic and advanced SEMs. Discusses the Bayes factor, Deviance Information Criterion (DIC), and $L_\nu$-measure for Bayesian model comparison. Introduces a number of important generalizations of SEMs, including multilevel and mixture SEMs, latent curve models and longitudinal SEMs, semiparametric SEMs and those with various types of discrete data, and nonparametric structural equations. Illustrates how to use the freely available software WinBUGS to produce the results. Provides numerous real examples for illustrating the theoretical concepts and computational procedures that are presented throughout the book. Researchers and advanced level students in statistics, biostatistics, public health, business, education, psychology and social science will benefit from this book.

Explores wide-ranging applications of modeling and simulation techniques that allow readers to conduct research and ask «What if??» Principles of Modeling and Simulation: A Multidisciplinary Approach is the first book to provide an introduction to modeling and simulation techniques across diverse areas of study. Numerous researchers from the fields of social science, engineering, computer science, and business have collaborated on this work to explore the multifaceted uses of computational modeling while illustrating their applications in common spreadsheets. The book is organized into three succinct parts: Principles of Modeling and Simulation provides a brief history of modeling and simulation, outlines its many functions, and explores the advantages and disadvantages of using models in problem solving. Two major reasons to employ modeling and simulation are illustrated through the study of a specific problem in conjunction with the use of related applications, thus gaining insight into complex concepts. Theoretical Underpinnings examines various modeling techniques and introduces readers to two significant simulation concepts: discrete event simulation and simulation of continuous systems. This section details the two primary methods in which humans interface with simulations, and it also distinguishes the meaning, importance, and significance of verification and validation. Practical Domains delves into specific topics related to transportation, business, medicine, social science, and enterprise decision support. The challenges of modeling and simulation are discussed, along with advanced applied principles of modeling and simulation such as representation techniques, integration into the application infrastructure, and emerging technologies. With its accessible style and wealth of real-world examples, Principles of Modeling and Simulation: A Multidisciplinary Approach is a valuable book for modeling and simulation courses at the upper-undergraduate and graduate levels. It is also an indispensable reference for researchers and practitioners working in statistics, mathematics, engineering, computer science, economics, and the social sciences who would like to further develop their understanding and knowledge of the field.