This book provides a comprehensive introduction to computational epidemiology, highlighting its major methodological paradigms throughout the development of the field while emphasizing the needs for a new paradigm shift in order to most effectively address the increasingly complex real-world challenges in disease control and prevention. Specifically, the book presents the basic concepts, related computational models, and tools that are useful for characterizing disease transmission dynamics with respect to a heterogeneous host population. In addition, it shows how to develop and apply computational methods to tackle the challenges involved in population-level intervention, such as prioritized vaccine allocation. A unique feature of this book is that its examination on the issues of vaccination decision-making is not confined only to the question of how to develop strategic policies on prioritized interventions, as it further approaches the issues from the perspective of individuals, offering a well integrated cost-benefit and social-influence account for voluntary vaccination decisions. One of the most important contributions of this book lies in it offers a blueprint on a novel methodological paradigm in epidemiology, namely, systems epidemiology, with detailed systems modeling principles, as well as practical steps and real-world examples, which can readily be applied in addressing future systems epidemiological challenges. The book is intended to serve as a reference book for researchers and practitioners in the fields of computer science and epidemiology. Together with the provided references on the key concepts, methods, and examples being introduced, the book can also readily be adopted as an introductory text for undergraduate and graduate courses in computational epidemiology as well as systems epidemiology, and as training materials for practitioners and field workers.

Provides a concise and intuitive overview of the role of statistics in surgical practice. Uses no mathematics but includes narrative descriptions of statistical concepts. Includes topics of specific interest to surgeons. Provides real surgical examples to illustrate applications.

Extracted from the Drug Abuse Handbook, 2nd edition, to give you just the information you need at an affordable price.

Postmortem Toxicology of Abused Drugs considers the role of toxicology in the investigation of homicide, suicide, accident, natural death, and overdose. It gives practical insights and case reviews on conducting toxicology tests and completing toxicology reports. It explains chain of custody; specimen collection and security; sampling of blood, urine, bile, and vitreous humor; and the selection of post-mortem specimens. Analyzing various testing procedures, the book covers simple chemical tests, microdiffusion tests, chromatography, spectroscopy, and more. It also discusses methods and strategies for analysis; and covers quality assurance protocols and controls. To help avoid common pitfalls, the text demonstrates the proper interpretation of postmortem drug levels based on knowledge of pharmacokinetics, metabolism, and pharmacogenetics; post-mortem redistribution and diffusion; and other considerations such as synergistic toxicity, and drug instability. Heavily referenced and containing several tables, figures, and useful appendices, this book is a handy reference for forensic scientists and medical examiners involved with death investigation.

Published in 1986: This book tells the story of how various persons and groups have successfully dealt with a type of problem which may threaten the lives and health of every group of humans - every community. The problem is that of a polluted environment.

The Statistical Analysis of Multivariate Failure Time Data: A Marginal Modeling Approach provides an innovative look at methods for the analysis of correlated failure times. The focus is on the use of marginal single and marginal double failure hazard rate estimators for the extraction of regression information. For example, in a context of randomized trial or cohort studies, the results go beyond that obtained by analyzing each failure time outcome in a univariate fashion. The book is addressed to researchers, practitioners, and graduate students, and can be used as a reference or as a graduate course text. Much of the literature on the analysis of censored correlated failure time data uses frailty or copula models to allow for residual dependencies among failure times, given covariates. In contrast, this book provides a detailed account of recently developed methods for the simultaneous estimation of marginal single and dual outcome hazard rate regression parameters, with emphasis on multiplicative (Cox) models. Illustrations are provided of the utility of these methods using Women's Health Initiative randomized controlled trial data of menopausal hormones and of a low-fat dietary pattern intervention. As byproducts, these methods provide flexible semiparametric estimators of pairwise bivariate survivor functions at specified covariate histories, as well as semiparametric estimators of cross ratio and concordance functions given covariates. The presentation also describes how these innovative methods may extend to handle issues of dependent censorship, missing and mismeasured covariates, and joint modeling of failure times and covariates, setting the stage for additional theoretical and applied developments. This book extends and continues the style of the classic Statistical Analysis of Failure Time Data by Kalbfleisch and Prentice. Ross L. Prentice is Professor of Biostatistics at the Fred Hutchinson Cancer Research Center and University of Washington in Seattle, Washington. He is the recipient of COPSS Presidents and Fisher awards, the AACR Epidemiology/Prevention and Team Science awards, and is a member of the National Academy of Medicine. Shanshan Zhao is a Principal Investigator at the National Institute of Environmental Health Sciences in Research Triangle Park, North Carolina.

Analysis of Correlated Data with SAS and R: 4th edition presents an applied treatment of recently developed statistical models and methods for the analysis of hierarchical binary, count and continuous response data. It explains how to use procedures in SAS and packages in R for exploring data, fitting appropriate models, presenting programming codes and results. The book is designed for senior undergraduate and graduate students in the health sciences, epidemiology, statistics, and biostatistics as well as clinical researchers, and consulting statisticians who can apply the methods with their own data analyses. In each chapter a brief description of the foundations of statistical theory needed to understand the methods is given, thereafter the author illustrates the applicability of the techniques by providing sufficient number of examples. The last three chapters of the 4th edition contain introductory material on propensity score analysis, meta-analysis and the treatment of missing data using SAS and R. These topics were not covered in previous editions. The main reason is that there is an increasing demand by clinical researchers to have these topics covered at a reasonably understandable level of complexity. Mohamed Shoukri is principal scientist and professor of biostatistics at The National Biotechnology Center, King Faisal Specialist Hospital and Research Center and Al-Faisal University, Saudi Arabia. Professor Shoukri's research includes analytic epidemiology, analysis of hierarchical data, and clinical biostatistics. He is an associate editor of the 3Biotech journal, a Fellow of the Royal Statistical Society and an elected member of the International Statistical Institute.

In a global clinical development strategy, multiregional clinical trials (MRCTs) are vital in the development of innovative medicines. Multiregional Clinical Trials for Simultaneous Global New Drug Development presents a comprehensive overview on the current status of conducting MRCTs in clinical development. International experts from academia, industry, and health organizations address various aspects of the important problems in global clinical development and MRCTs. The book first provides a high-level introduction to the context, motivation, opportunities, and challenges in simultaneous global clinical development using MRCTs. It then focuses on the design, monitoring, and analysis/interpretation of MRCTs. The book concludes with an examination of the latest research topics from MRCT perspectives, such as special considerations by local health authorities, health economic evaluations, benefit-risk assessment, and medical devices. Explaining how to design, conduct, and interpret MRCTs, this book will help biostatisticians working in the late-stage clinical development of medical products. It will also be useful for statisticians and clinicians in the biopharmaceutical industry, regulatory agencies, and medical research institutes.

Edited by a clinical psychologist who has been on the ground helping to develop psychosocial support for Ebola survivors in one of the hardest-hit regions of West Africa, this book explains the devastating emotional aspects of the epidemic and its impact on survivors and the population in West Africa, families in the diaspora, and people in the United States and other countries. It also describes lessons learned from past epidemics like HIV/AIDS and SARS, and valuable approaches to healing from future epidemics. While the devastating Ebola epidemic has been contained, the effects of this outbreak—referred to by the World Health Organization as "the most severe acute public health emergency seen in modern times"—have wreaked a tremendous emotional toll on the populations of West Africa as well as on families and survivors worldwide. This groundbreaking book covers the psychosocial needs, programs, and policies related to the Ebola epidemic and examines broader lessons of the outbreak, such as changes in the ways in which healing from future epidemics can be handled. Edited by Judy Kuriansky, PhD, a noted clinical psychologist and United Nations NGO representative with extensive experience helping after disasters worldwide, and direct experience gained from being "on the ground" in West Africa in the midst of the epidemic, this book identifies and explains universal psychological factors at play in all such crises. It debunks myths regarding Ebola and describes the resulting psychological and social harm caused by the epidemic. The chapters cover overarching emotional issues and problems as well as the long-term impact on at-risk groups, such as children, women, and health workers; the impact of emotional issues on social and economic life; responses of government officials, media, and various aid organizations; and solutions being offered by groups worldwide, including service and humanitarian organizations, politicians, policymakers, and public health education groups.

Thanks to enormous funding for educational programs, the whole world ?knows? that HIV causes AIDS. But is what we know compatible with the facts? This book challenges the conventional wisdom on this issue. Collating and analyzing, for the first time, the results of more than two decades of HIV testing, it reveals that the common assumptions about HIV and AIDS are incompatible with the published data. Among the many topics explored are the failings of HIV testing, statistical evidence that HIV is neither sexually transmitted nor increasingly prevalent, and problems caused by the differing diagnostic criteria for AIDS around the world. But how could everyone have been so wrong for so long? This vital question, unaddressed in previous works questioning the HIV-AIDS connection, is central to this book. The author considers comparable missteps of modern science, and discusses how funding influences discovery in today's scientific circles.

Statistical Analysis of Human Growth and Development is an accessible and practical guide to a wide range of basic and advanced statistical methods that are useful for studying human growth and development. Designed for nonstatisticians and statisticians new to the analysis of growth and development data, the book collects methods scattered throughout the literature and explains how to use them to solve common research problems. It also discusses how well a method addresses a specific scientific question and how to interpret and present the analytic results. Stata is used to implement the analyses, with Stata codes and macros for generating example data sets, a detrended Q-Q plot, and weighted maximum likelihood estimation of binary items available on the book's CRC Press web page. After reviewing research designs and basic statistical tools, the author discusses the use of existing tools to transform raw data into analyzable variables and back-transform them to raw data. He covers regression analysis of quantitative, binary, and censored data as well as the analysis of repeated measurements and clustered data. He also describes the development of new growth references and developmental indices, the generation of key variables based on longitudinal data, and the processes to verify the validity and reliability of measurement tools. Looking at the larger picture of research practice, the book concludes with coverage of missing values, multiplicity problems, and multivariable regression. Along with two simulated data sets, numerous examples from real experimental and observational studies illustrate the concepts and methods. Although the book focuses on examples of anthropometric measurements and changes in cognitive, social-emotional, locomotor, and other abilities, the ideas are applicable to many other physical and psychosocial phenomena, such as lung function and depressive symptoms.

Hospitals monitoring is becoming more complex and is increasing both because staff want their data analysed and because of increasing mandated surveillance. This book provides a suite of functions in R, enabling scientists and data analysts working in infection management and quality improvement departments in hospitals, to analyse their often non-independent data which is frequently in the form of trended, over-dispersed and sometimes auto-correlated time series; this is often difficult to analyse using standard office software. This book provides much-needed guidance on data analysis using R for the growing number of scientists in hospital departments who are responsible for producing reports, and who may have limited statistical expertise. This book explores data analysis using R and is aimed at scientists in hospital departments who are responsible for producing reports, and who are involved in improving safety. Professionals working in the healthcare quality and safety community will also find this book of interest Statistical Methods for Hospital Monitoring with R: * Provides functions to perform quality improvement and infection management data analysis. * Explores the characteristics of complex systems, such as self-organisation and emergent behaviour, along with their implications for such activities as root-cause analysis and the Pareto principle that seek few key causes of adverse events. * Provides a summary of key non-statistical aspects of hospital safety and easy to use functions. * Provides R scripts in an accompanying web site enabling analyses to be performed by the reader http://www.wiley.com/go/hospital-monitoring * Covers issues that will be of increasing importance in the future, such as, generalised additive models, and complex systems, networks and power laws.

A thoroughly updated new edition of the essential reference on the design, practice, and analysis of clinical trials

"Clinical Trials Dictionary: Terminology and Usage Recommendations, Second Edition "presents clear, precise, meticulously detailed entries on all" "aspects of modern-day clinical trials. Written and compiled by one of the world's leading clinical trialists, this comprehensive volume incorporates areas of medicine, statistics, epidemiology, computer science, and bioethics--providing a treasure trove of key terms and ideas.

This new edition continues to supply readers with the A-Z terminology needed to design, conduct, and analyze trials, introducing a vocabulary for the characterization and description of related features and activities. More than 300 new entries are now included, reflecting the current usage practices and conventions in the field, along with usage notes with recommendations on when to use the term in question. Detailed biographical notes highlight prominent historical figures and institutions in the field, and an extensive bibliography has been updated to provide readers with additional resources for further study.

The most up-to-date work of its kind, "Clinical Trials Dictionary, Second Edition "is an essential reference for anyone who needs to report on, index, " "analyze, or assess the scientific strength and validity of clinical trials.""

This book analyzes the development of female prostitution in the Pacific port of Puntarenas, Costa Rica during the advanced stage of the coffee exporting economy (1880-1930), at the height of the consolidation of the liberal state. Hayes argues that prostitution in the port differed from that of the coffee producing highlands due to differential economic, social, and political development. In the periphery of Puntarenas, the development of prostitution reflected a less stigmatized view of sexual commerce than that of the highlands, where prostitution, although legal, threatened the tenets of liberal nationalism based on racial homogeneity and family values. Women of the highlands were encouraged to reproduce the nation's "more European" stock of workers and to ensure the legal transference of property through legal church marriages - both part of a design to stabilize the coffee exporting project. By contrast, prostitutes and other working women of Puntarenas, many immigrants from the "less European" populations of neighboring regions and most in concubinage, were freer to do what the law prescribed - register as prostitutes in legitimate trade. Such regional disparities reveal weaknesses in traditional explanations of Costa Rican exceptionalism, which have rested on the premise of cultural homogeneity and have reflected the realities of only one region of the country. The book advances an alternative explanation for the development of the nation's more democratic institutions, situating Costa Rican exceptionalism in the nation's free labor system, of which the labor prostitute in Puntarenas provides an example.

A thorough treatment of the statistical methods used to analyze doubly truncated data In The Statistical Analysis of Doubly Truncated Data, an expert team of statisticians delivers an up-to-date review of existing methods used to deal with randomly truncated data, with a focus on the challenging problem of random double truncation. The authors comprehensively introduce doubly truncated data before moving on to discussions of the latest developments in the field. The book offers readers examples with R code along with real data from astronomy, engineering, and the biomedical sciences to illustrate and highlight the methods described within. Linear regression models for doubly truncated responses are provided and the influence of the bandwidth in the performance of kernel-type estimators, as well as guidelines for the selection of the smoothing parameter, are explored. Fully nonparametric and semiparametric estimators are explored and illustrated with real data. R code for reproducing the data examples is also provided. The book also offers: A thorough introduction to the existing methods that deal with randomly truncated data Comprehensive explorations of linear regression models for doubly truncated responses Practical discussions of the influence of bandwidth in the performance of kernel-type estimators and guidelines for the selection of the smoothing parameter In-depth examinations of nonparametric and semiparametric estimators Perfect for statistical professionals with some background in mathematical statistics, biostatisticians, and mathematicians with an interest in survival analysis and epidemiology, The Statistical Analysis of Doubly Truncated Data is also an invaluable addition to the libraries of biomedical scientists and practitioners, as well as postgraduate students studying survival analysis.

Patients are not alike! This simple truth is often ignored in the analysis of me- cal data, since most of the time results are presented for the "average" patient. As a result, potential variability between patients is ignored when presenting, e.g., the results of a multiple linear regression model. In medicine there are more and more attempts to individualize therapy; thus, from the author's point of view biostatis- cians should support these efforts. Therefore, one of the tasks of the statistician is to identify heterogeneity of patients and, if possible, to explain part of it with known explanatory covariates. Finite mixture models may be used to aid this purpose. This book tries to show that there are a large range of applications. They include the analysis of gene - pression data, pharmacokinetics, toxicology, and the determinants of beta-carotene plasma levels. Other examples include disease clustering, data from psychophysi- ogy, and meta-analysis of published studies. The book is intended as a resource for those interested in applying these methods.

A cluster randomization trial is one in which intact social units, or clusters of individuals, are randomized to different intervention groups. Trials randomizing clusters have become particularly widespread in the evaluation of non-therapeutic interventions, including lifestyle modification, educational programmes and innovations in the provision of health care. The increasing popularity of this design among health researchers over the past two decades has led to an extensive body of methodology on the subject. This is the first book to present a systematic and united treatment of this topic; it contains distinctive chapters on the history of cluster randomized trials, ethical issues and reporting guidelines.

The growing importance of the evidence-based movement has made experimental evaluation a key issue among researchers, practitioners, commissioners and policy makers. However, experimental evaluation remains controversial in the sexual health field. This partly reflects the diversity of groups involved in this area and their different views on the most appropriate research methods. This book provides an analysis of the methodological and practical issues involved in evaluating sexual health interventions.

The book will appeal to trial enthusiasts through discussion of specific issues in trial design, and also to those with a sceptical interest in the potential of experimentation and its appropriateness or feasibility. It is concerned with methodology rather than the substantive findings of research, and considers the requirements of research in both developed and developing countries. The focus of the book is on sexual health interventions, although many of the issues are equally applicable to other areas of behavioural and social research

This textbook focuses on the nascent field of Immunoepidemiology that addresses how differences in immune responses among individuals affect the epidemiology of infectious diseases, cancer, hypersensitivity, and autoimmunity. The idea for the book originated from a course entitled "Immunology for Epidemiologists" at the Yale School of Public Health. While many fine textbooks are available that address the immunological responses of individuals to pathogens, these provided very little information regarding how immunological variation among populations affects the epidemiology of disease. And yet, it has long been recognized that there is great immunologic diversity among people, which can have a profound effect on the epidemiology of disease. Careful review of the immunologic and epidemiologic literature revealed that there have been relatively few publications concerning immunoepidemiology and that no textbook is available on the subject. This textbook therefore aims to fill this void by providing a much-needed tool to comprehensively and efficiently teach immunoepidemiology. The book includes a section on the basic principles of immunology, and then applies them to particular examples of disease in human populations. The target audience for this text book are Masters of Public Health students. Others who should also find it of interest include PhD students in epidemiology, immunology, medical students, generalists, and specialists in immunology, infectious diseases, cancer, and rheumatology.

Findings from the field of evolutionary biology are yielding dramatic insights for health scientists, especially those involved in the fight against infectious diseases. This book is the first in-depth presentation of these insights. In detailing why the pathogens that cause malaria, smallpox, tuberculosis, and AIDS have their special kinds of deadliness, the book shows how efforts to control virtually all diseases would benefit from a more thorough application of evolutionary principles. When viewed from a Darwinian perspective, a pathogen is not simply a disease-causing agent, it is a self-replicating organism driven by evolutionary pressures to pass on as many copies of itself as possible. In this context, so-called "cultural vectors"--those aspects of human behavior and the human environment that allow spread of disease from immobilized people--become more important than ever. Interventions to control diseases don't simply hinder their spread but can cause pathogens and the diseases they engender to evolve into more benign forms. In fact, the union of health science with evolutionary biology offers an entirely new dimension to policy making, as the possibility of determining the future course of many diseases becomes a reality. By presenting the first detailed explanation of an evolutionary perspective on infectious disease, the author has achieved a genuine milestone in the synthesis of health science, epidemiology, and evolutionary biology. Written in a clear, accessible style, it is intended for a wide readership among professionals in these fields and general readers interested in science and health.

As screening programs for HIV, high cholesterol, high blood pressure, genetic abnormalities and other risk factors continue to proliferate, difficult questions are continually raised concerning the psychological and behavioral effects on the participants. Although members of the public health community have debated the costs and benefits of screening programs for over three decades, these questions have become especially pertinent with the current emphasis on early disease detection and prevention. While advocates argue that risk notification provides the impetus for individuals to improve their health habits and seek early treatment, skeptics contend that risk screening can have an adverse labeling effect, leading to increased anxiety, work absenteeism, and fatalism.
Now, for the first time, the widely scattered body of research on the effects of risk factor screening is comprehensively reviewed and evaluated in this volume. Here, an internationally recognized group of expert contributors summarizes and discusses current knowledge about the psychosocial consequences of risk factor testing, taking into account individual differences, gender differences, risk status, and intervention strategies. Both the public health and behavioral science viewpoints are explored through up-to-date reviews and stimulating commentary. Bridging the gap between data, theory and public health policy, this volume is essential reading for researchers, professionals and policymakers concerned with the prevention of acute and chronic disease.

For more than three thousand years of recorded history, human beings have been struggling to understand the epidemic - the rapid spread of a contagious disease throughout a human population. This book draws on an extensive list of primary texts to present a comprehensive history of epidemiological thought over the last three millennia. The book is primarily concerned with the human experience of epidemic disease and the various means through which this experience has been conceptualized and communicated. The discussion begins with the writers of antiquity, and Part I examines the religious, mythological and philosophical paradigms that ancient peoples used to comprehend and interpret epidemic disease. This dogmatic approach to the nature of disease is traced from Greco-Roman times to the present. Gradually, many people came to interpret the epidemic experience as a natural phenomenon rather than an instrument of divine purpose. The important transition from an emphasis on received doctrine to one on direct experience is the focus of Part II. Famous historical documents, such as Thucydides description of the plague of Athens in 430 B.C.E and Giovanni Boccaccio's description of the Black Death in The Decameron, are used to illuminate this transition. The systematic examination of biomedical phenomena that began in the seventeenth century and has developed into the complex field of modern medicine is the focus of Part III. Finally, Part IV considers the ways in which epidemic disease has been treated in various works of literature. The discussion includes factual eyewitness accounts as well as such popular works of fiction as Sinclair Lewis' Arrowsmith and Albert Camus' The Plague. In surveying human responses to endemic disease, the book relates three sub-genres of epidemiological writing to one another: the encyclopedia, the intellectual history, and the biographical collection. In all, this work covers one dozen illnesses, more than thirty select authors, and nearly fifty primary works.

Quantitative Methods in HIV/AIDS Research provides a comprehensive discussion of modern statistical approaches for the analysis of HIV/AIDS data. The first section focuses on statistical issues in clinical trials and epidemiology that are unique to or particularly challenging in HIV/AIDS research; the second section focuses on the analysis of laboratory data used for immune monitoring, biomarker discovery and vaccine development; the final section focuses on statistical issues in the mathematical modeling of HIV/AIDS pathogenesis, treatment and epidemiology. This book brings together a broad perspective of new quantitative methods in HIV/AIDS research, contributed by statisticians and mathematicians immersed in HIV research, many of whom are current or previous leaders of CFAR quantitative cores. It is the editors' hope that the work will inspire more statisticians, mathematicians and computer scientists to collaborate and contribute to the interdisciplinary challenges of understanding and addressing the AIDS pandemic.

This book offers an accessible and up-to-date reference on primate zoonoses. Recent years have witnessed a rise in human diseases zoonotically transferred from animals, with wild primates implicated in the spread of numerous newly emerging infections. The authors go beyond simply providing an inventory of diseases, helping readers to understand how and why they are transmitted. Important consideration is given to the contemporary cultural and ecological factors involved.

Containing method descriptions and step-by-step procedures, the Spatial Epidemiological Approaches in Disease Mapping and Analysis equips readers with skills to prepare health-related data in the proper format, process these data using relevant functions and software, and display the results as mapped or statistical summaries. Describing the wide range of available methods and key GIS concepts for spatial epidemiology, this book illustrates the utilities of the software using real-world data. Additional topics include geographic data models, address matching, geostatistical analysis, universal kriging, point pattern analysis, kernel density, spatio-temporal display, and disease surveillance.

Since 1945, "The Annual Deming Conference on Applied Statistics" has been an important event in the statistics profession. In Clinical Trial Biostatistics and Biopharmaceutical Applications, prominent speakers from past Deming conferences present novel biostatistical methodologies in clinical trials as well as up-to-date biostatistical applications from the pharmaceutical industry. Divided into five sections, the book begins with emerging issues in clinical trial design and analysis, including the roles of modeling and simulation, the pros and cons of randomization procedures, the design of Phase II dose-ranging trials, thorough QT/QTc clinical trials, and assay sensitivity and the constancy assumption in noninferiority trials. The second section examines adaptive designs in drug development, discusses the consequences of group-sequential and adaptive designs, and illustrates group sequential design in R. The third section focuses on oncology clinical trials, covering competing risks, escalation with overdose control (EWOC) dose finding, and interval-censored time-to-event data. In the fourth section, the book describes multiple test problems with applications to adaptive designs, graphical approaches to multiple testing, the estimation of simultaneous confidence intervals for multiple comparisons, and weighted parametric multiple testing methods. The final section discusses the statistical analysis of biomarkers from omics technologies, biomarker strategies applicable to clinical development, and the statistical evaluation of surrogate endpoints. This book clarifies important issues when designing and analyzing clinical trials, including several misunderstood and unresolved challenges. It will help readers choose the right method for their biostatistical application. Each chapter is self-contained with references.