Download or read book Spatiotemporal Modeling of Influenza written by William E. Schiesser and published by Morgan & Claypool Publishers. This book was released on 2019-05-06 with total page 113 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book has a two-fold purpose: An introduction to the computer-based modeling of influenza, a continuing major worldwide communicable disease. The use of (1) as an illustration of a methodology for the computer-based modeling of communicable diseases. For the purposes of (1) and (2), a basic influenza model is formulated as a system of partial differential equations (PDEs) that define the spatiotemporal evolution of four populations: susceptibles, untreated and treated infecteds, and recovereds. The requirements of a well-posed PDE model are considered, including the initial and boundary conditions. The terms of the PDEs are explained. The computer implementation of the model is illustrated with a detailed line-by-line explanation of a system of routines in R (a quality, open-source scientific computing system that is readily available from the Internet). The R routines demonstrate the straightforward numerical solution of a system of nonlinear PDEs by the method of lines (MOL), an established general algorithm for PDEs. The presentation of the PDE modeling methodology is introductory with a minumum of formal mathematics (no theorems and proofs), and with emphasis on example applications. The intent of the book is to assist in the initial understanding and use of PDE mathematical modeling of communicable diseases, and the explanation and interpretation of the computed model solutions, as illustrated with the influenza model.
Download or read book Spatiotemporal Modeling of Influenza written by William E. Schiesser and published by Springer Nature. This book was released on 2022-05-31 with total page 97 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book has a two-fold purpose: (1) An introduction to the computer-based modeling of influenza, a continuing major worldwide communicable disease. (2) The use of (1) as an illustration of a methodology for the computer-based modeling of communicable diseases. For the purposes of (1) and (2), a basic influenza model is formulated as a system of partial differential equations (PDEs) that define the spatiotemporal evolution of four populations: susceptibles, untreated and treated infecteds, and recovereds. The requirements of a well-posed PDE model are considered, including the initial and boundary conditions. The terms of the PDEs are explained. The computer implementation of the model is illustrated with a detailed line-by-line explanation of a system of routines in R (a quality, open-source scientific computing system that is readily available from the Internet). The R routines demonstrate the straightforward numerical solution of a system of nonlinear PDEs by the method of lines (MOL), an established general algorithm for PDEs. The presentation of the PDE modeling methodology is introductory with a minumum of formal mathematics (no theorems and proofs), and with emphasis on example applications. The intent of the book is to assist in the initial understanding and use of PDE mathematical modeling of communicable diseases, and the explanation and interpretation of the computed model solutions, as illustrated with the influenza model.
Download or read book Spatiotemporal Stochastic Modeling of Influenza Virus Infection in Human Lung Epithelial Cells written by Aleya Dhanji and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Respiratory epithelial cells are an important, initial target of the human influenza A virus during infection. An important question arises as to what factors determine whether the innate immune response of these cells is able to contain the infection. This is determined by the complex interplay of viral replication (where the virus hijacks the host cell machinery to replicate itself and ultimately infect other cells), the immune response (which detects, contains and eliminates the virus both through intracellular responses to limit viral replication and through intercellular communication by diffusing cytokines to trigger an antiviral response in uninfected cells) and viral antagonism (where the virus has evolved to counteract the host immune response). All these processes occur on different timescales from minutes to hours and on different length scales from subcellular to across a large population of cells. How this complex spatio-temporal dynamics determines the outcome of the competition between viral replication and immune response on the scale of days and at the level of tissues remains an open problem.
Download or read book Spatio Temporal Modeling for Peak Events of Seasonal Influenza written by Ying Wang and published by . This book was released on 2014 with total page 102 pages. Available in PDF, EPUB and Kindle. Book excerpt: Influenza is one of the most common infectious diseases with respect to its ability to easily spread from person to person and result in severe complications, or even death. For a typical season, influenza activity often peaks in one, or several weeks which incorporate a high proportion of the cases in an outbreak, and are referred to variously as "peak events", or "peak weeks". To address the significance of peak events behind the seasonal nature of influenza outbreaks, multidisciplinary research has been advocated for investigating the impacts of weather conditions on the occurrence of peak events. Taking 16 Florida counties as a study area, this research provides a series of innovative statistical analysis aiming to: 1) derive an unambiguous and practical definition of Influenza-like Illness (ILI) peak events and statistically characterize their properties extracted from limited historic ILI records, including: annual event density, their timing, magnitude over prescribed thresholds, and duration; 2) identify fine-scale time lags between weather fluctuations and ILI peak activity for various age groups in terms of the established definition of peak events; 3) investigate interplay among daily weather conditions, climate divisions, properties of peak events and daily ILI activity during peak events for age-specific groups in Florida based on the identified time lags. The conceptual framework and satisfactory results of this research will aid public health professionals in improving surveillance and determining optimal periods for cost-effective intervention strategies.
Download or read book Modelling Pandemic Influenza Progression Using Spatiotemporal Epidemiological Modeller STEM written by Hui Zhang (S. M.) and published by . This book was released on 2009 with total page 75 pages. Available in PDF, EPUB and Kindle. Book excerpt: The purpose of this project is to incorporate a Poisson disease model into the Spatiotemporal Epidemiological Modeler (STEM) and visualize the disease spread on Google Earth. It is done through developing a Poisson disease model plug-in using the Eclipse Modeling Framework (EMF), a modeling framework and code generation facility for building tools and other applications based on a structured data model. The project consists of two stages. First, it develops a disease model plug-in of a Poisson disease model of a homogenous population, which is built as an extension of the implemented SI disease model in the STEM. Next, it proposes an algorithm to port a Poisson disease model of a heterogeneous population into the STEM. The development of the two new diseases plugins explores the maximum compatibility of the STEM and sets model for potential users to flexibly construct their own disease model for simulation.
Download or read book Analyzing and Modeling Spatial and Temporal Dynamics of Infectious Diseases written by Dongmei Chen and published by John Wiley & Sons. This book was released on 2014-12-08 with total page 496 pages. Available in PDF, EPUB and Kindle. Book excerpt: Features modern research and methodology on the spread of infectious diseases and showcases a broad range of multi-disciplinary and state-of-the-art techniques on geo-simulation, geo-visualization, remote sensing, metapopulation modeling, cloud computing, and pattern analysis Given the ongoing risk of infectious diseases worldwide, it is crucial to develop appropriate analysis methods, models, and tools to assess and predict the spread of disease and evaluate the risk. Analyzing and Modeling Spatial and Temporal Dynamics of Infectious Diseases features mathematical and spatial modeling approaches that integrate applications from various fields such as geo-computation and simulation, spatial analytics, mathematics, statistics, epidemiology, and health policy. In addition, the book captures the latest advances in the use of geographic information system (GIS), global positioning system (GPS), and other location-based technologies in the spatial and temporal study of infectious diseases. Highlighting the current practices and methodology via various infectious disease studies, Analyzing and Modeling Spatial and Temporal Dynamics of Infectious Diseases features: Approaches to better use infectious disease data collected from various sources for analysis and modeling purposes Examples of disease spreading dynamics, including West Nile virus, bird flu, Lyme disease, pandemic influenza (H1N1), and schistosomiasis Modern techniques such as Smartphone use in spatio-temporal usage data, cloud computing-enabled cluster detection, and communicable disease geo-simulation based on human mobility An overview of different mathematical, statistical, spatial modeling, and geo-simulation techniques Analyzing and Modeling Spatial and Temporal Dynamics of Infectious Diseases is an excellent resource for researchers and scientists who use, manage, or analyze infectious disease data, need to learn various traditional and advanced analytical methods and modeling techniques, and become aware of different issues and challenges related to infectious disease modeling and simulation. The book is also a useful textbook and/or supplement for upper-undergraduate and graduate-level courses in bioinformatics, biostatistics, public health and policy, and epidemiology.
Download or read book Spatio temporal Prediction Modeling of Clusters of Influenza Cases written by Weiyu Qiu and published by . This book was released on 2011 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Spatial Aspects of Influenza Epidemics written by Andrew David Cliff and published by Routledge. This book was released on 1986 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Influenza Models written by P. Selby and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 239 pages. Available in PDF, EPUB and Kindle. Book excerpt: Kilbourne (1973) described the student of influenza as "continually looking back over his shoulder and asking 'what happened?', in the hope that understanding of past events will alert him to the catastrophies ofthe future". Experience suggests the futility of such a hope, since the most predictable feature of influenza is its unpredictability. Nonetheless, the stubborn viabil ity of this hope is strongly affirmed by the many attempts, described and discussed in this volume, to develop a useful and practical representation of influenza virus behavior. I hasten to add, however, that the desired model has yet to be perfected. The existence and usefulness of animal models of infectious diseases of man are well documented. Reproduction of disease by infecting an experimental animal satisfies the third of Koch's four postulates to establish proof of disease causation by a specific bacterium. Animal models also have been extremely useful in studies of the pathogenesis, immunoprophylaxis, and specific therapy of several important diseases, ineluding (with only modest success) influenza. Development of such a model is simple, at least in concept. and can be achieved by one or only a few scientists.
Download or read book Spatio temporal Prediction Modeling of Clusters of Influenza Cases in Edmonton written by Weiyu Qiu and published by . This book was released on 2011 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Spatio temporal Dynamics of the 1918 Influenza Pandemic written by and published by . This book was released on 2011 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Spatio temporal Point Process Models for the Spread of Avian In0 uenza Virus H5N1 written by Harry Kim and published by . This book was released on 2011 with total page 214 pages. Available in PDF, EPUB and Kindle. Book excerpt: An outbreak of the devastating avian influenza virus (H5N1) was first observed in China in 1996. The explosive re-emergence of the virus after 7 years of its debut is estimated to be responsible for 14 million poultry deaths globally. Our research aims to identify the key factors (such as promixities to cities and roads and temperature) that are associated with the spread of H5N1 in Turkey and quantify their relationships to the virus dispersal. Our statistical model, the EAI (Epidemic Avian Influenza) model, is based on self-exciting point processes inspired by Hawkes and Ogata. A self-exciting point process can incorporate spatial and temporal dependencies of H5N1 outbreaks by specifying a branching structure among the outbreaks. In addition to quantifying the relationship between the virus spread and the key factors, the estimation result of the EAI model is used to predict future flu occurences.
Download or read book The Geographic Spread of Infectious Diseases written by Lisa Sattenspiel and published by Princeton University Press. This book was released on 2009-07-26 with total page 299 pages. Available in PDF, EPUB and Kindle. Book excerpt: The 1918-19 influenza epidemic killed more than fifty million people worldwide. The SARS epidemic of 2002-3, by comparison, killed fewer than a thousand. The success in containing the spread of SARS was due largely to the rapid global response of public health authorities, which was aided by insights resulting from mathematical models. Models enabled authorities to better understand how the disease spread and to assess the relative effectiveness of different control strategies. In this book, Lisa Sattenspiel and Alun Lloyd provide a comprehensive introduction to mathematical models in epidemiology and show how they can be used to predict and control the geographic spread of major infectious diseases. Key concepts in infectious disease modeling are explained, readers are guided from simple mathematical models to more complex ones, and the strengths and weaknesses of these models are explored. The book highlights the breadth of techniques available to modelers today, such as population-based and individual-based models, and covers specific applications as well. Sattenspiel and Lloyd examine the powerful mathematical models that health authorities have developed to understand the spatial distribution and geographic spread of influenza, measles, foot-and-mouth disease, and SARS. Analytic methods geographers use to study human infectious diseases and the dynamics of epidemics are also discussed. A must-read for students, researchers, and practitioners, no other book provides such an accessible introduction to this exciting and fast-evolving field.
Download or read book Modeling Transmission Mechanisms of Pandemic 2009 A H1N1 in California written by Tanya Wilcox and published by . This book was released on 2011 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Using R for Bayesian Spatial and Spatio Temporal Health Modeling written by Andrew B. Lawson and published by CRC Press. This book was released on 2021-04-28 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: Progressively more and more attention has been paid to how location affects health outcomes. The area of disease mapping focusses on these problems, and the Bayesian paradigm has a major role to play in the understanding of the complex interplay of context and individual predisposition in such studies of disease. Using R for Bayesian Spatial and Spatio-Temporal Health Modeling provides a major resource for those interested in applying Bayesian methodology in small area health data studies. Features: Review of R graphics relevant to spatial health data Overview of Bayesian methods and Bayesian hierarchical modeling as applied to spatial data Bayesian Computation and goodness-of-fit Review of basic Bayesian disease mapping models Spatio-temporal modeling with MCMC and INLA Special topics include multivariate models, survival analysis, missing data, measurement error, variable selection, individual event modeling, and infectious disease modeling Software for fitting models based on BRugs, Nimble, CARBayes and INLA Provides code relevant to fitting all examples throughout the book at a supplementary website The book fills a void in the literature and available software, providing a crucial link for students and professionals alike to engage in the analysis of spatial and spatio-temporal health data from a Bayesian perspective using R. The book emphasizes the use of MCMC via Nimble, BRugs, and CARBAyes, but also includes INLA for comparative purposes. In addition, a wide range of packages useful in the analysis of geo-referenced spatial data are employed and code is provided. It will likely become a key reference for researchers and students from biostatistics, epidemiology, public health, and environmental science.
Download or read book Spatial Dynamics and Pattern Formation in Biological Populations written by Ranjit Kumar Upadhyay and published by CRC Press. This book was released on 2021-02-23 with total page 449 pages. Available in PDF, EPUB and Kindle. Book excerpt: Covers the fundamental concepts and mathematical skills required to analyse reaction-diffusion models for biological populations. Focuses on mathematical modeling and numerical simulations using basic conceptual and classic models of population dynamics, Virus and Brain dynamics. Covers wide range of models using spatial and non-spatial approaches. Covers single, two and multispecies reaction-diffusion models from ecology and models from bio-chemistry. Uses Mathematica for problem solving and MATLAB for pattern formations. Contains solved Examples and Problems in Exercises.
Download or read book Spatial Dynamics and Pattern Formation in Biological Populations written by Ranjit Kumar Upadhyay and published by Chapman & Hall/CRC. This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book provides an introduction to deterministic (and some stochastic) modeling of spatiotemporal phenomena in ecology, epidemiology, and neural systems. A survey of the classical models in the fields with up to date applications is given. The book begins with detailed description of how spatial dynamics/diffusive processes influence the dynamics of biological populations. These processes play a key role in understanding the outbreak and spread of pandemics which help us in designing the control strategies from the public health perspective. A brief discussion on the functional mechanism of the brain (single neuron models and network level) with classical models of neuronal dynamics in space and time is given. Relevant phenomena and existing modeling approaches in ecology, epidemiology and neuroscience are introduced, which provide examples of pattern formation in these models. The analysis of patterns enables us to study the dynamics of macroscopic and microscopic behaviour of underlying systems and travelling wave type patterns observed in dispersive systems. Moving on to virus dynamics, authors present a detailed analysis of different types models of infectious diseases including two models for influenza, five models for Ebola virus and seven models for Zika virus with diffusion and time delay. A Chapter is devoted for the study of Brain Dynamics (Neural systems in space and time). Significant advances made in modeling the reaction-diffusion systems are presented and spatiotemporal patterning in the systems is reviewed. Development of appropriate mathematical models and detailed analysis (such as linear stability, weakly nonlinear analysis, bifurcation analysis, control theory, numerical simulation) are presented. Key Features Covers the fundamental concepts and mathematical skills required to analyse reaction-diffusion models for biological populations. Concepts are introduced in such a way that readers with a basic knowledge of differential equations and numerical methods can understand the analysis. The results are also illustrated with figures. Focuses on mathematical modeling and numerical simulations using basic conceptual and classic models of population dynamics, Virus and Brain dynamics. Covers wide range of models using spatial and non-spatial approaches. Covers single, two and multispecies reaction-diffusion models from ecology and models from bio-chemistry. Models are analysed for stability of equilibrium points, Turing instability, Hopf bifurcation and pattern formations. Uses Mathematica for problem solving and MATLAB for pattern formations. Contains solved Examples and Problems in Exercises. The Book is suitable for advanced undergraduate, graduate and research students. For those who are working in the above areas, it provides information from most of the recent works. The text presents all the fundamental concepts and mathematical skills needed to build models and perform analyses.
