"Blackwell Publishing is delighted to announce that this book has been Highly Commended in the 2004 BMA Medical Book Competition. Here is the judges' summary of this book: "

""This is a technical book on a technical subject but presented in a delightful way. There are many books on statistics for doctors but there are few that are excellent and this is certainly one of them. Statistics is not an easy subject to teach or write about. The authors have succeeded in producing a book that is as good as it can get. For the keen student who does not want a book for mathematicians, this is an excellent first book on medical statistics.""

"Essential Medical Statistics" is a classic amongst medical statisticians. An introductory textbook, it presents statistics with a clarity and logic that demystifies the subject, while providing a comprehensive coverage of advanced as well as basic methods.

The second edition of "Essential Medical Statistics" has been comprehensively revised and updated to include modern statistical methods and modern approaches to statistical analysis, while retaining the approachable and non-mathematical style of the first edition. The book now includes full coverage of the most commonly used regression models, multiple linear regression, logistic regression, Poisson regression and Cox regression, as well as a chapter on general issues in regression modelling. In addition, new chapters introduce more advanced topics such as meta-analysis, likelihood, bootstrapping and robust standard errors, and analysis of clustered data.

Aimed at students of medical statistics, medical researchers, public health practitioners andpractising clinicians using statistics in their daily work, the book is designed as both a teaching and a reference text. The format of the book is clear with highlighted formulae and worked examples, so that all concepts are presented in a simple, practical and easy-to-understand way. The second edition enhances the emphasis on choice of appropriate methods with new chapters on strategies for analysis and measures of association and impact.

"Essential Medical Statistics" is supported by a web site at www.blackwellpublishing.com/essentialmedstats. This useful online resource provides statistical datasets to download, as well as sample chapters and future updates.

Computational Genomics with R provides a starting point for beginners in genomic data analysis and also guides more advanced practitioners to sophisticated data analysis techniques in genomics. The book covers topics from R programming, to machine learning and statistics, to the latest genomic data analysis techniques. The text provides accessible information and explanations, always with the genomics context in the background. This also contains practical and well-documented examples in R so readers can analyze their data by simply reusing the code presented. As the field of computational genomics is interdisciplinary, it requires different starting points for people with different backgrounds. For example, a biologist might skip sections on basic genome biology and start with R programming, whereas a computer scientist might want to start with genome biology. After reading: You will have the basics of R and be able to dive right into specialized uses of R for computational genomics such as using Bioconductor packages. You will be familiar with statistics, supervised and unsupervised learning techniques that are important in data modeling, and exploratory analysis of high-dimensional data. You will understand genomic intervals and operations on them that are used for tasks such as aligned read counting and genomic feature annotation. You will know the basics of processing and quality checking high-throughput sequencing data. You will be able to do sequence analysis, such as calculating GC content for parts of a genome or finding transcription factor binding sites. You will know about visualization techniques used in genomics, such as heatmaps, meta-gene plots, and genomic track visualization. You will be familiar with analysis of different high-throughput sequencing data sets, such as RNA-seq, ChIP-seq, and BS-seq. You will know basic techniques for integrating and interpreting multi-omics datasets. Altuna Akalin is a group leader and head of the Bioinformatics and Omics Data Science Platform at the Berlin Institute of Medical Systems Biology, Max Delbruck Center, Berlin. He has been developing computational methods for analyzing and integrating large-scale genomics data sets since 2002. He has published an extensive body of work in this area. The framework for this book grew out of the yearly computational genomics courses he has been organizing and teaching since 2015.

Contagion - even today the word conjures up fear of disease and plague and has the power to terrify. The nine essays gathered here examine what pre-modern societies thought about the spread of disease and how it could be controlled: to what extent were concepts familiar to modern epidemiology present? What does the pre-modern terminology tell us about the conceptions of those times? How did medical thought relate to religious and social beliefs? The contributors reveal the complexity of ideas on these subjects, from antiquity through to the early modern world, from China to India, the Middle East, and Europe. Particular topics include attitudes to leprosy in the Old Testament and the medieval West, conceptions of smallpox etiology in China, witchcraft and sorcery as disease agents in ancient India, and the influence of classical Greek medical theory. An important conclusion is that non-medical perceptions are as crucial as medical ones in people's beliefs about disease and the ways in which it can be combatted. Today we may not believe in the power of demons, but the idea that illness is retribution for sin retains great power, as was shown by the popular reaction to the spread of AIDS/HIV, and this is a lesson from the past that the medical profession would do well to heed.

Global problems require global information, which satellites can now provide. With ever more sophisticated control methods being developed for infectious diseases, our ability to map spatial and temporal variation in risk is more important than ever. Only then may we plan control campaigns and deliver novel interventions and remedies where the need is greatest, and sustainable success is most likely. This book presents a comprehensive guide to using the very latest methods of surveillance from satellites, including analysing spatial data within geographical information systems, interpreting complex biological patterns, and predicting risk both today and as it may change in the future. Of all infectious disease systems, those that involve free-living invertebrate vectors or intermediate hosts are most susceptible to changing environmental conditions, and have hitherto received most attention from the marriage of analytical biology with this new space technology. Accordingly, this volume presents detailed case studies on malaria, African trypanosomiasis (sleeping sickness), tick-borne infections and helminths (worms). For those who are unfamiliar with this science, and unsure how to start, the book ends with a chapter of practical advice on where to seek hands-on instruction. The lessons to be learned from these studies are applicable to many other epidemiological and ecological problems that face us today, most significantly the preservation of the world's biodiversity.
Key Features
* Only book to provide a synthesis of complex biology, quantitative analysis, space technology and practical applications, focused on solving real epidemiological problems on a global scale
* Broad scope, with methods relevant to subjects ranging from biodiversity to public health
* Practical advice on relevant courses
* 24 pages of colour plates

Cost-effectiveness analysis is becoming an increasingly important tool for decision making in the health systems. Cost-Effectiveness of Medical Treatments formulates the cost-effectiveness analysis as a statistical decision problem, identifies the sources of uncertainty of the problem, and gives an overview of the frequentist and Bayesian statistical approaches for decision making. Basic notions on decision theory such as space of decisions, space of nature, utility function of a decision and optimal decisions, are explained in detail using easy to read mathematics. Features Focuses on cost-effectiveness analysis as a statistical decision problem and applies the well-established optimal statistical decision methodology. Discusses utility functions for cost-effectiveness analysis. Enlarges the class of models typically used in cost-effectiveness analysis with the incorporation of linear models to account for covariates of the patients. This permits the formulation of the group (or subgroup) theory. Provides Bayesian procedures to account for model uncertainty in variable selection for linear models and in clustering for models for heterogeneous data. Model uncertainty in cost-effectiveness analysis has not been considered in the literature. Illustrates examples with real data. In order to facilitate the practical implementation of real datasets, provides the codes in Mathematica for the proposed methodology. The motivation for the book is to make the achievements in cost-effectiveness analysis accessible to health providers, who need to make optimal decisions, to the practitioners and to the students of health sciences. Elias Moreno is Professor of Statistics and Operational Research at the University of Granada, Spain, Corresponding Member of the Royal Academy of Sciences of Spain, and elect member of ISI. Francisco Jose Vazquez-Polo is Professor of Mathematics and Bayesian Methods at the University of Las Palmas de Gran Canaria, and Head of the Department of Quantitative Methods. Miguel Angel Negrin is Senior Lecturer in the Department of Quantitative Methods at the ULPGC. His main research topics are Bayesian methods applied to Health Economics, economic evaluation and cost-effectiveness analysis, meta-analysis and equity in the provision of healthcare services.

The human foetus is separated from the maternal blood by the syncytiotrophoblast induced by endogeneous human retrovirus-encoded proteins. This barrier is a highly developed one, which suppors apical-basolateral transport of maternal idiotype and anti-idiotype IgG, IgG-virus complexes. The selective maternal-fetal transport of epitope- and paratope-bearing entities can influence the developping fetal immune system during pregnancy. The bidirectional maternal-fetal transfer of cells are of even more importance during pregnancy. Maternal cells with latent viruses transport viruses without impairment of fetal development. Cells with premaligant and malignant genetic transformation are also transported to the fetus. Fetal and neonatal tumours are initiated by such cells in spite of the antitumour potential of fetal organism. On the contary, the fetal cells repair maternal tissue injouries and survive in the organisms of the recipients for decades. These possess new consequences for the neonatal immunity and organ transplatation surgery.

Statistical Approaches in Oncology Clinical Development : Current Paradigm and Methodological Advancement presents an overview of statistical considerations in oncology clinical trials, both early and late phase of development. It illustrates how novel statistical methods can enrich the design and analysis of modern oncology trials. The authors include many relevant real life examples from the pharmaceutical industry and academia based on their first-hand experience. Along with relevant references, the book highlights current regulatory views. The book covers all aspects of cancer clinical trial starting from early phase development. The early part of the book covers novel phase I dose escalation design, exposure response analysis, and innovative phase II design. This includes early development strategy for cancer immunotherapy trials. The contributors also emphasized the role of biomarker and modern era of precision medicine. The second part focuses on the late stage development. This includes the application of adaptive design, safety analysis, and quality of life (QoL) data analysis. The final part discusses current regulatory perspective and challenges. Features: Covers a wide spectrum of topics related to real-life statistical challenges in oncology clinical trials. Provides a comprehensive overview of novel statistical methods to improve trial design and statistical analysis. Detailed case studies illustrate the real life applications. Satrajit Roychoudhury is a Senior Director and a member of the Statistical Research and Innovation group in Pfizer Inc. Prior to joining; he was a member of Statistical Methodology and consulting group in Novartis. He has 11 years of extensive experience in working with different phases of clinical trial. His area of research includes early phase oncology trials, survival analysis, model informed drug development, and use of Bayesian methods in clinical trials. He is industry co-chair for the ASA Biopharmaceutical Section Regulatory-Industry Workshop and has provided statistical training in major conferences including the Joint Statistical Meetings, ASA Biopharmaceutical Section Regulatory-Industry Workshop, and ICSA Applied Statistics Symposium. Soumi Lahiri has 12 years of extensive experience in working different therapeutic areas. She is the former Director of Biostatistics in Clinical Oncology, GlaxoSmithKline. She has also worked in the oncology division of Novartis Pharmaceutical Company for two years. She is an active member of the ASA Biopharmaceutical section and former chair of the membership committee.

Concern about the impact of air pollution has led governments and local authorities across the world to regulate, among other things, the burning of fossil fuels, industrial effluence, cigarette smoke, and aerosols. This legislation has often followed dramatic findings about the impact of pollution on human health. At the same time there have been significant developments in our ability to detect and quantify pollutants and a proliferation of urban and rural air pollution networks to monitor levels of atmospheric contamination.
Air Pollution and Health is the first fully comprehensive and current account of air pollution science and it impact on human health. It ranges in scope from meteorology, atmospheric chemistry, and particle physics to the causes and scope of allergic reactions and respiratory, cardiovascular, and related disorders. The book has substantial international coverage and includes sections on cost implications, risk assessment, regulation, standards, and information networks. The multidisciplinary approach and the wide range of issues covered makes this an essential book for all concerned with monitoring and regulating air pollution as well as those concerned with its impact on human health.
Key Features
* Only comprehensive text covering all the important air pollutants and relating these to human health and regulatory bodies
* Brings together a wide range of issues concerning air pollution in an easily accessible format
* Contributions from government agencies in the US and UK provide information on public policy and resource networks in the areas of health promotion and environmental protection

This book focuses on analytical similarity assessment in biosimilar product development following the FDA's recommended stepwise approach for obtaining totality-of-the-evidence for approval of biosimilar products. It covers concepts such as the tiered approach for assessment of similarity of critical quality attributes in the manufacturing process of biosimilar products, models/methods like the statistical model for classification of critical quality attributes, equivalence tests for critical quality attributes in Tier 1 and the corresponding sample size requirements, current issues, and recent developments in analytical similarity assessment.

Statistics in Practice A new series of practical books outlining the use of statistical techniques in a wide range of application areas:

• Human and Biological Sciences
• Earth and Environmental Sciences
• Industry, Commerce and Finance

• Estimation of survival curves.
• Non-parametric methods for comparison of survival curves.
• The Cox regression model.
• The parametric regression model.
• The study of prognostic factors.
• Competing risks.

The aim of this book is to suggest and exemplify a systematic methodology for analysing survival data which contains "immune," or "cured" individuals, denoted generically as "long-term survivors." Such data occurs in medical and epidemiological applications, where the intention may be to identify whether or not cured or immune individuals are present in a population, perhaps as a result of treatments given; in the analysis of recidivism data in criminology, where the intentions are similar with respect to prisoners released from and possibly returning to prison; and in many other areas where followup data is available on individuals, with the possibility that not all suffer the event under investigation. Both nonparametric and parametric methods are proposed and developed. The effects of covariate information can be assessed via a kind of generalised linear framework in the parametric analyses. The proposed methodologies are supported by asymptotic analyses and simulations of real situations. While these theoretical underpinnings are presented in reasonable rigour and detail, the book is aimed very much at the practitioner who wishes to analyse survival data with (or even without) immunes.

Anthropological contributions to the study of infectious disease and to the study of actual infectious disease eradication programmes have rarely been collected in one volume. In the era of AIDS and the global resurgance of infectious diseases such as tuberculosis and malaria, there is widespread interest and concern about the cultural, ecological and political factors that are directly related to the increased prevalence of infectious disease. In this book, the authors have assembled the growing scholarship in one volume. Chapters explore the coevolution of genes and cultural traits; the cultural construction of 'disease' and how these models influence health-seeking behaviour; cultural adaptive strategies to infectious disease problems; the ways in which ethnography sheds light on epidemiological patterns of infectious disease; the practical and ethical dilemmas that anthropologists face by participating in infectious disease programmes; and the political ecology of infectious disease.

This book deals with the mathematical aspects of survival analysis and reliability as well as other topics, reflecting recent developments in the following areas: applications in epidemiology; probabilistic and statistical models and methods in reliability; models and methods in survival analysis, longevity, aging, and degradation; accelerated life models; quality of life; new statistical challenges in genomics.

The work will be useful to a broad interdisciplinary readership of researchers and practitioners in applied probability and statistics, industrial statistics, biomedicine, biostatistics, and engineering.

Anthropological contributions to the study of infectious disease and to the study of actual infectious disease eradication programmes have rarely been collected in one volume. In the era of AIDS and the global resurgance of infectious diseases such as tuberculosis and malaria, there is widespread interest and concern about the cultural, ecological and political factors that are directly related to the increased prevalence of infectious disease. In this book, the authors have assembled the growing scholarship in one volume. Chapters explore the coevolution of genes and cultural traits; the cultural construction of 'disease' and how these models influence health-seeking behaviour; cultural adaptive strategies to infectious disease problems; the ways in which ethnography sheds light on epidemiological patterns of infectious disease; the practical and ethical dilemmas that anthropologists face by participating in infectious disease programmes; and the political ecology of infectious disease.

DIRECTLY APPLIES TO LIFE ON LAND SDG and CLIMATE CHANGE SDG. International organizations such as the Intergovernmental Panel on Climate Change (IPPC), World Health Organization, Food and Agriculture Organization and World Organization for Animal Health have all reminded us that health impacts of climate change will become some of societies' greatest challenges. How we respond or adapt to climate change will have profound implications for people, animals, biodiversity, economies and ecosystems today as well as in the future. The book provides, in one easy reference, all of the information Animal Health practitioners need from defining the climate change concept, providing science-based evidence of climate change degradation of animal (ecosystem) health and successful mitigation and reversal strategies. Despite being arguably the most important challenges of the 21st century, engagement, and leadership from the animal health sector on climate change remains hard to find. This book attempts to support animal health professionals by providing information, knowledge, and experiences they can use to remedy this situation. There is no other book that covers anything like the proposed subject matter to this level of completeness and detail. The publishing of a text of this nature could help erode the power of the climate denialism lobby, shifting the debate and allowing mitigation efforts to gain higher priority. The tone of the book has an understated sense of urgency, leaning slightly toward presenting as a 'Manual for the apocalypse'. This has potential to be a benchmark publication. The text not only defines climate change but takes a proactive approach with intervention and corrective action examples: each chapter ends with suggestions on teachable and actionable ideas that could be used to mobilize concepts and information provided into education or advocacy. In this way, the book not only brings key ideas, principles and information to understand the implications for climate change for animal health, but will help translate the book's offerings into education and intervention. Teachers and researchers could use this one-of-a-kind book to frame a course or seminar series heightening student career engagement and stewardship of a more sustainable and healthier planet.

Series Information:
Social Aspects of AIDS

Praise for the Second Edition: "... this is a useful, comprehensive compendium of almost every possible sample size formula. The strong organization and carefully defined formulae will aid any researcher designing a study." -Biometrics "This impressive book contains formulae for computing sample size in a wide range of settings. One-sample studies and two-sample comparisons for quantitative, binary, and time-to-event outcomes are covered comprehensively, with separate sample size formulae for testing equality, non-inferiority, and equivalence. Many less familiar topics are also covered ..." - Journal of the Royal Statistical Society Sample Size Calculations in Clinical Research, Third Edition presents statistical procedures for performing sample size calculations during various phases of clinical research and development. A comprehensive and unified presentation of statistical concepts and practical applications, this book includes a well-balanced summary of current and emerging clinical issues, regulatory requirements, and recently developed statistical methodologies for sample size calculation. Features: Compares the relative merits and disadvantages of statistical methods for sample size calculations Explains how the formulae and procedures for sample size calculations can be used in a variety of clinical research and development stages Presents real-world examples from several therapeutic areas, including cardiovascular medicine, the central nervous system, anti-infective medicine, oncology, and women's health Provides sample size calculations for dose response studies, microarray studies, and Bayesian approaches This new edition is updated throughout, includes many new sections, and five new chapters on emerging topics: two stage seamless adaptive designs, cluster randomized trial design, zero-inflated Poisson distribution, clinical trials with extremely low incidence rates, and clinical trial simulation.

AIDS, Drugs and Prevention brings together a range of international contributions on the research, theory and practice of developing community-based HIV prevention. It aims to understand how individual actions to prevent HIV transmission are constrained and encouraged by situational and social context. Drawing on ethnographic and epidemiological research among populations of drug users, sex workers and gay men, it explores how future HIV prevention interventions can target changes at the level of the individual as well as at the level of the community and wider social environment.
AIDS, Drugs and Prevention offers practical and theoretical insights into community-based health work in the time of AIDS. It provides invaluable reading for students, lecturers, researchers and practioners in health promotion, health policy, social work and medical sociology.

Since early-on in the epidemic, there has been much interest in the role that bisexual behaviour among men may play in HIV transmission. This text reviews from an international perspective what has been learned about male bisexuality in countries as diverse as Peru and Britain. Its authors examine the forms that bisexuality takes in different cultures, what it means to the men concerned, and whether or not such behaviour poses special risks. The implications of such enquiry for HIV prevention efforts are also examined.

"AIDS, Drugs and Prevention" brings together a range of international contributions on the research, theory and practice of developing community-based HIV prevention. Its aims to understand how individual actions to prevent HIV transmission are constrained and encouraged by situational and social context. Drawing on ethnographic and epidemiological research among populations of drug users, sex workers and gay men, it explores how future HIV prevention interventions can target changes at the level of the individual as well as at the level of the community and wider social environment.
Essays are presented from an international group of contributors, including fifteen US scholars: Robert S. Broadhead, Richard Curtis, Don C. Des Jarlais, Samuel R. Friedman, Jean-Paul C. Grund, Douglas D. Heckathorn, Benny Jose, Steven K. Koester, Alan Neaigus, Cindy Patton, Bruce Stepherson, L. Synn Stern, Meryl Sufian, John K. Watters and Wayne Wiebel. "AIDS, Drugs and Prevention" considers the diverse practices of community-based responses to HIV prevention in theoretical contexts and addresses the problems of professional practice. It will be invaluable reading for lecturers, researchers and practitioners in health promotion, health policy, social work and medical sociology.

This captivating study tells Mexico's best untold stories. The book takes the devastating 1833 cholera epidemic as its dramatic center and expands beyond this episode to explore love, lust, lies, and midwives. Parish archives and other sources tell us human stories about the intimate decisions, hopes, aspirations, and religious commitments of Mexican men and women as they made their way through the transition from the Viceroyalty of New Spain to an independent republic. In this volume Stevens shows how Mexico assumed a new place in Atlantic history as a nation coming to grips with modernization and colonial heritage, helping us to understand the paradox of a country with a reputation for fervent Catholicism that moved so quickly to disestablish the Church.

Fuzzy Logic in Action: Applications in Epidemiology and Beyond, co-authored by Eduardo Massad, Neli Ortega, Laecio Barros, and Claudio Struchiner is a remarkable achievement. The book brings a major paradigm shift to medical sciences exploring the use of fuzzy sets in epidemiology and medical diagnosis arena. The volume addresses the most significant topics in the broad areas of epidemiology, mathematical modeling and uncertainty, embodying them within the framework of fuzzy set and dynamic systems theory. Written by leading contributors to the area of epidemiology, medical informatics and mathematics, the book combines a very lucid and authoritative exposition of the fundamentals of fuzzy sets with an insightful use of the fundamentals in the area of epidemiology and diagnosis. The content is clearly illustrated by numerous illustrative examples and several real world applications. Based on their profound knowledge of epidemiology and mathematical modeling, and on their keen understanding of the role played by uncertainty and fuzzy sets, the authors provide insights into the connections between biological phenomena and dynamic systems as a mean to predict, diagnose, and prescribe actions. An example is the use of Bellman-Zadeh fuzzy decision making approach to develop a vaccination strategy to manage measles epidemics in Sao Paulo. The book offers a comprehensive, systematic, fully updated and self- contained treatise of fuzzy sets in epidemiology and diagnosis. Its content covers material of vital interest to students, researchers and practitioners and is suitable both as a textbook and as a reference. The authors present new results of their own in most of the chapters. In doing so, they reflect the trend to view fuzzy sets, probability theory and statistics as an association of complementary and synergetic modeling methodologies.

Geographies of Plague Pandemics synthesizes our current understanding of the spatial and temporal dynamics of plague, Yersinia pestis. The environmental, political, economic, and social impacts of the plague from Ancient Greece to the modern day are examined. Chapters explore the identity of plague DNA, its human mortality, and the source of ancient and modern plagues. This book also discusses the role plague has played in shifting power from Mediterranean Europe to north-western Europe during the 500 years that plague has raged across the continent. The book demonstrates how recent colonial structures influenced the spread and mortality of plague while changing colonial histories. In addition, this book provides critical insight into how plague has shaped modern medicine, public health, and disease monitoring, and what role, if any, it might play as a terror weapon. The scope and breadth of Geographies of Plague Pandemics offers geographers, historians, biologists, and public health educators the opportunity to explore the deep connections among disease and human existence.

Intended for ethologists and sociologists, this text examines the problem of defining the "meaning of illness", an interpretation developed within a society which can itself be studied and interpreted from without, from a variety of viewpoints depending on the academic discipline to which observation has been allocated; to ethnology, for example, the observation of linear-based societies; to sociology, that of industrial societies. The fact that these distinctions today are called into question is of little importance. They encourage a questioning of the relationships between the respective methods and objectives of the different disciplines. The local interpretation of illness is one thing, but it is quite possible that the interpretation of this interpretation could vary, depending on whether it was the product of different methods - (anthropological, sociological, historical) or on whether it was applied to different societies. The situation may become even more complicated, since the question can always be raised as to whether types of method and types of society are linked, whether one type of society implies one type of method.

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.