Medical Product Safety Evaluation: Biological Models and Statistical Methods presents cutting-edge biological models and statistical methods that are tailored to specific objectives and data types for safety analysis and benefit-risk assessment. Some frequently encountered issues and challenges in the design and analysis of safety studies are discussed with illustrative applications and examples. Medical Product Safety Evaluation: Biological Models and Statistical Methods presents cutting-edge biological models and statistical methods that are tailored to specific objectives and data types for safety analysis and benefit-risk assessment. Some frequently encountered issues and challenges in the design and analysis of safety studies are discussed with illustrative applications and examples. The book is designed not only for biopharmaceutical professionals, such as statisticians, safety specialists, pharmacovigilance experts, and pharmacoepidemiologists, who can use the book as self-learning materials or in short courses or training programs, but also for graduate students in statistics and biomedical data science for a one-semester course. Each chapter provides supplements and problems as more readings and exercises.

This volume focuses on the contributions that social scientists can make to understanding emerging epidemics, their impact, the threats they pose, and their social and political contexts. While many of the international articles focus on infectious disease, some discussion is given to treating psychiatric epidemics and the analysis of the political and cultural meanings that epidemics have. A sociological volume on emerging epidemics, covering psychiatric or psychological diseases as well as infectious disease is long overdue and topics included here are as wide ranging as: bipolar disorder; obesity; malaria; HIV/AIDS; SARS; West Nile Virus; pandemic influenzas; deviance; depression; ADHD; Alzheimer's; and autism. This valuable reference tool empirically examines emerging epidemics themselves and offers a theoretical analysis of the use of epidemics and epidemiology as frameworks for understanding these phenomena. It will appeal to a broad audience of readers of researchers and practitioners in this field, ranging from those involved in public health policy, human security and community health to medical sociologists and other scientists working in health and medicine.

This invaluable, jargon-free guide to essential medical terminology in an accessible A-Z format is ideal for medical, allied health and biomedical science students and researchers, clinicians and health care practitioners. Avoiding the complex language that is so often a feature of statistics and research methodology, this text provides clear and succinct explanations, clarifying meaning and showing the interdependencies between important concepts. This edition includes enhanced explanations of statistical concepts and methods-including more illustrative content-for greater accessibility. The book makes frequent use of examples from the medical literature, with reference to landmark studies, ensuring clinical relevance. It remains an ideal aid to accompany the reading and critical appraisal of medical and health care literature, now widely recognized to be a practical lifelong skill required by all health professionals throughout undergraduate and postgraduate studies and during clinical practice.

An updated treatment of categorical data analysis in the biomedical sciences that now explores applications to translational research

Thoroughly updated with the latest advances in the field, "Applied Categorical Data Analysis and Translational Research, Second Edition" maintains the accessible style of its predecessor while also exploring the importance of translational research as it relates to basic scientific findings within clinical practice. With its easy-to-follow style, updated coverage of major methodologies, and broadened scope of coverage, this new edition provides an accessible guide to statistical methods involving categorical data and the steps to their application in problem solving in the biomedical sciences.

Delving even further into the applied direction, this update offers many real-world examples from biomedicine, epidemiology, and public health along with detailed case studies taken straight from modern research in these fields. Additional features of the Second Edition include:

A new chapter on the relationship between translational research and categorical data, focusing on design study, bioassay, and Phase I and Phase II clinical trials

A new chapter on categorical data and diagnostic medicine, with coverage of the diagnostic process, prevalence surveys, the ROC function and ROC curve, and important statistical considerations

A revised chapter on logistic regression models featuring an updated treatment of simple and multiple regression analysis

An added section on quantal bioassays

Each chapter features updated and new exercise sets along with numerous graphs that demonstrate the highly visual nature of the topic. A related Web site features the book's examples as well as additional data sets that can be worked with using SAS(R) software.

The only book of its kind to provide balanced coverage of methods for both categorical data and translational research, "Applied Categorical Data Analysis and Translational Research, Second Edition" is an excellent book for courses on applied statistics and biostatistics at the upper-undergraduate and graduate levels. It is also a valuable reference for researchers and practitioners in the biomedical and public health fields.

In the year 2000 the World Health Organization estimated that 85 percent of fifteen-year-olds in Botswana would eventually die of AIDS. In Saturday Is for Funerals we learn why that won't happen.

Unity Dow and Max Essex tell the true story of lives ravaged by AIDS of orphans, bereaved parents, and widows; of families who devote most Saturdays to the burial of relatives and friends. We witness the actions of community leaders, medical professionals, research scientists, and educators of all types to see how an unprecedented epidemic of death and destruction is being stopped in its tracks.

This book describes how a country responded in a time of crisis. In the true-life stories of loss and quiet heroism, activism and scientific initiatives, we learn of new techniques that dramatically reduce rates of transmission from mother to child, new therapies that can save lives of many infected with AIDS, and intricate knowledge about the spread of HIV, as well as issues of confidentiality, distributive justice, and human rights. The experiences of Botswana offer practical lessons along with the critical element of hope.

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.

The association of a suspect with the victim or crime scene through DNA evidence is one of the most powerful statements of complicity in a crime imaginable. No category of evidence has ever had the complete capacity to convict or exonerate an accused so absolutely in the eyes of the public. With the discriminatory powers of DNA and the variety of DNA markers now in regular use, the one thing keeping a third of all cases unsolved is the lack of human DNA evidence. However, the identification of polymorphic genetic loci in cats, dogs, plants, insects, bacteria, and viruses can provide the critical link between suspect and scene in the absence of human DNA. Non-Human DNA Typing: Theory and Casework Applications provides an introduction to the basic science underlying the emerging field of non-human DNA typing. It examines the use of non-human DNA evidence not just in homicide cases, but also in drug trafficking, poaching of endangered species, livestock fraud, and missing persons, as well as the identification of primary and secondary crime scenes. The book demonstrates the recognition, collection, and preservation of biological evidence at a crime scene, techniques of DNA fingerprinting, and DNA profiling. Using a wide variety of examples, applications, and case studies, the author describes the STR analysis of canine and feline samples, insects, and fungi, and their role as evidence in forensic science. Chapters consider the development of testing methods for animal evidence, soil DNA typing, and the use of DNA typing in wildlife investigations. A useful appendix includes an overview of the history of forensic serology and DNA. Combining science, case examples, legal decisions, andreferences, Non-Human DNA Typing: Theory and Casework Applications presents the forensic and legal applications of non-human DNA evidence for scientists, law enforcement, and attorneys.

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.

Epidemiological criminology is an emerging paradigm which explores the public health outcomes associated with engagement in crime and criminal justice. This book engages with this new theory and practice-based discipline drawing on knowledge from criminology, criminal justice, public health, epidemiology, public policy, and law to illustrate how the merging of epidemiology into the field of criminology allows for the work of both disciplines to be more interdisciplinary, evidence-based, enriched and expansive. This book brings together an innovative group of exemplary researchers and practitioners to discuss applications and provide examples of epidemiological criminology. It is divided into three sections; the first explores the integration of epidemiology and criminology through theory and methods, the second section focuses on special populations in epidemiological criminology research and the role of race, ethnicity, age, gender and space as it plays out in health outcomes among offenders and victims of crime, and the final section explores the role policy and practice plays in worsening and improving the health outcomes among those engaged in the criminal justice system. Epidemiological Criminology is the first text to bring together, in one source, the existing interdisciplinary work of academics and professionals that merge the fields of criminology and criminal justice to public health and epidemiology. It will be of interest to academics and students in the fields of criminology, epidemiology, and public health, as well as clinical psychologists, law and government policy analysts and those working within the criminal justice system.

The explanation and implementation of statistical methods for the medical researcher or statistician remains an integral part of modern medical research. This book explains the use of experimental and analytical biostatistics systems. Its accessible style allows it to be used by the non-mathematician as a fundamental component of successful research.

Since the third edition, there have been many developments in statistical techniques. The fourth edition provides the medical statistician with an accessible guide to these techniques and to reflect the extent of their usage in medical research.

The new edition takes a much more comprehensive approach to its subject. There has been a radical reorganization of the text to improve the continuity and cohesion of the presentation and to extend the scope by covering many new ideas now being introduced into the analysis of medical research data. The authors have tried to maintain the modest level of mathematical exposition that characterized the earlier editions, essentially confining the mathematics to the statement of algebraic formulae rather than pursuing mathematical proofs.

Received the Highly Commended Certificate in the Public Health Category of the 2002 BMA Books Competition.

Neurologic and neuropsychiatric disorders are of great importance to societies and they also raise special considerations in epidemiological research methodology. Not only do neurologic and neuropsychiatric disorders form a major group of disorders associated with ageing populations, but those disorders that occur in earlier life can be associated with severe individual, family, and societal distress and burden. The inter-relationship of syndromes and disorders is a topic of major interest and growing biological insights across psychiatry and neurology. This includes not only overlaps in neurodegenerative syndromes but also those related to other systems such as metabolic, inflammatory, immune and vascular disorders. Part of the Oxford Textbooks in Clinical Neurology series, the Oxford Textbook of Neurologic and Neuropsychiatric Epidemiology is designed to focus on the overlaps and inter-relationships between neuro-epidemiological disorders, as well as on ways to harmonise large cohort studies to maximise opportunities for determining causes related to rarer disorders. Divided into three main parts, the book covers 1) the principles of neurologic and neuropsychiatric epidemiology; 2) specific neuropsychiatric disorders and their inter-relationships and 3) the implications of neuro-epidemiologic research for patient populations and current medical practice. This comprehensive work serves as an invaluable reference to current neuro-epidemiological methods for neurologists, psychiatrists, and senior trainees in those disciplines, as well as public health practitioners and students with an interest in neurology and neuropsychiatry.

Cities and countries around the world, from New Zealand to Singapore to Iceland, are starting to take a well-being approach by reorienting policies, budgets and other actions to advance human and planetary well-being. Well-being metrics-holistic measurements of an individual's or population's capacity to thrive, including the condition of their community, society, and environment-provide a nuanced and predictive view that transcends purely economic measures; they illuminate conditions of inequity and despair that other tools ignore, and expand the notion of health beyond simply the absence of disease. Well-Being: Expanding the Definition of Progress summarizes the experiences and insights of practitioners, researchers and innovators from around the world, gathered together by the Robert Wood Johnson Foundation to explore how a well-being approach might further spread in the United States. Centered in the commitment to balance economic growth-the traditional dashboard of progress-with well-being, this book is a combination of scientific papers, case studies from the field, and excerpts from a lively, multidisciplinary discussion which intentionally connects issues of measurement to the imperative for action. Rich with insights on policy and practice, narratives and culture, equity and shifts in power, alignment with other movements, and cross-sector collaboration, it is intended to inspire governmental leaders, policymakers, economists, measurement scientists, reporters, and others who crave a more integrated and balanced pursuit of progress.

Textbook of Zoonoses Comprehensive resource covering the aetiology, epidemiology and transmission cycle, clinical symptoms, diagnosis, and prevention and control strategies of the important zoonoses. Zoonoses are the diseases which can spread from animals to humans. This book covers all important zoonoses that are prevalent in today's world. As a modern learning resource, it incorporates recent scientific developments and concepts to give readers a complete overview of each zoonoses. Written by three well-qualified authors in academia, sample topics covered within the book include: Bacterial, viral, parasitic, rickettsial, fungal, prion, and foodborne zoonoses Aetiology and epidemiology of each zoonotic disease Clinical symptoms and diagnosis in animals and humans Treatment options, plus prevention and control strategies CDC classification of zoonotic agents and the WHO's list of 'neglected zoonoses' Written for undergraduate and postgraduate students studying veterinary public health and epidemiology, Textbook of Zoonoses is also a helpful resource for other veterinary and medical professionals interested in public health and epidemiology.

Cluster randomised trials are trials in which groups (or clusters) of individuals are randomly allocated to different forms of treatment. In health care, these trials often compare different ways of managing a disease or promoting healthy living, in contrast to conventional randomised trials which randomise individuals to different treatments, classically comparing new drugs with a placebo. They are increasingly common in health services research. This book addresses the statistical, practical, and ethical issues arising from allocating groups of individuals, or clusters, to different interventions. Key features: * Guides readers through the stages of conducting a trial, from recruitment to reporting. * Presents a wide range of examples with particular emphasis on trials in health services research and primary care, with both principles and techniques explained. * Topics are specifically presented in the order in which investigators think about issues when they are designing a trial. * Combines information on the latest developments in the field together with a practical guide to the design and implementation of cluster randomised trials. * Explains principles and techniques through numerous examples including many from the authors own experience. * Includes a wide range of references for those who wish to read further. This book is intended as a practical guide, written for researchers from the health professions including doctors, psychologists, and allied health professionals, as well as statisticians involved in the design, execution, analysis and reporting of cluster randomised trials. Those with a more general interest will find the plentiful examples illuminating.

This is a unique, in-depth discussion of the uses and conduct of cost-effectiveness analyses (CEA) as decision-making aids in the health and medical fields. The product of over two years of deiberation by a multi-disciplinary Public Health Service appointed panel that included economists, ethicists, psychometricians, and clinicians, it explores cost-effectiveness in the context of societal decision-making for resource allocation purposes. It proposes that analysts include a "reference-case" analysis in all CEA's designed to inform resource allocation and puts forth the most expicit set of guidelines (together with their rationale) ever outlined of the conduct of CEAs. Important theoretical and practical issues encountered in measuring costs and effectiveness, valuing outcomes, discounting, and dealing with uncertainty are examined in separate chapters. These discussions are complemented by additional chapters on framing and reporting of CEAs that aim to clarify the purpose of the analysis and the effective communication of its findings. Primarily intended for analysts in medicine and public health who wish to improve practice and comparability of CEAs, this book will also be of interest to decision-makers in government, managed care, and industry who wish to consider the roles and limitations of CEA and become familiar with criteria for evaluating these studies.

A fundamental and straightforward guide to using and understanding statistical concepts in medical research Designed specifically for healthcare practitioners who need to understand basic biostatistics but do not have much time to spare, The Essentials of Biostatistics for Physicians, Nurses and Clinicians presents important statistical methods used in today's biomedical research and provides insight on their appropriate application. Rather than provide detailed mathematics for each of these methods, the book emphasizes what healthcare practitioners need to know to interpret and incorporate the latest biomedical research into their practices. The author draws from his own experience developing and teaching biostatistics courses for physicians and nurses, offering a presentation that is non-technical and accessible. The book begins with a basic introduction to the relationship between biostatistics and medical research, asking the question "why study statistics?," while also exploring the significance of statisitcal methods in medical literature and clinical trials research. Subsequent chapters explore key topics, including: * Correlation, regression, and logistic regression * Diagnostics * Estimating means and proportions * Normal distribution and the central limit theorem * Sampling from populations * Contingency tables * Meta-analysis * Nonparametric methods * Survival analysis Throughout the book, statistical methods that are often utilized in biomedical research are outlined, including repeated measures analysis of variance, hazard ratios, contingency tables, log rank tests, bioequivalence, cross-over designs, selection bias, and group sequential methods. Exercise sets at the end of each chapter allow readers to test their comprehension of the presented concepts and techniques. The Essentials of Biostatistics for Physicians, Nurses, and Clinicians is an excellent reference for doctors, nurses, and other practicing clinicians in the fields of medicine, public health, pharmacy, and the life sciences who need to understand and apply statistical methods in their everyday work. It also serves as a suitable supplement for courses on biostatistics at the upper-undergraduate and graduate levels.

This book presents strategies for analyzing qualitative and mixed methods data with MAXQDA software, and provides guidance on implementing a variety of research methods and approaches, e.g. grounded theory, discourse analysis and qualitative content analysis, using the software. In addition, it explains specific topics, such as transcription, building a coding frame, visualization, analysis of videos, concept maps, group comparisons and the creation of literature reviews. The book is intended for masters and PhD students as well as researchers and practitioners dealing with qualitative data in various disciplines, including the educational and social sciences, psychology, public health, business or economics.

Compiles the most current information on the Zika virus and its associated diseases This comprehensive book provides the most up-to-date information for students, medical students, and scientists on Zika virus and its associated diseases. It includes all the information related to the Zika virus since its discovery in 1947; its epidemic outbreak in 2007-2014; how the epidemiology changed in America in 2015-2016; its mode of transmission; how to prevent and treat it; and associated diseases. Zika Virus and Diseases: From Molecular Biology to Epidemiology offers complete and up-to-date coverage in 10 chapters. It presents information from papers that attempted to associate the virus with diseases in Africa until the first animal experiment; discusses its association with Guillain-Barre syndrome and microcephaly; describes the basic mechanisms for Zika (ZIKV) replication, including important differences between Dengue (DENV), West-Nile virus (WNV), and ZIKV; explains the difference between the strains and discusses the pathogenesis of them; covers the papers that showed all the interferences that Zika can cause, and the pathways which can be modified; and more. The first book since 1947 to put together all the scientific information Compiles all the information received in the last year about Zika virus Clearly demonstrates the origin and discovery of the virus Zika Virus and Diseases: From Molecular Biology to Epidemiology will appeal to graduate students, medical students, basic researchers, clinicians in infectious disease, microbiology, and virology, as well as people in related disciplines interested in learning more about this topic.

This highly popular introduction to confidence intervals has been thoroughly updated and expanded. It includes methods for using confidence intervals, with illustrative worked examples and extensive guidelines and checklists to help the novice.

In biological research, the amount of data available to researchers has increased so much over recent years, it is becoming increasingly difficult to understand the current state of the art without some experience and understanding of data analytics and bioinformatics. An Introduction to Bioinformatics with R: A Practical Guide for Biologists leads the reader through the basics of computational analysis of data encountered in modern biological research. With no previous experience with statistics or programming required, readers will develop the ability to plan suitable analyses of biological datasets, and to use the R programming environment to perform these analyses. This is achieved through a series of case studies using R to answer research questions using molecular biology datasets. Broadly applicable statistical methods are explained, including linear and rank-based correlation, distance metrics and hierarchical clustering, hypothesis testing using linear regression, proportional hazards regression for survival data, and principal component analysis. These methods are then applied as appropriate throughout the case studies, illustrating how they can be used to answer research questions. Key Features: * Provides a practical course in computational data analysis suitable for students or researchers with no previous exposure to computer programming. * Describes in detail the theoretical basis for statistical analysis techniques used throughout the textbook, from basic principles * Presents walk-throughs of data analysis tasks using R and example datasets. All R commands are presented and explained in order to enable the reader to carry out these tasks themselves. * Uses outputs from a large range of molecular biology platforms including DNA methylation and genotyping microarrays; RNA-seq, genome sequencing, ChIP-seq and bisulphite sequencing; and high-throughput phenotypic screens. * Gives worked-out examples geared towards problems encountered in cancer research, which can also be applied across many areas of molecular biology and medical research. This book has been developed over years of training biological scientists and clinicians to analyse the large datasets available in their cancer research projects. It is appropriate for use as a textbook or as a practical book for biological scientists looking to gain bioinformatics skills.

Data in the genomics field is booming. In just a few years, organizations such as the National Institutes of Health (NIH) will host 50+ petabytes-or over 50 million gigabytes-of genomic data, and they're turning to cloud infrastructure to make that data available to the research community. How do you adapt analysis tools and protocols to access and analyze that volume of data in the cloud? With this practical book, researchers will learn how to work with genomics algorithms using open source tools including the Genome Analysis Toolkit (GATK), Docker, WDL, and Terra. With this practical book, researchers will learn how to work with genomics algorithms using open source tools including the Genome Analysis Toolkit (GATK), Docker, WDL, and Terra. Geraldine Van der Auwera, longtime custodian of the GATK user community, and Brian O'Connor of the UC Santa Cruz Genomics Institute, guide you through the process. You'll learn by working with real data and genomics algorithms from the field. This book covers: Essential genomics and computing technology background Basic cloud computing operations Getting started with GATK, plus three major GATK Best Practices pipelines Automating analysis with scripted workflows using WDL and Cromwell Scaling up workflow execution in the cloud, including parallelization and cost optimization Interactive analysis in the cloud using Jupyter notebooks Secure collaboration and computational reproducibility using Terra

The growth of biostatistics has been phenomenal in recent years and has been marked by considerable technical innovation in both methodology and computational practicality. One area that has experienced significant growth is Bayesian methods. The growing use of Bayesian methodology has taken place partly due to an increasing number of practitioners valuing the Bayesian paradigm as matching that of scientific discovery. In addition, computational advances have allowed for more complex models to be fitted routinely to realistic data sets.

Through examples, exercises and a combination of introductory and more advanced chapters, this book provides an invaluable understanding of the complex world of biomedical statistics illustrated via a diverse range of applications taken from epidemiology, exploratory clinical studies, health promotion studies, image analysis and clinical trials.

"Key Features" Provides an authoritative account of Bayesian methodology, from its most basic elements to its practical implementation, with an emphasis on healthcare techniques.Contains introductory explanations of Bayesian principles common to all areas of application.Presents clear and concise examples in biostatistics applications such as clinical trials, longitudinal studies, bioassay, survival, image analysis and bioinformatics.Illustrated throughout with examples using software including WinBUGS, OpenBUGS, SAS and various dedicated R programs.Highlights the differences between the Bayesian and classical approaches.Supported by an accompanying website hosting free software and case study guides.

"Bayesian Biostatistics" introduces the reader smoothly into the Bayesian statistical methods with chapters that gradually increase in level of complexity. Master students in biostatistics, applied statisticians and all researchers with a good background in classical statistics who have interest in Bayesian methods will find this book useful.

In the mid-1950s, with planning and funding from the United States, Mexico embarked on an ambitious campaign to eradicate malaria, which was widespread and persistent. This new history explores the politics of that campaign. Marcos Cueto describes the international basis of the program, its national organization in Mexico, its local implementation by health practitioners and workers, and its reception among the population. Drawing on archives in the United States, Mexico, and Switzerland, he highlights the militant Cold War rhetoric of the founders and analyzes the mixed motives of participants at all levels. Following the story through the dwindling campaign in the late 1960s and early 1970s, Cueto raises questions relevant to today's international health campaigns against malaria, AIDS, and tuberculosis.

During the last twenty years statistical methodology has become of central importance in research studies in medicine and also in day-to-day clinical practice. The medical literature is now liberally punctuated not only with relatively routine statistical terms such as p-value, t-test, confidence interval, and correlation, but also with more esoteric items such as hazard function, multilevel model, generalized estimating equations and crossover design. Consequently researchers in medicine and clinicians who are not primarily statisticians need to have a source that provides readable accounts of these terms so that they can understand at least the essence of the statistical aspects of both the design and analysis of a reported investigation. "The Encyclopedic Companion to Medical Statistics" is that source, containing readable accounts of over 500 statistical topics central to current medical research, with each entry being written by an expert in the field. Examples and graphical material supplement the written material in many entries, and extensive cross-referencing sign posts the reader to other entries that are likely to be relevant.