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.

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.

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.

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

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.

Straightforward Statistics: Understanding the Tools of Research is a clear and direct introduction to statistics for the social, behavioral, and life sciences. Based on the author's extensive experience teaching undergraduate statistics, this book provides a narrative presentation of the core principles that provide the foundation for modern-day statistics. With step-by-step guidance on the nuts and bolts of computing these statistics, the book includes detailed tutorials how to use state-of-the-art software, SPSS, to compute the basic statistics employed in modern academic and applied research. Across 13 succinct chapters, this text presents statistics using a conceptual approach along with information on the relevance of the different tools in different contexts and summaries of current research examples. Students should find this book easy useful and engaging in its presentation while instructors should find it detailed, comprehensive, accessible, and helpful in complementing a basic course in statistics.

Review of the First Edition: The authors strive to reduce theory to a minimum, which makes it a self-learning text that is comprehensible for biologists, physicians, etc. who lack an advanced mathematics background. Unlike in many other textbooks, R is not introduced with meaningless toy examples; instead the reader is taken by the hand and shown around some analyses, graphics, and simulations directly relating to meta-analysis... A useful hands-on guide for practitioners who want to familiarize themselves with the fundamentals of meta-analysis and get started without having to plough through theorems and proofs. -Journal of Applied Statistics Statistical Meta-Analysis with R and Stata, Second Edition provides a thorough presentation of statistical meta-analyses (MA) with step-by-step implementations using R/Stata. The authors develop analysis step by step using appropriate R/Stata functions, which enables readers to gain an understanding of meta-analysis methods and R/Stata implementation so that they can use these two popular software packages to analyze their own meta-data. Each chapter gives examples of real studies compiled from the literature. After presenting the data and necessary background for understanding the applications, various methods for analyzing meta-data are introduced. The authors then develop analysis code using the appropriate R/Stata packages and functions. What's New in the Second Edition: Adds Stata programs along with the R programs for meta-analysis Updates all the statistical meta-analyses with R/Stata programs Covers fixed-effects and random-effects MA, meta-regression, MA with rare-event, and MA-IPD vs MA-SS Adds five new chapters on multivariate MA, publication bias, missing data in MA, MA in evaluating diagnostic accuracy, and network MA Suitable as a graduate-level text for a meta-data analysis course, the book is also a valuable reference for practitioners and biostatisticians (even those with little or no experience in using R or Stata) in public health, medical research, governmental agencies, and the pharmaceutical industry.

The past three decades have witnessed modern advances in statistical modeling and evidence discovery in biomedical, clinical, and population-based research. With these advances come the challenges in accurate model stipulation and application of models in scientific evidence discovery Applied Biostatistical Principles and Concepts provides practical knowledge using biological and biochemical specimen/samples in order to understand health and disease processes at cellular, clinical, and population levels. Concepts and techniques provided will help researchers design and conduct studies, then translate data from bench to clinics in attempt to improve the health of patients and populations. This book is suitable for both clinicians and health or biological sciences students. It presents the reality in statistical modelling of health research data in a concise manner that will address the issue of "big data" type I error tolerance and probability value, effect size and confidence interval for precision, effect measure modification and interaction as well as confounders, thus allowing for more valid inferences and yielding results that are more reliable, valid and accurate.

This book provides practical knowledge to clinicians and biomedical researchers using biological and biochemical specimen/samples in order to understand health and disease processes at cellular, clinical, and population levels. Concepts and techniques provided will help researchers design and conduct studies, then translate data from bench to clinics in attempt to improve the health of patients and populations. This book presents the extreme complexity of epidemiologic research in a concise manner that will address the issue of confounders, thus allowing for more valid inferences and yielding results that are more reliable and accurate.

Mathematical and Statistical Skills in the Biopharmaceutical Industry: A Pragmatic Approach describes a philosophy of efficient problem solving showcased using examples pertinent to the biostatistics function in clinical drug development. It was written to share a quintessence of the authors' experiences acquired during many years of relevant work in the biopharmaceutical industry. The book will be useful will be useful for biopharmaceutical industry statisticians at different seniority levels and for graduate students who consider a biostatistics-related career in this industry. Features: Describes a system of principles for pragmatic problem solving in clinical drug development. Discusses differences in the work of a biostatistician in small pharma and big pharma. Explains the importance/relevance of statistical programming and data management for biostatistics and necessity for integration on various levels. Describes some useful statistical background that can be capitalized upon in the drug development enterprise. Explains some hot topics and current trends in biostatistics in simple, non-technical terms. Discusses incompleteness of any system of standard operating procedures, rules and regulations. Provides a classification of scoring systems and proposes a novel approach for evaluation of the safety outcome for a completed randomized clinical trial. Presents applications of the problem solving philosophy in a highly problematic transfusion field where many investigational compounds have failed. Discusses realistic planning of open-ended projects.

Since the publication of the second edition, many new Bayesian tools and methods have been developed for space-time data analysis, the predictive modeling of health outcomes, and other spatial biostatistical areas. Exploring these new developments, Bayesian Disease Mapping: Hierarchical Modeling in Spatial Epidemiology, Third Edition provides an up-to-date, cohesive account of the full range of Bayesian disease mapping methods and applications. In addition to the new material, the book also covers more conventional areas such as relative risk estimation, clustering, spatial survival analysis, and longitudinal analysis. After an introduction to Bayesian inference, computation, and model assessment, the text focuses on important themes, including disease map reconstruction, cluster detection, regression and ecological analysis, putative hazard modeling, analysis of multiple scales and multiple diseases, spatial survival and longitudinal studies, spatiotemporal methods, and map surveillance. It shows how Bayesian disease mapping can yield significant insights into georeferenced health data. The target audience for this text is public health specialists, epidemiologists, and biostatisticians who need to work with geo-referenced health data.

This book presents a 360-degree picture of the world of insects and explores how their existence affects our lives: the "good, bad, and ugly" aspects of their interactions with humankind. It provides a lucid introductory text for beginning undergraduate students in the life sciences, particularly those pursuing beginner courses in entomology, agriculture, and botany.

This book demonstrates that a pandemic of coronary heart disease occurred in North America, western and northern Europe, and Australia and New Zealand from the 1930s to about 2000. At its peak it caused more deaths than any other disease. The book examines and compares trends in coronary heart disease mortality rates for individual countries. The most detailed analyses are for the United States, where mortality rates are examined for race, sex, and age groups and for geographic regions. Popular explanations for the rise and fall of coronary heart disease mortality rates are examined.