Single-Arm Phase II Survival Trial Design provides a comprehensive summary to the most commonly- used methods for single-arm phase II trial design with time-to-event endpoints. Single-arm phase II trials are a key component for successfully developing advanced cancer drugs and treatments, particular for target therapy and immunotherapy in which time-to-event endpoints are often the primary endpoints. Most test statistics for single-arm phase II trial design with time-to-event endpoints are not available in commercial software. Key Features: Covers the most frequently used methods for single-arm phase II trial design with time-to-event endpoints in a comprehensive fashion. Provides new material on phase II immunotherapy trial design and phase II trial design with TTP ratio endpoint. Illustrates trial designs by real clinical trial examples Includes R code for all methods proposed in the book, enabling straightforward sample size calculation.

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.

Signal Detection for Medical Scientists: Likelihood Ratio Based Test-Based Methodology presents the data mining techniques with focus on likelihood ratio test (LRT) based methods for signal detection. It emphasizes computational aspect of LRT methodology and is pertinent for first-time researchers and graduate students venturing into this interesting field. The book is written as a reference book for professionals in pharmaceutical industry, manufactures of medical devices, and regulatory agencies. The book deals with the signal detection in drug/device evaluation, which is important in the post-market evaluation of medical products, and in the pre-market signal detection during clinical trials for monitoring procedures. It should also appeal to academic researchers, and faculty members in mathematics, statistics, biostatistics, data science, pharmacology, engineering, epidemiology, and public health. Therefore, this book is well suited for both research and teaching. Key Features: Includes a balanced discussion of art of data structure, issues in signal detection, statistical methods and analytics, and implementation of the methods. Provides a comprehensive summary of the LRT methods for signal detection including the basic theory and extensions for varying datasets that may be large post-market data or pre-market clinical trial data. Contains details of scientific background, statistical methods, and associated algorithms that a reader can quickly master the materials and apply methods in the book on one's own problems

Statistical methods that are commonly used in the review and approval process of regulatory submissions are usually referred to as statistics in regulatory science or regulatory statistics. In a broader sense, statistics in regulatory science can be defined as valid statistics that are employed in the review and approval process of regulatory submissions of pharmaceutical products. In addition, statistics in regulatory science are involved with the development of regulatory policy, guidance, and regulatory critical clinical initiatives related research. This book is devoted to the discussion of statistics in regulatory science for pharmaceutical development. It covers practical issues that are commonly encountered in regulatory science of pharmaceutical research and development including topics related to research activities, review of regulatory submissions, recent critical clinical initiatives, and policy/guidance development in regulatory science. Devoted entirely to discussing statistics in regulatory science for pharmaceutical development. Reviews critical issues (e.g., endpoint/margin selection and complex innovative design such as adaptive trial design) in the pharmaceutical development and regulatory approval process. Clarifies controversial statistical issues (e.g., hypothesis testing versus confidence interval approach, missing data/estimands, multiplicity, and Bayesian design and approach) in review/approval of regulatory submissions. Proposes innovative thinking regarding study designs and statistical methods (e.g., n-of-1 trial design, adaptive trial design, and probability monitoring procedure for sample size) for rare disease drug development. Provides insight regarding current regulatory clinical initiatives (e.g., precision/personalized medicine, biomarker-driven target clinical trials, model informed drug development, big data analytics, and real world data/evidence). This book provides key statistical concepts, innovative designs, and analysis methods that are useful in regulatory science. Also included are some practical, challenging, and controversial issues that are commonly seen in the review and approval process of regulatory submissions. About the author Shein-Chung Chow, Ph.D. is currently a Professor at Duke University School of Medicine, Durham, NC. He was previously the Associate Director at the Office of Biostatistics, Center for Drug Evaluation and Research, United States Food and Drug Administration (FDA). Dr. Chow has also held various positions in the pharmaceutical industry such as Vice President at Millennium, Cambridge, MA, Executive Director at Covance, Princeton, NJ, and Director and Department Head at Bristol-Myers Squibb, Plainsboro, NJ. He was elected Fellow of the American Statistical Association and an elected member of the ISI (International Statistical Institute). Dr. Chow is Editor-in-Chief of the Journal of Biopharmaceutical Statistics and Biostatistics Book Series, Chapman and Hall/CRC Press, Taylor & Francis, New York. Dr. Chow is the author or co-author of over 300 methodology papers and 30 books.

Identifying the existing challenges and shortfalls of China's current HIV/AIDS programming, this book provides an understanding of the history of HIV/AIDS in China, comparing government responses to global best practice in prevention and treatment. Considering three key populations in China, namely, female sex workers, people who inject drugs and floating migrants, Living in the Shadows of China's HIV/AIDS Epidemics highlights the effects of high mobility and marginalisation on the spread of HIV in China. It is argued that these groups often suffer from stigmatisation and a lack of human security, resulting in sub-optimal outcomes for HIV/AIDS intervention and prevention efforts and the reinforcement of high-risk behaviours, further contributing to the transmission of the virus to the general population. In adding to the emerging body of literature, this book further elucidates the myriad of challenges posed by HIV/AIDS epidemics, allowing sustained engagement and a fresh insight into how governments might respond to the needs of individuals living with HIV/AIDS, both in China and globally. Including case studies which give voice to research participants in a rich and engaging way, this book will appeal to students and scholars of Chinese Studies, Asian Studies, International Relations and Political Science, as well as those engaged in epidemiological studies in the Health Sciences.

"This is truly an outstanding book. [It] brings together all of the latest research in clinical trials methodology and how it can be applied to drug development.... Chang et al provide applications to industry-supported trials. This will allow statisticians in the industry community to take these methods seriously." Jay Herson, Johns Hopkins University The pharmaceutical industry's approach to drug discovery and development has rapidly transformed in the last decade from the more traditional Research and Development (R & D) approach to a more innovative approach in which strategies are employed to compress and optimize the clinical development plan and associated timelines. However, these strategies are generally being considered on an individual trial basis and not as part of a fully integrated overall development program. Such optimization at the trial level is somewhat near-sighted and does not ensure cost, time, or development efficiency of the overall program. This book seeks to address this imbalance by establishing a statistical framework for overall/global clinical development optimization and providing tactics and techniques to support such optimization, including clinical trial simulations. Provides a statistical framework for achieve global optimization in each phase of the drug development process. Describes specific techniques to support optimization including adaptive designs, precision medicine, survival-endpoints, dose finding and multiple testing. Gives practical approaches to handling missing data in clinical trials using SAS. Looks at key controversial issues from both a clinical and statistical perspective. Presents a generous number of case studies from multiple therapeutic areas that help motivate and illustrate the statistical methods introduced in the book. Puts great emphasis on software implementation of the statistical methods with multiple examples of software code (both SAS and R). It is important for statisticians to possess a deep knowledge of the drug development process beyond statistical considerations. For these reasons, this book incorporates both statistical and "clinical/medical" perspectives.

The world continues to lose more than a million lives each year to the HIV epidemic, and nearly two million individuals were infected with HIV in 2017 alone. The new Sustainable Development Goals, adopted by countries of the United Nations in September 2015, include a commitment to end the AIDS epidemic by 2030. Considerable emphasis on prevention of new infections and treatment of those living with HIV will be needed to make this goal achievable. With nearly 37 million people now living with HIV, it is a communicable disease that behaves like a noncommunicable disease. Nutritional management is integral to comprehensive HIV care and treatment. Improved nutritional status and weight gain can increase recovery and strength of individuals living with HIV/AIDS, improve dietary diversity and caloric intake, and improve quality of life. This book highlights evidence-based research linking nutrition and HIV and identifies research gaps to inform the development of guidelines and policies for the United Nations' Sustainable Development Goals. A comprehensive approach that includes nutritional interventions is likely to maximize the benefit of antiretroviral therapy in preventing HIV disease progression and other adverse outcomes in HIV-infected men and women. Modification of nutritional status has been shown to enhance the quality of life of those suffering HIV/AIDS, both physically in terms of improved body mass index and immunological markers, and psychologically, by improving symptoms of depression. While the primary focus for those infected should remain on antiretroviral treatment and increasing its availability and coverage, improvement of nutritional status plays a complementary role in the management of HIV infection.

Self-Controlled Case Series Studies: A Modelling Guide with R provides the first comprehensive account of the self-controlled case series (SCCS) method, a statistical technique for investigating associations between outcome events and time-varying exposures. The method only requires information from individuals who have experienced the event of interest, and automatically controls for multiplicative time-invariant confounders, even when these are unmeasured or unknown. It is increasingly being used in epidemiology, most frequently to study the safety of vaccines and pharmaceutical drugs. Key features of the book include: A thorough yet accessible description of the SCCS method, with mathematical details provided in separate starred sections. Comprehensive discussion of assumptions and how they may be verified. A detailed account of different SCCS models, extensions of the SCCS method, and the design of SCCS studies. Extensive practical illustrations and worked examples from epidemiology. Full computer code from the associated R package SCCS, which includes all the data sets used in the book. The book is aimed at a broad range of readers, including epidemiologists and medical statisticians who wish to use the SCCS method, and also researchers with an interest in statistical methodology. The three authors have been closely involved with the inception, development, popularisation and programming of the SCCS method.

With ever-rising healthcare costs, evidence generation through Health Economics and Outcomes Research (HEOR) plays an increasingly important role in decision-making about the allocation of resources. Accordingly, it is now customary for health technology assessment and reimbursement agencies to request for HEOR evidence, in addition to data from clinical trials, to inform decisions about patient access to new treatment options. While there is a great deal of literature on HEOR, there is a need for a volume that presents a coherent and unified review of the major issues that arise in application, especially from a statistical perspective. Statistical Topics in Health Economics and Outcomes Research fulfils that need by presenting an overview of the key analytical issues and best practice. Special attention is paid to key assumptions and other salient features of statistical methods customarily used in the area, and appropriate and relatively comprehensive references are made to emerging trends. The content of the book is purposefully designed to be accessible to readers with basic quantitative backgrounds, while providing an in-depth coverage of relatively complex statistical issues. The book will make a very useful reference for researchers in the pharmaceutical industry, academia, and research institutions involved with HEOR studies. The targeted readers may include statisticians, data scientists, epidemiologists, outcomes researchers, health economists, and healthcare policy and decision-makers.

Diet is a major factor in health and disease. Controlled, long-term studies in humans are impractical, and investigators have utilized long-term epidemiological investigations to study the contributions of diet to the human condition. Such studies, while valuable, have often been limited by contradictory findings; a limitation secondary to systematic errors in traditional self-reported dietary assessment tools that limit the percentage of variances in diseases explained by diet. New approaches are available to help overcome these limitations, and Advances in the Assessment of Dietary Intake is focused on these advances in an effort to provide more accurate dietary data to understand human health. Chapters cover the benefits and limitations of traditional self-report tools; strategies for improving the validity of dietary recall and food recording methods; objective methods to assess food and nutrient intake; assessment of timing and meal patterns using glucose sensors; and physical activity patterns using validated accelerometers. Advances in the Assessment of Dietary Intake describes new avenues to investigate the role of diet in human health and serves as the most up-to-date reference and teaching tool for these methods that will improve the accuracy of dietary assessment and lay the ground work for future studies.

The term health technology refers to drugs, devices, and programs that can improve and extend quality of life. As decision-makers struggle to find ways to reduce costs while improving health care delivery, health technology assessments (HTA) provide the evidence required to make better-informed decisions. This is the first book that focuses on the statistical options of HTAs, to fully capture the value of health improvements along with their associated economic consequences. After reading the book, readers will better understand why some health technologies receive regulatory or reimbursement approval while others do not, what can be done to improve the chances of approval, as well as common shortcomings of submissions for drug and device reimbursement. The book begins by contrasting the differences between regulatory approval and reimbursement approval. Next, it reviews the principles and steps for conducting an HTA, including the reasons why different agencies will have a different focus for their scope in the HTA. Supplying an accessible introduction to the various statistical options for different methods in an HTA, the book identifies the links to regulatory and reimbursement decisions for each option. It highlights many of the methodological advances that have occurred since HTA research began, to provide researchers and decision-makers with a cutting-edge framework. It also details the logical basis for the methods along with simple instructions on how to conduct the various techniques. Both authors have considerable experience in generating evidence for submissions and reviewing submissions to decision-makers for funding. One of the authors has also received a nationally recognized lifetime achievement award in this area.

1. Explains the clear role of geospatial data in managing pandemics. 2. Discusses Covid-19 and its relevance to location intelligence. 3. Includes a big population trajectory tracking and reasoning. 4. Analyses population behavior modeling and simulation, using location-based service. 5. Integrates community prevention, surveillance, and risk assessment.

Mendelian Randomization: Methods For Causal Inference Using Genetic Variants provides thorough coverage of the methods and practical elements of Mendelian randomization analysis. It brings together diverse aspects of Mendelian randomization from the fields of epidemiology, statistics, genetics, and bioinformatics. Through multiple examples, the first part of the book introduces the reader to the concept of Mendelian randomization, showing how to perform simple Mendelian randomization investigations and interpret the results. The second part of the book addresses specific methodological issues relevant to the practice of Mendelian randomization, including robust methods, weak instruments, multivariable methods, and power calculations. The authors present the theoretical aspects of these issues in an easy-to-understand way by using non-technical language. The last part of the book examines the potential for Mendelian randomization in the future, exploring both methodological and applied developments. Features Offers first-hand, in-depth guidance on Mendelian randomization from leaders in the field Makes the diverse aspects of Mendelian randomization understandable to newcomers Illustrates technical details using data from applied analyses Discusses possible future directions for research involving Mendelian randomization Software code is provided in the relevant chapters and is also available at the supplementary website This book gives epidemiologists, statisticians, geneticists, and bioinformaticians the foundation to understand how to use genetic variants as instrumental variables in observational data. New in Second Edition: The second edition of the book has been substantially re-written to reduce the amount of technical content, and emphasize practical consequences of theoretical issues. Extensive material on the use of two-sample Mendelian randomization and publicly-available summarized data has been added. The book now includes several real-world examples that show how Mendelian randomization can be used to address questions of disease aetiology, target validation, and drug development

Mendelian Randomization: Methods For Causal Inference Using Genetic Variants provides thorough coverage of the methods and practical elements of Mendelian randomization analysis. It brings together diverse aspects of Mendelian randomization from the fields of epidemiology, statistics, genetics, and bioinformatics. Through multiple examples, the first part of the book introduces the reader to the concept of Mendelian randomization, showing how to perform simple Mendelian randomization investigations and interpret the results. The second part of the book addresses specific methodological issues relevant to the practice of Mendelian randomization, including robust methods, weak instruments, multivariable methods, and power calculations. The authors present the theoretical aspects of these issues in an easy-to-understand way by using non-technical language. The last part of the book examines the potential for Mendelian randomization in the future, exploring both methodological and applied developments. Features Offers first-hand, in-depth guidance on Mendelian randomization from leaders in the field Makes the diverse aspects of Mendelian randomization understandable to newcomers Illustrates technical details using data from applied analyses Discusses possible future directions for research involving Mendelian randomization Software code is provided in the relevant chapters and is also available at the supplementary website This book gives epidemiologists, statisticians, geneticists, and bioinformaticians the foundation to understand how to use genetic variants as instrumental variables in observational data. New in Second Edition: The second edition of the book has been substantially re-written to reduce the amount of technical content, and emphasize practical consequences of theoretical issues. Extensive material on the use of two-sample Mendelian randomization and publicly-available summarized data has been added. The book now includes several real-world examples that show how Mendelian randomization can be used to address questions of disease aetiology, target validation, and drug development

This fascinating book gives readers an appreciation of how biomedical research should work and how the reality is all too often seriously flawed. Explaining the logical basis of the different research approaches used by biomedical research scientists and their relative merits, it will help readers to make more realistic appraisal of media reports linking aspects of lifestyle, environment or diet to health outcomes and thus judge whether such claims are a real effect worthy of consideration for behavior change or deserving of further research resources. Key features: increases awareness of research fraud and some of the characteristics of fraudulent science and scientific fraudsters shows that whilst outright fraud may be uncommon, fudging of results to help achieve statistical significance may be more prevalent incorporates real-life case studies highlighting some of the infamous cases of research fraud and major scientific mistakes and the impact that they have had provides a convenient overview of the research process in the biomedical sciences, with a focus on research strategy rather than individual methods find supplemental detail on the author's blog https://drgeoffnutrition.wordpress.com/about/ By raising awareness of the possibility that research data may have been dishonestly generated and outlining some of the signs and symptoms that might suggest data fabrication, Error and Fraud: The Dark Side of Biomedical Research will help students and researchers to identify the strengths and limitations of different research approaches and allow them to make a realistic evaluations of their own and others' research findings.

The fields of rare diseases research and orphan products development continue to expand with more products in research and development status. In recent years, the role of the patient advocacy groups has evolved into a research partner with the academic research community and the bio-pharmaceutical industry. Unique approaches to research and development require epidemiological data not previously available to assist in protocol study design and patient recruitment for clinical trials required by regulatory agencies prior to approval for access by patents and practicing physicians.

The Multiplayer Classroom: Game Plans is a companion to The Multiplayer Classroom: Designing Coursework as a Game, now in its second edition from CRC Press. This book covers four multiplayer classroom projects played in the real world in real time to teach and entertain. They were funded by grants or institutions, collaborations between Lee Sheldon, as writer/designer, and subject matter experts in various fields. They are written to be accessible to anyone--designer, educator, or layperson--interested in game-based learning. The subjects are increasingly relevant in this day and age: physical fitness, Mandarin, cybersecurity, and especially an online class exploring culture and identity on the internet that is unlike any online class you have ever seen. Read the annotated, often-suspenseful stories of how each game, with its unique challenges, thrills, and spills, was built. Lee Sheldon began his writing career in television as a writer-producer, eventually writing more than 200 shows ranging from Charlie's Angels (writer) to Edge of Night (head writer) to Star Trek: The Next Generation (writer-producer). Having written and designed more than forty commercial and applied video games, Lee spearheaded the first full writing for games concentration in North America at Rensselaer Polytechnic Institute and the second writing concentration at Worcester Polytechnic Institute. He is a regular lecturer and consultant on game design and writing in the United States and abroad. His most recent commercial game, the award-winning The Lion's Song, is currently on Steam. For the past two years he consulted on an "escape room in a box," funded by NASA, that gives visitors to hundreds of science museums and planetariums the opportunity to play colonizers on the moon. He is currently writing his second mystery novel.

The Multiplayer Classroom: Game Plans is a companion to The Multiplayer Classroom: Designing Coursework as a Game, now in its second edition from CRC Press. This book covers four multiplayer classroom projects played in the real world in real time to teach and entertain. They were funded by grants or institutions, collaborations between Lee Sheldon, as writer/designer, and subject matter experts in various fields. They are written to be accessible to anyone--designer, educator, or layperson--interested in game-based learning. The subjects are increasingly relevant in this day and age: physical fitness, Mandarin, cybersecurity, and especially an online class exploring culture and identity on the internet that is unlike any online class you have ever seen. Read the annotated, often-suspenseful stories of how each game, with its unique challenges, thrills, and spills, was built. Lee Sheldon began his writing career in television as a writer-producer, eventually writing more than 200 shows ranging from Charlie's Angels (writer) to Edge of Night (head writer) to Star Trek: The Next Generation (writer-producer). Having written and designed more than forty commercial and applied video games, Lee spearheaded the first full writing for games concentration in North America at Rensselaer Polytechnic Institute and the second writing concentration at Worcester Polytechnic Institute. He is a regular lecturer and consultant on game design and writing in the United States and abroad. His most recent commercial game, the award-winning The Lion's Song, is currently on Steam. For the past two years he consulted on an "escape room in a box," funded by NASA, that gives visitors to hundreds of science museums and planetariums the opportunity to play colonizers on the moon. He is currently writing his second mystery novel.

It is common practice to evaluate wastewater to understand drug consumption, from antibiotics to illegal narcotics, and even to analyze dietary habits and trends. Evaluating contaminants in wastewater enables researchers, environmental scientists, and water quality experts to gain valuable information and data. Wastewater-based epidemiology is an emerging science that has proven to be a cost- and time-effective biomonitoring tool. This book provides a roadmap for detecting wastewater-borne pathogenic contaminants such as viruses, bacteria, fungi, and others. It provides a basic, fundamental discussion of how sampling and monitoring of wastewater using epidemiological concepts and practices can aid in determining the presence of the COVID-19 virus in a community, for example, and may help predict future outbreaks. Features * Offers a unique discussion of the detection of bacteria, fungi, and COVID-19, and other viruses in wastewater * Presents the fundamentals of wastewater chemistry and microbiology * Explains biomonitoring, sampling, testing, and health surveillance in a practical manner Fundamentals of Wastewater-Based Epidemiology: Biomonitoring of Bacteria, Fungi, COVID-19, and Other Viruses is an invaluable resource to a wide array of readers with varying interests and backgrounds in water science and public health.

This book aims to offer a comprehensive and up-to-date overview of male stress urinary incontinence that will serve as a useful tool and reference for urologists, andrologists, physiotherapists, general practitioners, and nurses. Detailed information is provided on diagnostic workup, including clinical assessment and the role of urodynamic evaluations and other instrumental examinations, and on the full range of potential treatments, from conservative and pharmacological interventions to surgical options. In addition to careful descriptions of the surgical procedures themselves, clear advice is given on the management of iatrogenic complications of incontinence surgery. Helpful treatment algorithms and recommendations offer further practical support. Relevant background knowledge is provided in expert reviews of topics such as the functional anatomy of the male pelvis and the pathophysiology, epidemiology, and classification of male urinary incontinence.

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.

The average age of the world's population is increasing at an unprecedented rate and this increase is changing the world. This "Silver tsunami" emphasizes the need to provide advanced training in epidemiology and increase the cadre of experts in the study of aging. This book is designed to summarize unique methodological issues relevant to the study of aging, biomarkers of aging and the biology/physiology of aging and in-depth discussions of the etiology and epidemiology of common geriatric syndromes and diseases. Contributing authors in the book represent many disciplines, not only epidemiology and clinical geriatrics, but also demography, health services, research, cardiovascular disease, diabetes, psychiatry, neurology, social services, musculoskeletal diseases and cancer. The aim of the book is to provide a broad multidisciplinary background for any student/researcher interested in aging. The material in the book is organized and comprehensive. It represents the most up-to-date information on the scientific issues in aging research written by academics who specialize in research and training in the broad field of aging. The structure and organization of the book reflects our course series in the Epidemiology of Aging starting with the broad issues of demography and methodology, and then addressing specific health conditions and geriatric conditions common to older persons.

Epidemiology is often referred to as the science of public health. However, unlike other major sciences, its theoretical foundations are rarely articulated. While the idea of epidemiologic theory may seem dry and arcane, it is at its core about explaining the people's health. It is about life and death. It is about biology and society. It is about ecology and the economy. It is about how myriad aspects of people's lives - involving work, dignity, desire, love, play, conflict, discrimination, and injustice - become literally incorporated into our bodies and manifest in our health status, individually and collectively. And it is about essential knowledge critical for improving the people's health and minimizing inequitable burdens of disease, disability, and death. Woven from a vast array of schools of thought, including those in the natural, social, and biomedical sciences, epidemiologic theory is a rich tapestry whose time for analysis is long overdue. By tracing its history and contours from ancient societies on through the development of - and debates within - contemporary epidemiology worldwide, Dr. Krieger shows how epidemiologic theory has long shaped epidemiologic practice, knowledge, and the politics of public health. Outlining an ecosocial theory of disease distribution that situates both population health and epidemiologic theory in societal and ecologic context, she offers a more holistic picture of how we embody the human experience. This concise, conceptually rich, and accessible book is a rallying cry for a return to the study and discussion of epidemiologic theory: what it is, why it matters, how it has changed over time, and its implications for improving population health and promoting health equity. It should be required reading for all epidemiologists, or anyone involved in the study of human health and well-being.

Medical Data Management is a systematic introduction to the basic methodology of professional clinical data management. It emphasizes generic methods of medical documentation applicable to such diverse tasks as the electronic patient record, maintaining a clinical trials database, and building a tumor registry. This book is for all students in medical informatics and health information management, and it is ideal for both the undergraduate and the graduate levels. The book also guides professionals in the design and use of clinical information systems in various health care settings. It is an invaluable resource for all health care professionals involved in designing, assessing, adapting, or using clinical data management systems in hospitals, outpatient clinics, study centers, health plans, etc. The book combines a consistent theoretical foundation of medical documentation methods outlining their practical applicability in real clinical data management systems. Two new chapters detail hospital information systems and clinical trials. There is a focus on the international classification of diseases (ICD-9 and -10) systems, as well as a discussion on the difference between the two codes. All chapters feature exercises, bullet points, and a summary to provide the reader with essential points to remember. New to the Third Edition is a comprehensive section comprised of a combined Thesaurus and Glossary which aims to clarify the unclear and sometimes inconsistent terminology surrounding the topic.