How do we identify and measure human disease in the past? In the absence of soft tissue, paleoepidemiologists have developed ingenious ways of assessing illness and mortality in archaeological populations. In this volume, the key methods of epidemiology are outlined for non-specialists, showing the importance of studying prevalence over incidence, adjustments needed in studying past groups, how to compare studies, and the dangers of assessing occupation based upon bone evidence. A model for planning a proper paleoepidemiological study concludes the volume. Both as an introduction to epidemiology for archaeologists, and as a primer on archaeological analysis for epidemiologists, this book should serve the needs of both populations.

As rapid technological developments occur in electronics, photonics, mechanics, chemistry, and biology, the demand for portable, lightweight integrated microsystems is relentless. These devices are getting exponentially smaller, increasingly used in everything from video games, hearing aids, and pacemakers to more intricate biomedical engineering and military applications. Edited by Kris Iniewski, a revolutionary in the field of advanced semiconductor materials, Integrated Microsystems: Electronics, Photonics, and Biotechnology focuses on techniques for optimized design and fabrication of these intelligent miniaturized devices and systems. Composed of contributions from experts in academia and industry around the world, this reference covers processes compatible with CMOS integrated circuits, which combine computation, communications, sensing, and actuation capabilities. Light on math and physics, with a greater emphasis on microsystem design and configuration and electrical engineering, this book is organized in three sections-Microelectronics and Biosystems, Photonics and Imaging, and Biotechnology and MEMs. It addresses key topics, including physical and chemical sensing, imaging, smart actuation, and data fusion and management. Using tables, figures, and equations to help illustrate concepts, contributors examine and explain the potential of emerging applications for areas including biology, nanotechnology, micro-electromechanical systems (MEMS), microfluidics, and photonics.

This book, commissioned by the World Health Organization (WHO) and written by international experts, provides consensus views on the most important issues related to allergic hypersensitivities. The text details predictive testing, diagnosis, epidemiological monitoring of intervention measures, sources of sensitizing agents, and mechanisms of action.
Contributors extensively cover allergic hypersensitivity reactions of the skin and the respiratory system. They present the current knowledge on hypersensitivity reactions of the gastrointestinal tract and kidneys. Major gaps in existing information about allergic hypersensitivities are highlighted and recommendations for future research are given. Practical methods are provided for establishing preventive programs.
Allergic Hypersensitivities Induced by Chemicals offers valuable information to both scientists and public health officials. This is a useful reference for health professionals in their work with allergies, allergens, and allergy sufferers.

This book presents the statistical analysis of compositional data using the log-ratio approach. It includes a wide range of classical and robust statistical methods adapted for compositional data analysis, such as supervised and unsupervised methods like PCA, correlation analysis, classification and regression. In addition, it considers special data structures like high-dimensional compositions and compositional tables. The methodology introduced is also frequently compared to methods which ignore the specific nature of compositional data. It focuses on practical aspects of compositional data analysis rather than on detailed theoretical derivations, thus issues like graphical visualization and preprocessing (treatment of missing values, zeros, outliers and similar artifacts) form an important part of the book. Since it is primarily intended for researchers and students from applied fields like geochemistry, chemometrics, biology and natural sciences, economics, and social sciences, all the proposed methods are accompanied by worked-out examples in R using the package robCompositions.

A uniquely accessible overview of statistics for the medical industry

Statistics is a vital discipline with growing applications across many industries, especially the ever-evolving field of health care, where it plays an essential part in the design of new medical devices, the implementation and analysis of clinical trials, and various epidemiological studies. In today’s modern age of computing, both statistical methodology and its applications are expanding as rapidly as the technology will allow, resulting in an upsurge of new developments and more effective methodologies.

Introductory Biostatistics for the Health Sciences: Modern Applications Including Bootstrap addresses the need for a book that presents a basic, accurate, and up-to-date overview of statistical methodology as it applies to today’s health care industry. The authors, both professionals in the areas of medical consulting and epidemiological research, provide balanced coverage of the latest developments in the industry, liberally illustrated with real-world examples. Students and professionals will find this text helpful in several important ways:

• Presents motivating applications in light of honest theory
• Incorporates resampling statistics software throughout
• Discusses Outliers by way of detection and treatment
• Covers such recent statistical advances as bootstrapping
• Includes helpful exercises throughout

A lucid writing style and numerous real-world examples add to the book’s appeal and value, and make a complex subject uniquely accessible to a diverse audience including medical personnel, public health trainees, as well as nursing and medical students.

Produced amidst the still rippling effects of a pandemic and as the world experiences the increasing burden of global warming and a rapidly changing biosphere, the second edition of Parasitology: A Conceptual Approach offers a timely overview of the eukaryotic parasites affecting human health and the health of domestic and wild animals and plants. The book offers a broadly encompassing, integrative view of the phenomenon of parasitism and of the remarkable diversity of the world's parasites. This second edition has been thoroughly updated on all aspects of parasitism, including expanded sections on parasite biodiversity, parasite genomes, the interface between parasitology and disease ecology, and applications of new techniques like CRISPR and gene drives for parasite control. Key selling features: Emphasis on a distinctive integrative and conceptual approach rather than the taxon-by-taxon approach used in most parasitology books A concise, handy Rogues Gallery section that summarizes the basic biology for the most important eukaryotic parasites of humans and domestic animals, one a reader is repeatedly directed to throughout the chapters Outstanding full-color illustrations and photographs to reinforce key points The use of text boxes to set apart important topics or ideas that deserve special emphasis Provision of end-of-chapter summaries, questions to test understanding and key references for those wishing to seek further information Reference to particular URLs to highlight recent developments that often pose new and distinctive problems awaiting solution Parasitology: A Conceptual Approach is designed for an upper-level undergraduate audience, but its readability and careful explanation of underlying scientific concepts and terminology makes it appropriate for anyone seeking a broader understanding of the impact of infectious organisms on our well-being and the changes underway in the modern world.

To advance the epidemiological analysis of social inequalities in health, and of the ways in which population distributions of disease, disability, and death reflect embodied expressions of social inequality, this volume draws on articles published in the "International Journal of Health Services" between 1990 and 2000. Framed by ecosocial theory, it employs ecosocial constructs of "embodiment"; "pathways of embodiment"; "cumulative interplay of exposure, susceptibility, and resistance across the lifecourse"; and "accountability and agency" to address the question; and who and what drives current and changing patterns of social inequalities in health.

Advancing the development, validation, and use of patient-reported outcome (PRO) measures, Patient-Reported Outcomes: Measurement, Implementation and Interpretation helps readers develop and enrich their understanding of PRO methodology, particularly from a quantitative perspective. Designed for biopharmaceutical researchers and others in the health sciences community, it provides an up-to-date volume on conceptual and analytical issues of PRO measures. The book discusses key concepts relating to the measurement, implementation, and interpretation of PRO measures. It covers both introductory and advanced psychometric and biostatistical methods for constructing and analyzing PRO measures. The authors include many relevant real-life applications based on their extensive first-hand experiences in the pharmaceutical industry. They implement a wealth of simulated datasets to illustrate concepts and heighten understanding based on practical scenarios. For readers interested in conducting statistical analyses of PRO measures and delving more deeply into the analytic details, most chapters contain SAS code and output that illustrate the methodology. Along with providing numerous references, the book highlights current regulatory guidelines.

Empirical Likelihood Methods in Biomedicine and Health provides a compendium of nonparametric likelihood statistical techniques in the perspective of health research applications. It includes detailed descriptions of the theoretical underpinnings of recently developed empirical likelihood-based methods. The emphasis throughout is on the application of the methods to the health sciences, with worked examples using real data. Provides a systematic overview of novel empirical likelihood techniques. Presents a good balance of theory, methods, and applications. Features detailed worked examples to illustrate the application of the methods. Includes R code for implementation. The book material is attractive and easily understandable to scientists who are new to the research area and may attract statisticians interested in learning more about advanced nonparametric topics including various modern empirical likelihood methods. The book can be used by graduate students majoring in biostatistics, or in a related field, particularly for those who are interested in nonparametric methods with direct applications in Biomedicine.

Statistical Testing Strategies in the Health Sciences provides a compendium of statistical approaches for decision making, ranging from graphical methods and classical procedures through computationally intensive bootstrap strategies to advanced empirical likelihood techniques. It bridges the gap between theoretical statistical methods and practical procedures applied to the planning and analysis of health-related experiments. The book is organized primarily based on the type of questions to be answered by inference procedures or according to the general type of mathematical derivation. It establishes the theoretical framework for each method, with a substantial amount of chapter notes included for additional reference. It then focuses on the practical application for each concept, providing real-world examples that can be easily implemented using corresponding statistical software code in R and SAS. The book also explains the basic elements and methods for constructing correct and powerful statistical decision-making processes to be adapted for complex statistical applications. With techniques spanning robust statistical methods to more computationally intensive approaches, this book shows how to apply correct and efficient testing mechanisms to various problems encountered in medical and epidemiological studies, including clinical trials. Theoretical statisticians, medical researchers, and other practitioners in epidemiology and clinical research will appreciate the book's novel theoretical and applied results. The book is also suitable for graduate students in biostatistics, epidemiology, health-related sciences, and areas pertaining to formal decision-making mechanisms.

The third edition of the bestselling Clinical Trials in Oncology provides a concise, nontechnical, and thoroughly up-to-date review of methods and issues related to cancer clinical trials. The authors emphasize the importance of proper study design, analysis, and data management and identify the pitfalls inherent in these processes. In addition, the book has been restructured to have separate chapters and expanded discussions on general clinical trials issues, and issues specific to Phases I, II, and III. New sections cover innovations in Phase I designs, randomized Phase II designs, and overcoming the challenges of array data. Although this book focuses on cancer trials, the same issues and concepts are important in any clinical setting. As always, the authors use clear, lucid prose and a multitude of real-world examples to convey the principles of successful trials without the need for a strong statistics or mathematics background. Armed with Clinical Trials in Oncology, Third Edition, clinicians and statisticians can avoid the many hazards that can jeopardize the success of a trial.

As a maritime trading nation, the issue of quarantine was one of constant concern to Britain. Whilst naturally keen to promote international trade, there was a constant fear of importing potentially devastating diseases into British territories. In this groundbreaking study, John Booker examines the methods by which British authorities sought to keep their territories free from contagious diseases, and the reactions to, and practical consequences of, these policies. Drawing upon a wealth of documentary sources, Dr Booker paints a vivid picture of this controversial episode of British political and mercantile history, concluding that quarantine was a peculiarly British disaster, doomed to inefficiency by the royal prerogative and concerns for trade and individual liberty. Whilst it may not have fatally hindered the economic development of Britain, it certainly irritated the City and the mercantile elites and remained a source of constant political friction for many years. As such, an understanding of British maritime quarantine provides a fuller picture of attitudes to trade, culture, politics and medicine in the eighteenth and nineteenth centuries.

Genetic Association Studies is designed for students of public health, epidemiology, and the health sciences, covering the main principles of molecular genetics, population genetics, medical genetics, epidemiology and statistics. It presents a balanced view of genetic associations with coverage of candidate gene studies as well as genome-wide association studies. All aspects of a genetic association study are included, from the lab to analysis and interpretation of results, but also bioinformatics approaches to causality assessment. The role of the environment in genetic disease is also highlighted. Genetic Association Studies will enable readers to understand and critique genetic association studies and set them on the way to designing, executing, analyzing, interpreting, and reporting their own.

Applied statistics is more than data analysis, but it is easy to lose sight of the big picture. David Cox and Christl Donnelly distil decades of scientific experience into usable principles for the successful application of statistics, showing how good statistical strategy shapes every stage of an investigation. As you advance from research or policy question, to study design, through modelling and interpretation, and finally to meaningful conclusions, this book will be a valuable guide. Over a hundred illustrations from a wide variety of real applications make the conceptual points concrete, illuminating your path and deepening your understanding. This book is essential reading for anyone who makes extensive use of statistical methods in their work.

Healthcare is important to everyone, yet large variations in its quality have been well documented both between and within many countries. With demand and expenditure rising, it's more crucial than ever to know how well the healthcare system and all its components - from staff member to regional network - are performing. This requires data, which inevitably differ in form and quality. It also requires statistical methods, the output of which needs to be presented so that it can be understood by whoever needs it to make decisions. Statistical Methods for Healthcare Performance Monitoring covers measuring quality, types of data, risk adjustment, defining good and bad performance, statistical monitoring, presenting the results to different audiences and evaluating the monitoring system itself. Using examples from around the world, it brings all the issues and perspectives together in a largely non-technical way for clinicians, managers and methodologists. Statistical Methods for Healthcare Performance Monitoring is aimed at statisticians and researchers who need to know how to measure and compare performance, health service regulators, health service managers with responsibilities for monitoring performance, and quality improvement scientists, including those involved in clinical audits.

Identity theft, criminal investigations of the dead or missing, mass disasters both by natural causes and by criminal intent - with this as our day to day reality, the establishment and verification of human identity has never been more important or more prominent in our society. Maintaining and protecting the integrity of out identity has reached levels of unprecedented importance and has led to international legislation to protect our human rights.
Forensic Human Identification: An Introduction examines the variety of biological indicators that are available to investigators and illustrates the basic principles of each discipline. While DNA and fingerprints are clearly the favored methods of identification, they require a prior record and verifiable baseline for comparison. When these tools cannot be used it is necessary to employ those biological factors with higher variation and lower diagnostic probability. This reference introduces a number of different specialties such as, foot- and earprinting, dental interventions, skeletal anomalies, tattoos, facial reconstruction, personal effects, and handwriting.
While recognizing that no single factor is an absolute indicator of identity, the contributors explain how a multitude of factors taken into summative consideration can establish a probability for confirmation. They discuss the difference between positive and probable identification and the use of exclusion to confirm identity. Using three high profile case studies, the book addresses the context of human identification in today's society and illustrates the use of techniques described in the text.
Heavily referenced and using more than 120 charts, figures, photographs, and tables, Forensic Human Identification: An Introduction provides detailed introductory and extended information to newcomers and experts alike on the wide range of identification techniques in international practice.

Health geographers are well situated for undertaking population health intervention research (PHIR), and have an opportunity to be at the forefront of this emerging area of inquiry. However, in order to advance PHIR, the scientific community needs to be innovative with its methodologies, theories, and ability to think critically about population health issues. For example, using alternatives (e.g. community-based participatory research) to traditional study designs such as the randomised control trial, health geographers can contribute in important ways to understanding the complex relationships between population health (both intended and unintended consequences), interventions and place. Representing a diverse array of health concerns ranging across chronic and infectious diseases, and research employing varied qualitative and quantitative methodologies, the contributions to this book illustrate how geographic concepts and approaches have informed the design and planning of intervention(s) and/or the evaluation of health impacts. For example, the authors argue that geographically targeting interventions to places of high-need and tailoring interventions to local place contexts are critically important for intervention success. Including an afterword by Professor Louise Potvin, this book will appeal to researchers interested in population and public/community health and epidemiology as well as health geography.

Reliably optimizing a new treatment in humans is a critical first step in clinical evaluation since choosing a suboptimal dose or schedule may lead to failure in later trials. At the same time, if promising preclinical results do not translate into a real treatment advance, it is important to determine this quickly and terminate the clinical evaluation process to avoid wasting resources. Bayesian Designs for Phase I-II Clinical Trials describes how phase I-II designs can serve as a bridge or protective barrier between preclinical studies and large confirmatory clinical trials. It illustrates many of the severe drawbacks with conventional methods used for early-phase clinical trials and presents numerous Bayesian designs for human clinical trials of new experimental treatment regimes. Written by research leaders from the University of Texas MD Anderson Cancer Center, this book shows how Bayesian designs for early-phase clinical trials can explore, refine, and optimize new experimental treatments. It emphasizes the importance of basing decisions on both efficacy and toxicity.

* The first book to explore the complex challenges of the Covid19 pandemic from an inter-disciplinary perspective. * Written by leaders across a range of different sectors that are impacted by the pandemic - medicine, business, law, higher education, government. * The book provides an accessible overview of some of the key tensions presented by the Covid19 pandemic to enable policymakers and researchers to gain insight quickly.

The aim of this book is an applied and unified introduction into parametric, non- and semiparametric regression that closes the gap between theory and application. The most important models and methods in regression are presented on a solid formal basis, and their appropriate application is shown through many real data examples and case studies. Availability of (user-friendly) software has been a major criterion for the methods selected and presented. Thus, the book primarily targets an audience that includes students, teachers and practitioners in social, economic, and life sciences, as well as students and teachers in statistics programs, and mathematicians and computer scientists with interests in statistical modeling and data analysis. It is written on an intermediate mathematical level and assumes only knowledge of basic probability, calculus, and statistics. The most important definitions and statements are concisely summarized in boxes. Two appendices describe required matrix algebra, as well as elements of probability calculus and statistical inference.

Now in its second edition, this book brings multivariate statistics to graduate-level practitioners, making these analytical methods accessible without lengthy mathematical derivations. Using the open source shareware program R, Dr. Zelterman demonstrates the process and outcomes for a wide array of multivariate statistical applications. Chapters cover graphical displays; linear algebra; univariate, bivariate and multivariate normal distributions; factor methods; linear regression; discrimination and classification; clustering; time series models; and additional methods. He uses practical examples from diverse disciplines, to welcome readers from a variety of academic specialties. Each chapter includes exercises, real data sets, and R implementations. The book avoids theoretical derivations beyond those needed to fully appreciate the methods. Prior experience with R is not necessary. New to this edition are chapters devoted to longitudinal studies and the clustering of large data. It is an excellent resource for students of multivariate statistics, as well as practitioners in the health and life sciences who are looking to integrate statistics into their work.

Foodborne Diseases: Case Studies of Outbreaks in the Agri-Food Industries defines the context of foodborne disease across a range of food sectors. It provides insight into the causes and management of outbreaks along with practical lessons about foodborne disease prevention strategies relevant to stakeholders throughout the food supply chain. Individual chapters capture the epidemiological and traceback investigations of foodborne disease outbreaks in a wide range of food sectors that include fresh produce, dairy and eggs, and meat products, to complex food ingredients and products within the food manufacturing and food service sectors. Under each food category, case studies of real outbreaks are presented, along with lessons learned in the way they were managed for future control of foodborne disease outbreaks. The authors look at management of outbreaks across borders and consider how both local and international authorities dealt with the issues in each case. They focus on real-life microbiological/chemical-associated outbreaks and provide insights on how the outbreaks occurred and, if possible, how they were traced to the source of contamination. Each outbreak is unique, and readers are given the distinctive circumstances associated with different hazards, challenges faced during epidemiological and environmental investigations, risk communication to the general public, and insights into outbreak management. The authors cover the entire food supply chain, including a chapter on animal feed safety. A chapter on fraud and foodborne outbreaks considers scenarios where food industries, food services, and other stakeholders commit food adulteration, which ultimately leads to foodborne illnesses. Outbreak management and prevention strategies are key parts of each case study.

This volume of the Biostatistics and Health Sciences Set focuses on statistics applied to clinical research. The use of Stata for data management and statistical modeling is illustrated using various examples. Many aspects of data processing and statistical analysis of cross-sectional and experimental medical data are covered, including regression models commonly found in medical statistics. This practical book is primarily intended for health researchers with basic knowledge of statistical methodology. Assuming basic concepts, the authors focus on the practice of biostatistical methods essential to clinical research, epidemiology and analysis of biomedical data (including comparison of two groups, analysis of categorical data, ANOVA, linear and logistic regression, and survival analysis). The use of examples from clinical trials and epideomological studies provide the basis for a series of practical exercises, which provide instruction and familiarize the reader with essential Stata packages and commands.

This study examines the pre-history of statistics in eighteenth-century England and France, before state governments and other institutions began to collect statistical data on a regular basis. Eighteenth-century political and medical arithmeticians developed a variety of useful techniques to measure health and population. This book highlights the history of numerical tables, as new scientific instruments, and explains how they were used to evaluate smallpox inoculations, and the health and size of populations.

SARS from East to West is the production of international collaboration investigating the first major pandemic in the new millennium, SARS. As the only major outbreak of a deadly infectious disease in modern times, the SARS case is an excellent example of an emerging contagious disease in an interdependent and interconnected world and provided the bases for how subsequent pandemics, like the bird flu and swine flu, are viewed and managed. Eva-Karin Olsson and Lan Xue bring together crisis management scholars with genuine knowledge of the geographic area covered in each of the chapters to examine the response to the SARS crisis at national and international levels, as well as media analysis.