Aimed at all types of public health practitioners and theorists, this book is a compilation of methodological and application developments in spatial epidemiological approaches for environmental and public health studies in the Asia Pacific region. It aims to plug a gap in the literature that has seen a shortage of materials documenting the development of health GIS in this crucial part of the world.

A comprehensive overview of the effects of trichloroethylene toxicity caused by real-life exposure levels highlighting how exposure to trichloroethylene may contribute to the etiology of several idiopathic human diseases. Discussion will focus on different kinds of modeling and how they may be used to predict functional consequences and to dissect the contribution of different mechanistic pathways, including potential mechanisms of action for trichloroethylene toxicity in different organ systems. It will explore the role of epigenetic alterations in trichloroethylene toxicity, this provides important mechanistic information and may also provide the basis for intervention therapy. Chapters will also explain how the risks from trichloroethylene exposure may be greater in certain populations based on genetic predisposition, age of exposure and co-exposure to other chemicals With contributions from international experts in the field, Trichloroethylene: Toxicity and Health Risks is an essential resource for researchers and clinicians in toxicology, immunology, medicine and public health as well as industry and government regulatory scientists involved in safety and health protection and epidemiologists, highlighting the need for interdisciplinary cooperation in solving issues of environmental toxicity.

The role that the social and behavioural sciences play in the daily practice of dentistry is now an essential part of all dentistry training, but it can often seem distant from the reality of daily clinical practice. Dentists often ask: what is sociology? Why do I need to know about psychology? Why do I need sociology and psychology to be an effective dentist? How can they help improve my clinical practice? This new textbook answers these important questions and shows how the social and behavioural sciences can inform the practice of dentistry and allied healthcare services in the twenty-first century. It provides a comprehensive, accessible introduction to sociology and psychology for students and members of the dental team with no prior knowledge of the subject, and although the book assumes little or no previous knowledge of psychology or sociology, it also provides enough depth to meet the needs of those with some background in these fields. Throughout, the links between sociology and psychology and everyday practice are emphasized and explained and theoretical concepts are put into the context of everyday clinical work. The authors have extensive experience in teaching and researching the social and behavioural sciences from undergraduate to post-doctoral levels. This book will be an indispensable teaching aid within dental health education, and other allied health and social care disciplines.

*Provides an overview of statistical and analytic methodologies in real-world evidence to generate insights on healthcare, with a special focus on the pharmaceutical industry *Examines timely topics of high relevance to industry such as bioethical considerations, regulatory standards and compliance requirements *Highlights emerging and current trends, and provides guidelines for best practices *Illustrates methods through examples and use-case studies to demonstrate impact *Provides guidance on software choices and digital applications for successful analytics.

From the President of the Research Society on Alcoholism In recent years, increasingly convincing evidence in support of a biobehavioral conceptual model of the etiology of alcoholism has emerged. In this model, the disorder is perceived as arising from the interaction of geneticlbiological vulnerability and psychosocial risk. Drinking, or alcohol-seeking, is a metric trait. Alcoholism, which is a state of abnormally intense alcohol-seeking be havior that, over time, leads to the alcohol dependence syndrome, lies at the extreme, high end of this quantitative measure. Metric traits are influenced by multiple genes; the extent of genetic loading of biological risk for alcoholism would be different in different individuals. Added to this kind of variability is the wide range of options for exposure to the psychosocial risk factors of heavy drinking provided by modern society. Further, environmental prov ocation also changes when life events change. It is not surprising, therefore, from the combination of the kinds of genetic and environmental variability described above that there is a wide array of patterns of expression of the disorder alcoholism, referred to by some as "alcoholisms. " In the search for understanding of underlying mechanisms and rational bases for potential therapy, it is important to focus our attention on the final common pathway of this disorder, alcohol-seeking behavior. This series, ever since its beginning in 1983, has been sensitive to the complexities of the interaction between biological and psychosocial risk factors in alcoholism."

Medical Risk Prediction Models: With Ties to Machine Learning is a hands-on book for clinicians, epidemiologists, and professional statisticians who need to make or evaluate a statistical prediction model based on data. The subject of the book is the patient's individualized probability of a medical event within a given time horizon. Gerds and Kattan describe the mathematical details of making and evaluating a statistical prediction model in a highly pedagogical manner while avoiding mathematical notation. Read this book when you are in doubt about whether a Cox regression model predicts better than a random survival forest. Features: All you need to know to correctly make an online risk calculator from scratch Discrimination, calibration, and predictive performance with censored data and competing risks R-code and illustrative examples Interpretation of prediction performance via benchmarks Comparison and combination of rival modeling strategies via cross-validation Thomas A. Gerds is a professor at the Biostatistics Unit at the University of Copenhagen and is affiliated with the Danish Heart Foundation. He is the author of several R-packages on CRAN and has taught statistics courses to non-statisticians for many years. Michael W. Kattan is a highly cited author and Chair of the Department of Quantitative Health Sciences at Cleveland Clinic. He is a Fellow of the American Statistical Association and has received two awards from the Society for Medical Decision Making: the Eugene L. Saenger Award for Distinguished Service, and the John M. Eisenberg Award for Practical Application of Medical Decision-Making Research.

Immunizationisoneofthegreatadvancesinpublichealth. Figure0. 1showsacamel with a solar-powered refrigerator on his back carrying vaccines across a hot desert to the far reaches of civilization. Many vaccines contain live viruses that need to be kept cold, or the vaccine viruses will die, and the vaccines will lose their ability to produce an immune response. Thus a continuous chain of refrigeration, the cold chain, from the origin to delivery of some vaccines needs to be maintained. The inspiration of the camel image is that it represents the dedication of the world to bring vaccines to everyone. The ?rst major success, and the origin of the word vaccination (vacca for cow), was Jenner's introducing cowpox-based vaccine against smallpox in the late 18th century. After nearly a century hiatus, at the end of the 19th century, inoculations against cholera, typhoid, plague (caused by bacteria) and rabies (caused by a virus) were developed. By the early 20th century, statisticians of the stature of Karl Pe- son, Major Greenwood, and Udny Yule were heartily involved in discussions of evaluating these vaccines in the ?eld. In the 1920s, new vaccines included pert- sis, diptheria, tetanus, and bacille Calmette-Guerin ' against tuberculosis. The 1930s saw development of yellow fever, in?uenza, and rickettsia vaccines. After World War II, the advent of cell cultures in which viruses could grow enabled production of polio vaccine and vaccines against measles, mumps, rubella, varicella, and a- novirus, among others (Plotkin et al 2008).

Over the past fifty years, the case-control method, and to a lesser extent its case-based variants, have become the most important tools for the investigator of health problems. The case control method is the study of persons with the disease and a suitable control group of persons who do not have the disease. The book helps readers address a number of general and specific questions dealing with the case-control and other case-based methods, including questions of how to design and implement a case-control study that minimizes biases, how to analyze the data to appropriately deal with confounding variables and help identify reactions, and how to interpret data and present the results from a case-control study.

In a series of case studies of sexually transmitted disease and HIV/AIDS from around Africa, contributors examine the social, cultural, and political-economic bases of risk, transmission, and response to epidemic disease. This book brings together major contributions to the historical study of epidemic disease in developing countries and considers how particular constellations of cultural, social, political, and economic factors in different countries have affected the historical patterns of disease and collective (official and community) response to them. This book is a companion volume to "Sex, Disease, and Society: A Comparative History of Sexually Transmitted Diseases and HIV/AIDS in Asia and the Pacific" (Greenwood, 1997).

From this endeavor to provide insight into the conjunctions and disjunctions between the histories of STDs and the AIDS pandemic in Sub-Saharan Africa certain common issues have emerged. These include medical ambiguity and epidemiologic diversity; cultural change; racism; gender, labor migration, and economic instability; and the practice of biomedicine and epidemiology in African contexts. All of these factors are embedded in the colonial legacy and post-colonial political economic conditions across the continent.

Covid-19 has hit the world unprepared, as the deadliest pandemic of the century. Governments and authorities, as leaders and decision makers fighting against the virus, enormously tap on the power of AI and its data analytics models for urgent decision supports at the greatest efforts, ever seen from human history. This book showcases a collection of important data analytics models that were used during the epidemic, and discusses and compares their efficacy and limitations. Readers who from both healthcare industries and academia can gain unique insights on how data analytics models were designed and applied on epidemic data. Taking Covid-19 as a case study, readers especially those who are working in similar fields, would be better prepared in case a new wave of virus epidemic may arise again in the near future.

This book provides detailed and updated knowledge about medically important 'Big Four' venomous snakes of India (Indian spectacled cobra, Indian common krait, Indian Russell's viper, and Indian saw-scaled viper). This book essentially covers the snakebite problem in the world with particular reference to Asia and India. It discusses the evolution and systematics of venomous snakes, emphasizing 'Big Four' venomous snakes of India; the evolution and composition of venoms determined by traditional biochemical and modern proteomic analyses. It also describes the pharmacological properties of enzymatic and non-enzymatic toxins of 'Big Four' venomous snakes of India. Different chapters discuss exciting topics such as species-specific and geographical differences in venom composition and its impact on pathophysiology and clinical manifestations of snakebite envenomation in India, biomedical application of Indian snake venom toxins; production and quality assessment of commercial antivenom, prevention, and treatment of snakebite in India, adverse effects of antivenom including strategies to combat antivenom reactions inpatient. This book caters to toxinologists, pharmacologists, zoologists, antivenom manufacturers, biochemists, clinicians, evolutionary biologists, herpetologists, and informed non-specialists interested to know about the Indian snake venoms.

This book comprehensively reviews various vector-borne diseases and their control methods. It discusses morphology, life history, and pathogenicity of protozoan and helminth parasites. Further, it analyzes host-parasite interactions and their adaptation within the host system for understanding parasitic infections. The book discusses the complex life cycle, biochemical adaptations, and molecular biology of the parasites. It investigates the immunological response to different infectious agents and explores new targets for combined therapeutic approaches. It also summarizes the evolution of parasitism and the ecology of parasites of the different phylum. Lastly, it provides information on vector biology emphasizing the role of basic vector research in developing future disease control methods and improving upon the existing approaches.

This innovative textbook brings together modern concepts in mathematical epidemiology, computational modeling, physics-based simulation, data science, and machine learning to understand one of the most significant problems of our current time, the outbreak dynamics and outbreak control of COVID-19. It teaches the relevant tools to model and simulate nonlinear dynamic systems in view of a global pandemic that is acutely relevant to human health. If you are a student, educator, basic scientist, or medical researcher in the natural or social sciences, or someone passionate about big data and human health: This book is for you! It serves as a textbook for undergraduates and graduate students, and a monograph for researchers and scientists. It can be used in the mathematical life sciences suitable for courses in applied mathematics, biomedical engineering, biostatistics, computer science, data science, epidemiology, health sciences, machine learning, mathematical biology, numerical methods, and probabilistic programming. This book is a personal reflection on the role of data-driven modeling during the COVID-19 pandemic, motivated by the curiosity to understand it.

In this intimate history of the extraordinary Black Plague pandemic that swept through the British Isles in 1665, Evelyn Lord focuses on the plague's effects on smaller towns, where every death was a singular blow affecting the entire community. Lord's fascinating reconstruction of life during plague times presents the personal experiences of a wide range of individuals, from historical notables Samuel Pepys and Isaac Newton to common folk who tilled the land and ran the shops. She brings this dark era to vivid life through stories of loss and survival from those who grieved, those who fled, and those who hid to await their fate.

This book addresses the COVID-19 pandemic from a quantitative perspective based on mathematical models and methods largely used in nonlinear physics. It aims to study COVID-19 epidemics in countries and SARS-CoV-2 infections in individuals from the nonlinear physics perspective and to model explicitly COVID-19 data observed in countries and virus load data observed in COVID-19 patients. The first part of this book provides a short technical introduction into amplitude spaces given by eigenvalues, eigenvectors, and amplitudes.In the second part of the book, mathematical models of epidemiology are introduced such as the SIR and SEIR models and applied to describe COVID-19 epidemics in various countries around the world. In the third part of the book, virus dynamics models are considered and applied to infections in COVID-19 patients. This book is written for researchers, modellers, and graduate students in physics and medicine, epidemiology and virology, biology, applied mathematics, and computer sciences. This book identifies the relevant mechanisms behind past COVID-19 outbreaks and in doing so can help efforts to stop future COVID-19 outbreaks and other epidemic outbreaks. Likewise, this book points out the physics underlying SARS-CoV-2 infections in patients and in doing so supports a physics perspective to address human immune reactions to SARS-CoV-2 infections and similar virus infections.

Mathematical and Statistical Estimation Approaches in Epidemiology compiles t- oretical and practical contributions of experts in the analysis of infectious disease epidemics in a single volume. Recent collections have focused in the analyses and simulation of deterministic and stochastic models whose aim is to identify and rank epidemiological and social mechanisms responsible for disease transmission. The contributions in this volume focus on the connections between models and disease data with emphasis on the application of mathematical and statistical approaches that quantify model and data uncertainty. The book is aimed at public health experts, applied mathematicians and sci- tists in the life and social sciences, particularly graduate or advanced undergraduate students, who are interested not only in building and connecting models to data but also in applying and developing methods that quantify uncertainty in the context of infectious diseases. Chowell and Brauer open this volume with an overview of the classical disease transmission models of Kermack-McKendrick including extensions that account for increased levels of epidemiological heterogeneity. Their theoretical tour is followed by the introduction of a simple methodology for the estimation of, the basic reproduction number,R . The use of this methodology 0 is illustrated, using regional data for 1918-1919 and 1968 in uenza pandemics.

Simulating for a crisis is far more than creating a simulation of a crisis situation. In order for a simulation to be useful during a crisis, it should be created within the space of a few days to allow decision makers to use it as quickly as possible. Furthermore, during a crisis the aim is not to optimize just one factor, but to balance various, interdependent aspects of life. In the COVID-19 crisis, decisions had to be made concerning e.g. whether to close schools and restaurants, and the (economic) consequences of a 3 or 4-week lock-down had to be considered. As such, rather than one simulation focusing on a very limited aspect, a framework allowing the simulation of several different scenarios focusing on different aspects of the crisis was required. Moreover, the results of the simulations needed to be easily understandable and explainable: if a simulation indicates that closing schools has no effect, this can only be used if the decision makers can explain why this is the case. This book describes how a simulation framework was created for the COVID-19 crisis, and demonstrates how it was used to simulate a wide range of scenarios that were relevant for decision makers at the time. It also discusses the usefulness of the approach, and explains the decisions that had to be made along the way as well as the trade-offs. Lastly, the book examines the lessons learned and the directions for the further development of social simulation frameworks to make them better suited to crisis situations, and to foster a more resilient society.

Now in its second edition, this book provides a state of the art overview on basic concepts of epigenetic epidemiology and a comprehensive review of the rapidly evolving field of human epigenetics. Epigenetics plays an important role in shaping who we are and contributes to our prospects of health and disease. Unlike our genetic inheritance, our epigenome is malleable throughout the lifecourse and is shaped by our environmental experiences. Population-based epidemiologic studies increasingly incorporate epigenetic components. These so called epigenome-wide association studies (EWAS) contribute substantially to our understanding of the relevance of epigenetic marks, such as DNA methylation, histone modification, and non-coding RNAs for disease causation. Written by leading experts in the field, the book opens with a comprehensive introduction of the principles of epigenetic epidemiology and discusses challenges in study design, analysis, and interpretation. It summarizes the latest advances in epigenetic laboratory techniques, the influence of age and environmental factors on shaping the epigenome, the epigenetic clock, and the role of epigenetics in the developmental origins hypothesis. The final part focuses on epigenetic epidemiology of various health conditions such as imprinting disorders, cancer, infectious diseases, inflammation and rheumatoid arthritis, asthma, metabolic disorder and vascular disease, as well as neurodevelopmental and psychiatric disorders. Given its scope, Epigenetic Epidemiology is an indispensable resource for researchers working in the field of human epigenetics.

This textbook and guide focuses on methodologies for bias analysis in epidemiology and public health, not only providing updates to the first edition but also further developing methods and adding new advanced methods. As computational power available to analysts has improved and epidemiologic problems have become more advanced, missing data, Bayes, and empirical methods have become more commonly used. This new edition features updated examples throughout and adds coverage addressing: Measurement error pertaining to continuous and polytomous variables Methods surrounding person-time (rate) data Bias analysis using missing data, empirical (likelihood), and Bayes methods A unique feature of this revision is its section on best practices for implementing, presenting, and interpreting bias analyses. Pedagogically, the text guides students and professionals through the planning stages of bias analysis, including the design of validation studies and the collection of validity data from other sources. Three chapters present methods for corrections to address selection bias, uncontrolled confounding, and measurement errors, and subsequent sections extend these methods to probabilistic bias analysis, missing data methods, likelihood-based approaches, Bayesian methods, and best practices.

Drug development is an iterative process. The recent publications of regulatory guidelines further entail a lifecycle approach. Blending data from disparate sources, the Bayesian approach provides a flexible framework for drug development. Despite its advantages, the uptake of Bayesian methodologies is lagging behind in the field of pharmaceutical development. Written specifically for pharmaceutical practitioners, Bayesian Analysis with R for Drug Development: Concepts, Algorithms, and Case Studies, describes a wide range of Bayesian applications to problems throughout pre-clinical, clinical, and Chemistry, Manufacturing, and Control (CMC) development. Authored by two seasoned statisticians in the pharmaceutical industry, the book provides detailed Bayesian solutions to a broad array of pharmaceutical problems. Features Provides a single source of information on Bayesian statistics for drug development Covers a wide spectrum of pre-clinical, clinical, and CMC topics Demonstrates proper Bayesian applications using real-life examples Includes easy-to-follow R code with Bayesian Markov Chain Monte Carlo performed in both JAGS and Stan Bayesian software platforms Offers sufficient background for each problem and detailed description of solutions suitable for practitioners with limited Bayesian knowledge Harry Yang, Ph.D., is Senior Director and Head of Statistical Sciences at AstraZeneca. He has 24 years of experience across all aspects of drug research and development and extensive global regulatory experiences. He has published 6 statistical books, 15 book chapters, and over 90 peer-reviewed papers on diverse scientific and statistical subjects, including 15 joint statistical works with Dr. Novick. He is a frequent invited speaker at national and international conferences. He also developed statistical courses and conducted training at the FDA and USP as well as Peking University. Steven Novick, Ph.D., is Director of Statistical Sciences at AstraZeneca. He has extensively contributed statistical methods to the biopharmaceutical literature. Novick is a skilled Bayesian computer programmer and is frequently invited to speak at conferences, having developed and taught courses in several areas, including drug-combination analysis and Bayesian methods in clinical areas. Novick served on IPAC-RS and has chaired several national statistical conferences.

Handbook on the Toxicology of Metals, Fourth Edition bridges the gap between established knowledgebase and new advances in metal toxicology to provide one essential reference for all those involved in the field. This book provides comprehensive coverage of basic toxicological data, emphasizing toxic effects primarily in humans, but also those of animals and biological systems in vitro. The fourth edition also contains several new chapters on important topics such as nanotoxicology, metals in prosthetics and dental implants, gene-environment interaction, neurotoxicology, metals in food, renal, cardiovascular, and diabetes effects of metal exposures and more. Volume I covers "General Considerations" and Volume II is devoted to "Specific Metals." A multidisciplinary resource with contributions from internationally-recognized experts, the fourth edition of the Handbook on the Toxicology of Metals is a prominent and indispensable reference for toxicologists, physicians, pharmacologists, engineers, and all those involved in the toxicity of metals.

Since the early 2000s, there has been increasing interest within the pharmaceutical industry in the application of Bayesian methods at various stages of the research, development, manufacturing, and health economic evaluation of new health care interventions. In 2010, the first Applied Bayesian Biostatistics conference was held, with the primary objective to stimulate the practical implementation of Bayesian statistics, and to promote the added-value for accelerating the discovery and the delivery of new cures to patients. This book is a synthesis of the conferences and debates, providing an overview of Bayesian methods applied to nearly all stages of research and development, from early discovery to portfolio management. It highlights the value associated with sharing a vision with the regulatory authorities, academia, and pharmaceutical industry, with a view to setting up a common strategy for the appropriate use of Bayesian statistics for the benefit of patients. The book covers: Theory, methods, applications, and computing Bayesian biostatistics for clinical innovative designs Adding value with Real World Evidence Opportunities for rare, orphan diseases, and pediatric development Applied Bayesian biostatistics in manufacturing Decision making and Portfolio management Regulatory perspective and public health policies Statisticians and data scientists involved in the research, development, and approval of new cures will be inspired by the possible applications of Bayesian methods covered in the book. The methods, applications, and computational guidance will enable the reader to apply Bayesian methods in their own pharmaceutical research.