The Eradication of Dracunculiasis (Guinea Worm Disease) in Nigeria: An Eyewitness Account documents the process used to eradicate one of the most neglected public health challenges in Nigeria. The book's chapters discuss the need for well developed and implemented eradication strategies, the availability of human and material resources, and the collaboration that is necessary with international partners. In addition, sections highlight challenges, the benefits of perseverance, and the international support and multi-sectoral approach that is needed to tackle national problems. It demonstrates that other endemic tropical diseases and conditions can be eliminated or controlled if a similar approach is adopted.

Theory of Drug Development presents a formal quantitative framework for understanding drug development that goes beyond simply describing the properties of the statistics in individual studies. It examines the drug development process from the perspectives of drug companies and regulatory agencies. By quantifying various ideas underlying drug development, the book shows how to systematically address problems, such as: Sizing a phase 2 trial and choosing the range of p-values that will trigger a follow-up phase 3 trial Deciding whether a drug should receive marketing approval based on its phase 2/3 development program and recent experience with other drugs in the same clinical area Determining the impact of adaptive designs on the quality of drugs that receive marketing approval Designing a phase 3 pivotal study that permits the data-driven adjustment of the treatment effect estimate Knowing when enough information has been gathered to show that a drug improves the survival time for the whole patient population Drawing on his extensive work as a statistician in the pharmaceutical industry, the author focuses on the efficient development of drugs and the quantification of evidence in drug development. He provides a rationale for underpowered phase 2 trials based on the notion of efficiency, which leads to the identification of an admissible family of phase 2 designs. He also develops a framework for evaluating the strength of evidence generated by clinical trials. This approach is based on the ratio of power to type 1 error and transcends typical Bayesian and frequentist statistical analyses.

How does pollution impact our daily quality of life? What are the effects of pollution on children's development? Why do industry and environmental experts disagree about what levels of pollutants are safe? This clearly written book, traces the debates over five key pollutants - lead, mercury, noise, pesticides, and dioxins and PCBs - and provides an overview of the history of each pollutant, basic research findings, and the scientific and regulatory controversies surrounding it. It focuses, in particular, on the impact of these pollutants on children's psychological development, their intellectual functioning, behaviour, and emotional states. Only by understanding the impact of pollution can we prevent future negative effects on quality of life and even pollution disasters from occurring. This volume will be of great interest to parents, child health care experts, public health officials, regulators, and health and environmental lawyers.

Seasonal fluctuations in mortality are a persistent phenomenon, but variations from culture to culture pose fascinating questions. This book investigates whether sociodemographic and socioeconomic factors play a role as important for seasonal mortality as they do for mortality in general. Using modern statistical methods, the book shows, for example, that in the United States the fluctuations between winter and summer mortality are smaller the more years someone has spent in school.

An essential collection that advances our understanding of how cities influence our health More than half the world's population lives in cities - a figure that will grow to two-thirds by 2030. As global populations rapidly consolidate around urban centers, the scientific understanding of what this means for human health faces a new and greater urgency. Urban Health connects urban exposures - the experiences, choices, and behaviors shaped by living in a city - to their impact on population health. By using the ubiquitous aspects of the urban experience as a lens to study these exposures across borders and demographics, it offers a new, scalable framework for understanding health and disease. Its applications to public health, epidemiology, and social science are virtually unlimited. Enriched with case studies that consider the state of health in cities all over the world, this book does more than capture the state of a nascent field; it holds a critical mirror to itself, considering the next decade and arming a new generation with the tools for research and practice.

While regression models have become standard tools in medical research, understanding how to properly apply the models and interpret the results is often challenging for beginners. Regression Models as a Tool in Medical Research presents the fundamental concepts and important aspects of regression models most commonly used in medical research, including the classical regression model for continuous outcomes, the logistic regression model for binary outcomes, and the Cox proportional hazards model for survival data. The text emphasizes adequate use, correct interpretation of results, appropriate presentation of results, and avoidance of potential pitfalls. After reviewing popular models and basic methods, the book focuses on advanced topics and techniques. It considers the comparison of regression coefficients, the selection of covariates, the modeling of nonlinear and nonadditive effects, and the analysis of clustered and longitudinal data, highlighting the impact of selection mechanisms, measurement error, and incomplete covariate data. The text then covers the use of regression models to construct risk scores and predictors. It also gives an overview of more specific regression models and their applications as well as alternatives to regression modeling. The mathematical details underlying the estimation and inference techniques are provided in the appendices.

COVID-19: Surviving a Pandemic provides critical insights into survival strategies employed by communities and individuals around the world during the pandemic. A central question since this pandemic began has been how to survive it. That question has applied not just to staying alive, but also to staying healthy, both physically and mentally. Survival is certainly key, but surviving, and what that means, is also critical. The scholarship included in this volume will take a closer look at what it means to survive by addressing such issues as the importance of ethnicity in vaccine uptake, the gendered and racialized impacts of the pandemic, the impact on those with disabilities, questions of food security, and what it means to grieve. Drawing on the expertise of scholars from around the world, the work presented here represents a remarkable diversity and quality of impassioned scholarship on the impact of COVID-19 and is a timely and critical advance in knowledge related to the pandemic.

Explore Important Tools for High-Quality Work in Pharmaceutical Safety Statistical Methods for Drug Safety presents a wide variety of statistical approaches for analyzing pharmacoepidemiologic data. It covers both commonly used techniques, such as proportional reporting ratios for the analysis of spontaneous adverse event reports, and newer approaches, such as the use of marginal structural models for controlling dynamic selection bias in the analysis of large-scale longitudinal observational data. Choose the Right Statistical Approach for Analyzing Your Drug Safety Data The book describes linear and non-linear mixed-effects models, discrete-time survival models, and new approaches to the meta-analysis of rare binary adverse events. It explores research involving the re-analysis of complete longitudinal patient records from randomized clinical trials. The book discusses causal inference models, including propensity score matching, marginal structural models, and differential effects, as well as mixed-effects Poisson regression models for analyzing ecological data, such as county-level adverse event rates. The authors also cover numerous other methods useful for the analysis of within-subject and between-subject variation in adverse events abstracted from large-scale medical claims databases, electronic health records, and additional observational data streams. Advance Statistical Practice in Pharmacoepidemiology Authored by two professors at the forefront of developing new statistical methodologies to address pharmacoepidemiologic problems, this book provides a cohesive compendium of statistical methods that pharmacoepidemiologists can readily use in their work. It also encourages statistical scientists to develop new methods that go beyond the foundation covered in the text.

This volume elaborately studies the challenges posed and impact made by the Covid 19 pandemic. Through detailed case studies, it presents ethical, political, economic, medical, logistical and social impediments faced by contemporary states in the EU. The book focuses on the short and long-term consequences of the economic shock caused by the COVID-19 pandemic and covers issues concerning the world economy, the EU economy, as well as the Visegrad economies. The essays in this volume: Probes into the response of states to the economic phenomena resulting from the pandemic and analyses the institutional framework of the resulting crisis, lapses in social communication, social protests and the decline in democratic standards in countries such as the Czech Republic, Poland, Slovakia, and Hungary; Discusses issues related to state security under conditions of the pandemic, the effectiveness of state and self-government administration, the transition of states from an external controllability to an internal controllability model of power, as well as challenges related to security in the digital space; Presents policy actions at three basic levels, i.e. at the global, regional and sub-regional, and investigate strategies of the UN, WHO, the EU and the Visegrad Group as they play the most important role in the fight against COVID-19; This insightful and timely volume will be of great interest to scholars, researchers and anyone inquisitive about political theory, public policy, public health and social care, international relations, governance, security studies, and public administration.

- The only textbook that combines an introduction to both the technical operations and conceptual premises of biostatistics - Details the conceptual consequences of the mathematical premises of biostatistics that distort our understanding of holistic and contextual nature of health and medicine - Emphasizes the qualitative and subjective decisions that precede any quantitative analysis - The conceptual implications of biostatistical tools and techniques-such as contriving to fit objects to tools rather than fitting tools to objects-apply equally to statistics in general - Presents univariate, bivariate, and regression analysis through a single common scenario to facilitate student comprehension - Organizes biostatistical tools and techniques into nine configurations that help frame use and rationale of statistical tests and measures - Walks the reader through the technical steps for the examples associated with the nine configurations

Encyclopedic in breadth, yet practical and concise, Medical Biostatistics, Fourth Edition focuses on the statistical aspects ofmedicine with a medical perspective, showing the utility of biostatistics as a tool to manage many medical uncertainties. This edition includes more topics in order to fill gaps in the previous edition. Various topics have been enlarged and modified as per the new understanding of the subject.

With ever-rising healthcare costs, evidence generation through Health Economics and Outcomes Research (HEOR) plays an increasingly important role in decision-making about the allocation of resources. Accordingly, it is now customary for health technology assessment and reimbursement agencies to request for HEOR evidence, in addition to data from clinical trials, to inform decisions about patient access to new treatment options. While there is a great deal of literature on HEOR, there is a need for a volume that presents a coherent and unified review of the major issues that arise in application, especially from a statistical perspective. Statistical Topics in Health Economics and Outcomes Research fulfils that need by presenting an overview of the key analytical issues and best practice. Special attention is paid to key assumptions and other salient features of statistical methods customarily used in the area, and appropriate and relatively comprehensive references are made to emerging trends. The content of the book is purposefully designed to be accessible to readers with basic quantitative backgrounds, while providing an in-depth coverage of relatively complex statistical issues. The book will make a very useful reference for researchers in the pharmaceutical industry, academia, and research institutions involved with HEOR studies. The targeted readers may include statisticians, data scientists, epidemiologists, outcomes researchers, health economists, and healthcare policy and decision-makers.

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

Using real data sets throughout, Survival Analysis in Medicine and Genetics introduces the latest methods for analyzing high-dimensional survival data. It provides thorough coverage of recent statistical developments in the medical and genetics fields. The text mainly addresses special concerns of the survival model. After covering the fundamentals, it discusses interval censoring, nonparametric and semiparametric hazard regression, multivariate survival data analysis, the sub-distribution method for competing risks data, the cure rate model, and Bayesian inference methods. The authors then focus on time-dependent diagnostic medicine and high-dimensional genetic data analysis. Many of the methods are illustrated with clinical examples. Emphasizing the applications of survival analysis techniques in genetics, this book presents a statistical framework for burgeoning research in this area and offers a set of established approaches for statistical analysis. It reveals a new way of looking at how predictors are associated with censored survival time and extracts novel statistical genetic methods for censored survival time outcome from the vast amount of research results in genomics.

Hepatitis C in Developing Countries: Current and Future Challenges explores the current state of HCV in several countries, including Africa, Asia and South America. It maintains a dedicated focus on the epidemiology, clinical patterns, virologic diversity, coinfections, natural history and progression, complications, and response to standard of care (SOC) pegylated interferon and ribavirin therapy of HCV with recommendations specific to middle and low income countries. Readers will find detailed information on the burden of HCV infection from a global health and economic perspective, along with data from multicenter trials on DAAs that have enrolled patients infected with HCV non-genotype 1.

Many new challenges have arisen in the area of oncology clinical trials. New cancer therapies are often based on cytostatic or targeted agents, which pose new challenges in the design and analysis of all phases of trials. The literature on adaptive trial designs and early stopping has been exploding. Inclusion of high-dimensional data and imaging techniques have become common practice, and statistical methods on how to analyse such data have been refined in this area. A compilation of statistical topics relevant to these new advances in cancer research, this third edition of Handbook of Statistics in Clinical Oncology focuses on the design and analysis of oncology clinical trials and translational research. Addressing the many challenges that have arisen since the publication of its predecessor, this third edition covers the newest developments involved in the design and analysis of cancer clinical trials, incorporating updates to all four parts: Phase I trials: Updated recommendations regarding the standard 3 + 3 and continual reassessment approaches, along with new chapters on phase 0 trials and phase I trial design for targeted agents. Phase II trials: Updates to current experience in single-arm and randomized phase II trial designs. New chapters include phase II designs with multiple strata and phase II/III designs. Phase III trials: Many new chapters include interim analyses and early stopping considerations, phase III trial designs for targeted agents and for testing the ability of markers, adaptive trial designs, cure rate survival models, statistical methods of imaging, as well as a thorough review of software for the design and analysis of clinical trials. Exploratory and high-dimensional data analyses: All chapters in this part have been thoroughly updated since the last edition. New chapters address methods for analyzing SNP data and for developing a score based on gene expression data. In addition, chapters on risk calculators and forensic bioinformatics have been added. Accessible to statisticians and oncologists interested in clinical trial methodology, the book is a single-source collection of up-to-date statistical approaches to research in clinical oncology.

Disaster Epidemiology: Methods and Applications applies the core methods of epidemiological research and practice to the assessment of the short- and long-term health effects of disasters. The persistent movement of people and economic development to regions vulnerable to natural disasters, as well as new vulnerabilities related to environmental, technological, and terrorism incidents, means that in spite of large global efforts to reduce the impacts and costs of disasters, average annual expenditures to fund rebuilding from catastrophic losses is rising faster than either population or the gross world product. Improving the resilience of individuals and communities to these natural and technological disasters, climate change, and other natural and manmade stressors is one of the grand challenges of the 21st century. This book provides a guide to disaster epidemiology methods, supported with applications from practice. It helps researchers, public health practitioners, and governmental policy makers to better quantify the impacts of disaster on the health of individuals and communities to enhance resilience to future disasters. Disaster Epidemiology: Methods and Applications explains how public health surveillance, rapid assessments, and other epidemiologic studies can be conducted in the post-disaster setting to prevent injury, illness, or death; provide accurate and timely information for decisions makers; and improve prevention and mitigation strategies for future disasters. These methods can also be applied to the study of other types of public health emergencies, such as infectious outbreaks, emerging and re-emerging diseases, and refugee health. This book gives both the public health practitioner and researcher the tools they need to conduct epidemiological studies in a disaster setting and can be used as a reference or as part of a course.

In Cancer Screening: A Practical Guide for Physicians, a panel of highly experienced clinicians and researchers from around the world present their up-to-date screening techniques for a wide variety of cancers. The techniques range from screening for breast, gynecological, and gastrointestinal cancers, to testing for urogenital, dermatological, and respiratory cancers. In addition to providing the busy practitioner with quick access to guidelines for particular cancers, the epidemiology and biology of the various cancers, as well as the sensitivity and specificity of the methods, are discussed in detail. Authoritative and physician-friendly, Cancer Screening: A Practical Guide for Physicians offers to all internists, oncologists, various subspecialists, and primary care physicians a concise practical review of cancer screening designed specifically for daily use in the consulting room.

Features Represents the first book to provide comprehensive coverage of model-assisted designs for various types of dose-finding and optimization clinical trials Describes the up-to-date theory and practice for model-assisted designs Presents many practical challenges and issues arising from early-phase clinical trials Illustrates with many real trial applications Offers numerous tips and guidance on designing dose finding and optimization trials Provides step-by-step illustration of using software to design trials Develops a companion website (www.trialdesign.org) to provide easy-to-use software to assist learning and implementing model-assisted designs.

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.

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.

Somewhere in the world, in the next forty seconds, a person is going to commit suicide. Globally, suicides account for 50 percent of all violent deaths among men and 71 percent for women. Despite suicide prevention programs, therapy, and pharmacological treatments, the suicide rate is either increasing or remaining high around the world. Media and Suicide holds traditional and emergent media accountable for influencing an individual's decision to commit suicide. Global experts present research, historical analysis, theoretical disputes (including discussion on the Werther and Papageno effects), and policy regarding the media's impact on suicide. They answer questions about the effects of different types of media and storytelling, show how the impact of social media can be diminished, discuss internet bullying, mass-shootings and mass-suicides, show the effects of recovery stories, and much more. The editors also present examples of suicide policy in the United States, Switzerland, the United Kingdom, Ireland, and Hong Kong on how to best communicate reporting guidelines to decrease the copycat effect, especially in less developed nations where most of the world's nearly one million suicides occur each year. Although there is much work to be done to prevent media-influenced suicide, this innovative volume will contribute a large piece to this complex puzzle.

Wide-Ranging Coverage of Parametric Modeling in Linear and Nonlinear Mixed Effects ModelsMixed Effects Models for the Population Approach: Models, Tasks, Methods and Tools presents a rigorous framework for describing, implementing, and using mixed effects models. With these models, readers can perform parameter estimation and modeling across a whole population of individuals at the same time. Easy-to-Use Techniques and Tools for Real-World Data ModelingThe book first shows how the framework allows model representation for different data types, including continuous, categorical, count, and time-to-event data. This leads to the use of generic methods, such as the stochastic approximation of the EM algorithm (SAEM), for modeling these diverse data types. The book also covers other essential methods, including Markov chain Monte Carlo (MCMC) and importance sampling techniques. The author uses publicly available software tools to illustrate modeling tasks. Methods are implemented in Monolix, and models are visually explored using Mlxplore and simulated using Simulx. Careful Balance of Mathematical Representation and Practical ImplementationThis book takes readers through the whole modeling process, from defining/creating a parametric model to performing tasks on the model using various mathematical methods. Statisticians and mathematicians will appreciate the rigorous representation of the models and theoretical properties of the methods while modelers will welcome the practical capabilities of the tools. The book is also useful for training and teaching in any field where population modeling occurs.

CONTAINS IMPORTANT INFORMATION ABOUT THE CORONAVIRUS! "Portrays epidemiologists as disease detectives who tirelessly hunt for clues and excel at deductive reasoning. Even Sherlock Holmes would be proud of this astute group of professionals."-Booklist This updated edition features a brand new section detailing important facts about the coronavirus and tips for keeping yourself and your family safe. Despite advances in health care, infectious microbes continue to be a formidable adversary to scientists and doctors. Vaccines and antibiotics, the mainstays of modern medicine, have not been able to conquer infectious microbes because of their amazing ability to adapt, evolve, and spread to new places. Terrorism aside, one of the greatest dangers from infectious disease we face today is from a massive outbreak of drug-resistant microbes. Deadly Outbreaks recounts the scientific adventures of a special group of intrepid individuals who investigate these outbreaks around the world and figure out how to stop them. Part homicide detective, part physician, these medical investigators must view the problem from every angle, exhausting every possible source of contamination. Any data gathered in the field must be stripped of human sorrows and carefully analyzed into hard statistics. Author Alexandra Levitt, PhD, is an expert on emerging diseases and other public health threats. Here she shares insider accounts she's collected that go behind the alarming headlines we've seen in the media: mysterious food poisonings, unexplained deaths at a children's hospital, a strange neurologic disease afflicting slaughterhouse workers, flocks of birds dropping dead out of the sky, and drug-resistant malaria running rampant in a refugee camp. Meet the resourceful investigators-doctors, veterinarians, and research scientists-and discover the truth behind these cases and more.

Capture-recapture methods have been used in biology and ecology for more than 100 years. However, it is only recently that these methods have become popular in the social and medical sciences to estimate the size of elusive populations such as illegal immigrants, illicit drug users, or people with a drinking problem. Capture-Recapture Methods for the Social and Medical Sciences brings together important developments which allow the application of these methods. It has contributions from more than 40 researchers, and is divided into eight parts, including topics such as ratio regression models, capture-recapture meta-analysis, extensions of single and multiple source models, latent variable models and Bayesian approaches. The book is suitable for everyone who is interested in applying capture-recapture methods in the social and medical sciences. Furthermore, it is also of interest to those working with capture-recapture methods in biology and ecology, as there are some important developments covered in the book that also apply to these classical application areas.