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 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 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 Mathematical and statistical modeling of infection and transmission dynamics of viral diseases written by Pierre Magal and published by Frontiers Media SA. This book was released on 2023-10-30 with total page 170 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Twitter A Digital Socioscope written by Michael W. Macy and published by Cambridge University Press. This book was released on 2015-05-05 with total page 185 pages. Available in PDF, EPUB and Kindle. Book excerpt: A resource for social scientists on how Twitter data can be used to study individual behavior and social interaction.
Download or read book Advances in Minimum Description Length written by Peter D. Grünwald and published by MIT Press. This book was released on 2005 with total page 464 pages. Available in PDF, EPUB and Kindle. Book excerpt: A source book for state-of-the-art MDL, including an extensive tutorial and recent theoretical advances and practical applications in fields ranging from bioinformatics to psychology.
Download or read book Artificial Intelligence in Medicine written by Lei Xing and published by Academic Press. This book was released on 2020-09-03 with total page 570 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence Medicine: Technical Basis and Clinical Applications presents a comprehensive overview of the field, ranging from its history and technical foundations, to specific clinical applications and finally to prospects. Artificial Intelligence (AI) is expanding across all domains at a breakneck speed. Medicine, with the availability of large multidimensional datasets, lends itself to strong potential advancement with the appropriate harnessing of AI. The integration of AI can occur throughout the continuum of medicine: from basic laboratory discovery to clinical application and healthcare delivery. Integrating AI within medicine has been met with both excitement and scepticism. By understanding how AI works, and developing an appreciation for both limitations and strengths, clinicians can harness its computational power to streamline workflow and improve patient care. It also provides the opportunity to improve upon research methodologies beyond what is currently available using traditional statistical approaches. On the other hand, computers scientists and data analysts can provide solutions, but often lack easy access to clinical insight that may help focus their efforts. This book provides vital background knowledge to help bring these two groups together, and to engage in more streamlined dialogue to yield productive collaborative solutions in the field of medicine. Provides history and overview of artificial intelligence, as narrated by pioneers in the field Discusses broad and deep background and updates on recent advances in both medicine and artificial intelligence that enabled the application of artificial intelligence Addresses the ever-expanding application of this novel technology and discusses some of the unique challenges associated with such an approach
Download or read book Modeling the Interplay Between Human Behavior and the Spread of Infectious Diseases written by Piero Manfredi and published by Springer Science & Business Media. This book was released on 2013-01-04 with total page 329 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume summarizes the state-of-the-art in the fast growing research area of modeling the influence of information-driven human behavior on the spread and control of infectious diseases. In particular, it features the two main and inter-related “core” topics: behavioral changes in response to global threats, for example, pandemic influenza, and the pseudo-rational opposition to vaccines. In order to make realistic predictions, modelers need to go beyond classical mathematical epidemiology to take these dynamic effects into account. With contributions from experts in this field, the book fills a void in the literature. It goes beyond classical texts, yet preserves the rationale of many of them by sticking to the underlying biology without compromising on scientific rigor. Epidemiologists, theoretical biologists, biophysicists, applied mathematicians, and PhD students will benefit from this book. However, it is also written for Public Health professionals interested in understanding models, and to advanced undergraduate students, since it only requires a working knowledge of mathematical epidemiology.
Download or read book Spatio Temporal Statistics with R written by Christopher K. Wikle and published by CRC Press. This book was released on 2019-02-18 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: The world is becoming increasingly complex, with larger quantities of data available to be analyzed. It so happens that much of these "big data" that are available are spatio-temporal in nature, meaning that they can be indexed by their spatial locations and time stamps. Spatio-Temporal Statistics with R provides an accessible introduction to statistical analysis of spatio-temporal data, with hands-on applications of the statistical methods using R Labs found at the end of each chapter. The book: Gives a step-by-step approach to analyzing spatio-temporal data, starting with visualization, then statistical modelling, with an emphasis on hierarchical statistical models and basis function expansions, and finishing with model evaluation Provides a gradual entry to the methodological aspects of spatio-temporal statistics Provides broad coverage of using R as well as "R Tips" throughout. Features detailed examples and applications in end-of-chapter Labs Features "Technical Notes" throughout to provide additional technical detail where relevant Supplemented by a website featuring the associated R package, data, reviews, errata, a discussion forum, and more The book fills a void in the literature and available software, providing a bridge for students and researchers alike who wish to learn the basics of spatio-temporal statistics. It is written in an informal style and functions as a down-to-earth introduction to the subject. Any reader familiar with calculus-based probability and statistics, and who is comfortable with basic matrix-algebra representations of statistical models, would find this book easy to follow. The goal is to give as many people as possible the tools and confidence to analyze spatio-temporal data.
Download or read book Bayesian Modeling of Spatio Temporal Data with R written by Sujit Sahu and published by CRC Press. This book was released on 2022-02-23 with total page 385 pages. Available in PDF, EPUB and Kindle. Book excerpt: Applied sciences, both physical and social, such as atmospheric, biological, climate, demographic, economic, ecological, environmental, oceanic and political, routinely gather large volumes of spatial and spatio-temporal data in order to make wide ranging inference and prediction. Ideally such inferential tasks should be approached through modelling, which aids in estimation of uncertainties in all conclusions drawn from such data. Unified Bayesian modelling, implemented through user friendly software packages, provides a crucial key to unlocking the full power of these methods for solving challenging practical problems. Key features of the book: • Accessible detailed discussion of a majority of all aspects of Bayesian methods and computations with worked examples, numerical illustrations and exercises • A spatial statistics jargon buster chapter that enables the reader to build up a vocabulary without getting clouded in modeling and technicalities • Computation and modeling illustrations are provided with the help of the dedicated R package bmstdr, allowing the reader to use well-known packages and platforms, such as rstan, INLA, spBayes, spTimer, spTDyn, CARBayes, CARBayesST, etc • Included are R code notes detailing the algorithms used to produce all the tables and figures, with data and code available via an online supplement • Two dedicated chapters discuss practical examples of spatio-temporal modeling of point referenced and areal unit data • Throughout, the emphasis has been on validating models by splitting data into test and training sets following on the philosophy of machine learning and data science This book is designed to make spatio-temporal modeling and analysis accessible and understandable to a wide audience of students and researchers, from mathematicians and statisticians to practitioners in the applied sciences. It presents most of the modeling with the help of R commands written in a purposefully developed R package to facilitate spatio-temporal modeling. It does not compromise on rigour, as it presents the underlying theories of Bayesian inference and computation in standalone chapters, which would be appeal those interested in the theoretical details. By avoiding hard core mathematics and calculus, this book aims to be a bridge that removes the statistical knowledge gap from among the applied scientists.
Download or read book Next Generation Earth System Prediction written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2016-08-22 with total page 351 pages. Available in PDF, EPUB and Kindle. Book excerpt: As the nation's economic activities, security concerns, and stewardship of natural resources become increasingly complex and globally interrelated, they become ever more sensitive to adverse impacts from weather, climate, and other natural phenomena. For several decades, forecasts with lead times of a few days for weather and other environmental phenomena have yielded valuable information to improve decision-making across all sectors of society. Developing the capability to forecast environmental conditions and disruptive events several weeks and months in advance could dramatically increase the value and benefit of environmental predictions, saving lives, protecting property, increasing economic vitality, protecting the environment, and informing policy choices. Over the past decade, the ability to forecast weather and climate conditions on subseasonal to seasonal (S2S) timescales, i.e., two to fifty-two weeks in advance, has improved substantially. Although significant progress has been made, much work remains to make S2S predictions skillful enough, as well as optimally tailored and communicated, to enable widespread use. Next Generation Earth System Predictions presents a ten-year U.S. research agenda that increases the nation's S2S research and modeling capability, advances S2S forecasting, and aids in decision making at medium and extended lead times.
Download or read book Handbook of Infectious Disease Data Analysis written by Leonhard Held and published by CRC Press. This book was released on 2019-11-07 with total page 567 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent years have seen an explosion in new kinds of data on infectious diseases, including data on social contacts, whole genome sequences of pathogens, biomarkers for susceptibility to infection, serological panel data, and surveillance data. The Handbook of Infectious Disease Data Analysis provides an overview of many key statistical methods that have been developed in response to such new data streams and the associated ability to address key scientific and epidemiological questions. A unique feature of the Handbook is the wide range of topics covered. Key features Contributors include many leading researchers in the field Divided into four main sections: Basic concepts, Analysis of Outbreak Data, Analysis of Seroprevalence Data, Analysis of Surveillance Data Numerous case studies and examples throughout Provides both introductory material and key reference material
Download or read book Attribution of Extreme Weather Events in the Context of Climate Change written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2016-07-28 with total page 187 pages. Available in PDF, EPUB and Kindle. Book excerpt: As climate has warmed over recent years, a new pattern of more frequent and more intense weather events has unfolded across the globe. Climate models simulate such changes in extreme events, and some of the reasons for the changes are well understood. Warming increases the likelihood of extremely hot days and nights, favors increased atmospheric moisture that may result in more frequent heavy rainfall and snowfall, and leads to evaporation that can exacerbate droughts. Even with evidence of these broad trends, scientists cautioned in the past that individual weather events couldn't be attributed to climate change. Now, with advances in understanding the climate science behind extreme events and the science of extreme event attribution, such blanket statements may not be accurate. The relatively young science of extreme event attribution seeks to tease out the influence of human-cause climate change from other factors, such as natural sources of variability like El Niño, as contributors to individual extreme events. Event attribution can answer questions about how much climate change influenced the probability or intensity of a specific type of weather event. As event attribution capabilities improve, they could help inform choices about assessing and managing risk, and in guiding climate adaptation strategies. This report examines the current state of science of extreme weather attribution, and identifies ways to move the science forward to improve attribution capabilities.
Download or read book Emerging Viral Diseases written by Institute of Medicine and published by National Academies Press. This book was released on 2015-03-19 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the past half century, deadly disease outbreaks caused by novel viruses of animal origin - Nipah virus in Malaysia, Hendra virus in Australia, Hantavirus in the United States, Ebola virus in Africa, along with HIV (human immunodeficiency virus), several influenza subtypes, and the SARS (sudden acute respiratory syndrome) and MERS (Middle East respiratory syndrome) coronaviruses - have underscored the urgency of understanding factors influencing viral disease emergence and spread. Emerging Viral Diseases is the summary of a public workshop hosted in March 2014 to examine factors driving the appearance, establishment, and spread of emerging, re-emerging and novel viral diseases; the global health and economic impacts of recently emerging and novel viral diseases in humans; and the scientific and policy approaches to improving domestic and international capacity to detect and respond to global outbreaks of infectious disease. This report is a record of the presentations and discussion of the event.
Download or read book Epidemics written by Ottar N. Bjørnstad and published by Springer. This book was released on 2018-10-30 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is designed to be a practical study in infectious disease dynamics. The book offers an easy to follow implementation and analysis of mathematical epidemiology. The book focuses on recent case studies in order to explore various conceptual, mathematical, and statistical issues. The dynamics of infectious diseases shows a wide diversity of pattern. Some have locally persistent chains-of-transmission, others persist spatially in ‘consumer-resource metapopulations’. Some infections are prevalent among the young, some among the old and some are age-invariant. Temporally, some diseases have little variation in prevalence, some have predictable seasonal shifts and others exhibit violent epidemics that may be regular or irregular in their timing. Models and ‘models-with-data’ have proved invaluable for understanding and predicting this diversity, and thence help improve intervention and control. Using mathematical models to understand infectious disease dynamics has a very rich history in epidemiology. The field has seen broad expansions of theories as well as a surge in real-life application of mathematics to dynamics and control of infectious disease. The chapters of Epidemics: Models and Data using R have been organized in a reasonably logical way: Chapters 1-10 is a mix and match of models, data and statistics pertaining to local disease dynamics; Chapters 11-13 pertains to spatial and spatiotemporal dynamics; Chapter 14 highlights similarities between the dynamics of infectious disease and parasitoid-host dynamics; Finally, Chapters 15 and 16 overview additional statistical methodology useful in studies of infectious disease dynamics. This book can be used as a guide for working with data, models and ‘models-and-data’ to understand epidemics and infectious disease dynamics in space and time.
Download or read book Stochastic Population Models in Ecology and Epidemiology written by Maurice Stevenson Bartlett and published by . This book was released on 1960 with total page 108 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Analysing Seasonal Health Data written by Adrian G. Barnett and published by Springer Science & Business Media. This book was released on 2010-01-08 with total page 174 pages. Available in PDF, EPUB and Kindle. Book excerpt: Seasonal patterns have been found in a remarkable range of health conditions, including birth defects, respiratory infections and cardiovascular disease. Accurately estimating the size and timing of seasonal peaks in disease incidence is an aid to understanding the causes and possibly to developing interventions. With global warming increasing the intensity of seasonal weather patterns around the world, a review of the methods for estimating seasonal effects on health is timely. This is the first book on statistical methods for seasonal data written for a health audience. It describes methods for a range of outcomes (including continuous, count and binomial data) and demonstrates appropriate techniques for summarising and modelling these data. It has a practical focus and uses interesting examples to motivate and illustrate the methods. The statistical procedures and example data sets are available in an R package called ‘season’.
