Farming Human Pathogens: Ecological Resilience and Evolutionary Process introduces a cutting-edge mathematical formalism based on the asymptotic limit theorems of information theory to describe how punctuated shifts in mesoscale ecosystems can entrain patterns of gene expression and organismal evolution. The authors apply the new formalism toward characterizing a number of infectious diseases that have evolved in response to the world as humans have made it. Many of the human pathogens that are emerging out from underneath epidemiological control are 'farmed' in the metaphorical sense, as the evolution of drug-resistant HIV makes clear, but also quite literally, as demonstrated by avian influenza's emergence from poultry farms in southern China. The most successful pathogens appear able to integrate selection pressures humans have imposed upon them from a variety of socioecological scales. The book also presents a related treatment of Eigen's Paradox and the RNA 'error catastrophe' that bedevils models of the origins of viruses and of biological life itself.

This book presents the state of the art in multilevel analysis, with an emphasis on more advanced topics. These topics are discussed conceptually, analyzed mathematically, and illustrated by empirical examples. Multilevel analysis is the statistical analysis of hierarchically and non-hierarchically nested data. The simplest example is clustered data, such as a sample of students clustered within schools. Multilevel data are especially prevalent in the social and behavioral sciences and in the biomedical sciences. The chapter authors are all leading experts in the field. Given the omnipresence of multilevel data in the social, behavioral, and biomedical sciences, this book is essential for empirical researchers in these fields.

An earlier book by Rodrick Wallace entitled Consciousness: A Mathematical Treatment of the Global Neuronal Workspace Model, introduced a formal information-theoretic approach to individual consciousness implementing approaches developed previously by the cognitive scientist Bernard Baars and the philosopher Fred Dretske.

This book takes a more formal 'groupoid' perspective and generalizes the results of that book to processes of 'distributed cognition' characteristic of large institutions that can entertain several, sometimes many, simultaneous 'global workspaces' which must compete for resources while communicating and cooperating.

Equivalence classes of 'states' produce a network of language-analogs characterizing interacting cognitive modules which entertain multiple workspaces. Equivalence classes of these language-analogs produce dynamical manifolds describing temporal processes carried out by multiple-workspace institutions.

One of the few books on the topic, this updated edition offers alternatives to disease models of addiction by exploring personal pathways to recovery. Focusing on alcohol and drug problems, it provides a literature review of 40 years of studies on self-change with particular emphasis on the current decade and methodological issues (starting with how much or how little treatment constitutes "treatment"). The 24 experts keep the coverage consistently readable, and dozens of brief narratives from individuals who have successfully recovered from an addictive behavior without formal help lend valuable personal perspectives.

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.

All aspects of ophthalmic trauma from the lid to the optic nerve of both mechanical and nonmechanical trauma are covered in this unique book. The focus is on practical issues and incorporates cutting-edge approaches, such as temporary keratosprosthesis, artificial iris diaphragm, and prophylactic retinectomy.

This book explains and answers not simply the when, the what, and the how, but also the why questions. The information is based on epidemiologic and clinical data from evaluation to management.

All chapters are written using the standardized ocular traumatology terminology. The user-friendly format, including many tables, flowcharts and illustrations, allows the reader to quickly find the information they are looking for.

Written by a well-known expert in the field, this concise pocketbook provides clinically useful information that will be of great help to the attending ophthalmologists and emergency room physicians in the decision-making process. The book has practical recommendations for all who see patients with eye injuries."

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.

This is the third edition of this text on logistic regression methods, originally published in 1994, with its second e- tion published in 2002. As in the first two editions, each chapter contains a pres- tation of its topic in "lecture?book" format together with objectives, an outline, key formulae, practice exercises, and a test. The "lecture book" has a sequence of illust- tions, formulae, or summary statements in the left column of each page and a script (i. e. , text) in the right column. This format allows you to read the script in conjunction with the illustrations and formulae that highlight the main points, formulae, or examples being presented. This third edition has expanded the second edition by adding three new chapters and a modified computer appendix. We have also expanded our overview of mod- ing strategy guidelines in Chap. 6 to consider causal d- grams. The three new chapters are as follows: Chapter 8: Additional Modeling Strategy Issues Chapter 9: Assessing Goodness of Fit for Logistic Regression Chapter 10: Assessing Discriminatory Performance of a Binary Logistic Model: ROC Curves In adding these three chapters, we have moved Chaps. 8 through 13 from the second edition to follow the new chapters, so that these previous chapters have been ren- bered as Chaps. 11-16 in this third edition.

Focusing on the most prevalent conditions affecting seniors - including diabetes, cardiovascular disease, osteoporosis, arthritis, and fibromyalgia - Morewitz and Goldstein analyze the impact of chronic disease on aging. Separate chapters are devoted to cognitive changes, psychological problems, and trends in health care utilization, and all chapters are amplified by current research findings.

Because aging is accompanied by a steady decline in resistance to infectious diseases, the diagnosis and treatment of these diseases in the elderly is not only much more complex, but also often quite different from that for younger patients.

In the second edition of Infectious Disease in the Aging: A Clinical Handbook, a panel of well known and highly experienced geriatric physicians and infectious disease experts review the most important common infections affecting the elderly and delineate their well-proven diagnostic, therapeutic, and preventive techniques. Among the illnesses discussed are urinary tract infections, pneumonia, ocular infections, tuberculosis, and fungal and viral infections. In addition, there are detailed discussions of sepsis, infective endocarditis, intraabdominal infections, bacterial meningitis, osteomyelitis and septic arthritis, and prosthetic device infections.

With many Asian countries experiencing increasing economic growth and globalization, infectious diseases that were once contained in certain pockets of the continent now proliferate throughout its geographical area. It is the alarming prospect of unchecked epidemics that makes this book so crucial. The chapters cover the historical description of infectious diseases, analyze the causes of them and even forecast outbreaks, as well as the regional and global impact of these diseases. There is a pressing need for public health professionals worldwide to know and understand the variety of these infections, the methods through which they are transmitted, and the ways to control and prevent them. This comprehensive text offers them just that.

Applied statisticians in many fields must frequently analyze time to event data. While the statistical tools presented in this book are applicable to data from medicine, biology, public health, epidemiology, engineering, economics, and demography, the focus here is on applications of the techniques to biology and medicine. The analysis of survival experiments is complicated by issues of censoring, where an individual's life length is known to occur only in a certain period of time, and by truncation, where individuals enter the study only if they survive a sufficient length of time or individuals are included in the study only if the event has occurred by a given date. The use of counting process methodology has allowed for substantial advances in the statistical theory to account for censoring and truncation in survival experiments. This book makes these complex methods more accessible to applied researchers without an advanced mathematical background. The authors present the essence of these techniques, as well as classical techniques not based on counting processes, and apply them to data. Practical suggestions for implementing the various methods are set off in a series of Practical Notes at the end of each section. Technical details of the derivation of the techniques are sketched in a series of Technical Notes. This book will be useful for investigators who need to analyze censored or truncated life time data, and as a textbook for a graduate course in survival analysis. The prerequisite is a standard course in statistical methodology.

The book is devoted to the study of limit theorems and stability of evolving biologieal systems of "particles" in random environment. Here the term "particle" is used broadly to include moleculas in the infected individuals considered in epidemie models, species in logistie growth models, age classes of population in demographics models, to name a few. The evolution of these biological systems is usually described by difference or differential equations in a given space X of the following type and dxt/dt = g(Xt, y), here, the vector x describes the state of the considered system, 9 specifies how the system's states are evolved in time (discrete or continuous), and the parameter y describes the change ofthe environment. For example, in the discrete-time logistic growth model or the continuous-time logistic growth model dNt/dt = r(y)Nt(l-Nt/K(y)), N or Nt is the population of the species at time n or t, r(y) is the per capita n birth rate, and K(y) is the carrying capacity of the environment, we naturally have X = R, X == Nn(X == Nt), g(x, y) = r(y)x(l-xl K(y)) , xE X. Note that n t for a predator-prey model and for some epidemie models, we will have that X = 2 3 R and X = R , respectively. In th case of logistic growth models, parameters r(y) and K(y) normaIly depend on some random variable y.

The last few years have seen enormous progress in terms of our understanding of the etiology and pathogenesis of cervical cancer (particularly with respect to the role of human papillomaviruses), and this has opened up new avenues for prevention. Additionally, there have been further refinements of existing technologies for cervical cancer control. To read about the state of the art on cervical cancer, health professionals have to locate individual articles and reviews of specific topics. In recognition of this, we propose to produce a book that will bring together in one place reviews of the contribution of descriptive and analytical epidemiological research to our understanding of cervical cancer etiology, as well as research on the application of that knowledge (plus knowledge gained from basic science investigations) to prevention through screening, chemoprevention, and vaccine development. The proposed book will include authoritative reviews by scientists working on the disciplines that are pertinent to the topic of the epidemiology and prevention of cervical cancer.

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.

-The latest "buzz word" in HIV prevention

-Few resources available on "positive prevention"

-Kalichman is a known and recognized name in the field of HIV prevention

It is a truism among biologists that an organism's phenotype is the product of both its genotype and its environment. An organism's genotype contains the total informational potential of the individual, while its environment shapes the expression of the ge- type, influences the rate of mutation and occurrence of modifications, and ultimately determines the likelihood that the genotype (or fractions thereof) will survive into the next generation. In the relationship between host and pathogen, therefore, each forms a part of the environment of the other, mutually influencing the biology of both partners on scales ranging from the life history of individuals to the fate of populations or entire species. Molecular biologists working on problems in pathogenesis generally think of the host organism as the pathogen's environment and perhaps occasionally consider the pathogen as part of the host's environment. However, because "environment" can be defined at many scales, so, too, can phenotypes: if a pathogen, as a species, is c- sidered to exist in a host, as a species, then among its phenotypes is the nature of the pandemic disease it can cause within the host community. The contributors to the proceedings of this NATO Advanced Research Workshop have treated the interplay of environment and genotype in the host-pathogen relationship and its relationship to the problem of emerging infectious disease at both the macroscopic and microscopic/ molecular levels along this continuum of scale (with some human history thrown in at times for good measure).

Chronic pain is a major cause of distress, disability, and work loss, and it is becoming increasingly prevalent through the general move towards an ageing population, which impacts dramatically upon society and health care systems worldwide. Due to improvements in health care, it is becoming more common for patients to continue living with long-term illness or disease (rather than these being terminal). Yet little attention has been paid to chronic pain as a public health problem or to the potential for its prevention, even though it can be studied and assessed using concepts and ideas from classical epidemiology.
This book takes an unusual approach in making a symptom the focus of public health research and policy. Written by leaders in the field of pain, it fills a gap in current literature by presenting chronic pain in terms of cause, impact, consequence and prevention. It presents individual conditions as examples of chronic pain, together with chapters that provide overviews on the assessment of pain and methodological issues behind population assessment.
Chronic Pain Epidemiology - From Aetiology to Public Health provides an invaluable framework and basis for thinking about chronic pain and the potential for its prevention in public health terms. It will appeal to readers from public health, epidemiology and policy perspectives, and those involved in the treatment of pain - such as pain researchers, clinicians and specialists. It will also be an invaluable resource for postgraduate students studying pain management, public health, and epidemiology.

The last half century has witnessed two landmark events in medical history. The 1970s saw euphoria about the defeat of one of humankind's oldest disease scourges with the global eradication of smallpox. To set against this, the 2020s are experiencing the pandemic ravages of new viral diseases, of which COVID-19 is currently the most potent. But it is only the latest of a succession of threats. A Geography of Infection explores the distinctive spatial patterns and processes by which such infectious diseases spread from place to place and can grow from local and regional epidemics into global pandemics. This resource focuses initially on the local scale of doctors' practices and small islands where epidemic outbreaks are slight in the numbers infected and in geographical extent. Such local area studies raise two questions. First, how and where do epidemic diseases emerge and second, why do more diseases appear to be emerging now? To approach such questions implies a shift in spatial gear from painting epidemics with a fine-tipped local brush to an expanded palette on which doctors' practices and small islands are replaced by regional and global populations. Simultaneously, time bands are extended backwards to the origins of civilization and forwards into the twenty-first century. It eventually leads to a consideration of global pandemics - both historical (for example, plague, cholera and influenza) and contemporary (HIV/AIDS and COVID-19) and examines the ways the spread of infection can be prevented. All chapters are extensively illustrated with full-colour diagrams and maps - some of which are in colour for the first time. Bringing together the authors' collective 150 years of experience in research, mapping, and writing on spatial aspects of medical history, this is an invaluable resource for anyone interested in the spread, control, and eradication of epidemic and pandemic diseases.

The story of the rise and fall of smallpox, one of the most savage killers in the history of mankind, and the only disease ever to be successfully exterminated (30 years ago next year) by a public health campaign. Proceeds from the sale of this book will to to support the Edward Jenner Museum in Berkeley, UK (visit www.jennermuseum.com).

All too often, the words "computer validation" strike terror into the hearts of those new to the process and may even cause those familiar with it to tremble. Validating Pharmaceutical Systems: Good Computer Practice in Life Science Manufacturing delineates GCP, GLP, and GMP regulatory requirements and provides guidance from seasoned practitioners on how to fulfill them. John Andrews and his team tackle the perceived complexities surrounding the validation of a wide variety of automated systems. Sprinkled with case studies and real-life examples, the book offers a step-by-step review of topics such as planning, design, auditing, risk management, and specification. The in-depth, by example coverage demystifies the challenges of manufacturing execution systems(MES), laboratory information management systems(LIMS), and network qualification. The first section examines the different levels of automated systems used throughout the drug development, manufacture, and delivery lifecycle, using the GAMP 4 lifecycle approach to their validation. The second section uncovers some real-life applications of GAMP 4 to different areas of the regulations such as GLP, GCP, GMP, and GDP. The book explores some of the latest thinking on computer validation and reflects changes that have occurred in the industry since the early days of validation. The contributors are a deliberate blend of those who have faced the problems of the 1990s and the Y2K controversies and those who have more recently arrived on the scene and made an impact on the perception of validation of automated systems across the field of GxP. They do more than show you how to do the right thing; they show you how to do the right thing in compliance with regulations.

As timely as it is urgent, the well-researched book from veteran science journalist Madeline Drexler delivers a compelling report about today's most ominous infections disease threats. Focusing on a different danger in each chapter-from the looming risk of lethal influenza to in-depth information on the public health perils posed by bioterrorism-Drexler takes readers straight to the front lines, where scientists are racing to catch nearly invisible adversaries superior in speed and guile. Drawing on a powerful combination of fresh research and surprising history, she warns us that the most ceaselessly creative bioterrorist is still Mother Nature, whose microbial operatives are all around us, ready to ounce whenever conditions are right.

Since the dawn of the industrial age, we have unleashed a bewildering number of potentially harmful chemicals. But out of this vast array, how do we identify the actual threats? What does it take to prove that a certain chemical causes cancer? How do we translate academic knowledge of the toxic effects of particular substances into understanding real-world health consequences? The science that answers these questions is toxicology. In The Alchemy of Disease, John Whysner offers an accessible and compelling history of toxicology and its key findings. He details the experiments and discoveries that revealed the causal connections between chemical exposures and diseases. Balancing clear accounts of groundbreaking science with human drama and public-policy relevance, Whysner describes key moments in the development of toxicology and their thorny social and political implications. The book features discussions of toxicological problems past and present, including DDT, cigarettes and other carcinogens, lead poisoning, fossil fuels, chemical warfare, pharmaceuticals-including opioids-and the efficacy of animal testing. Offering valuable insight into the science and politics of crucial public-health concerns, The Alchemy of Disease shows that toxicology's task-pinpointing the chemical cause of an illness-is as compelling as any detective story.

The "Tutorials in Biostatistics" have become a very popular feature of the prestigious Wiley journal, "Statistics in Medicine" (SIM). The introductory style and practical focus make them accessible to a wide audience including medical practitioners with limited statistical knowledge. This book represents the first of two volumes presenting the best tutorials published in SIM, focusing on statistical methods in clinical studies. Topics include the design and analysis of clinical trials, epidemiology, survival analysis, and data monitoring. Each tutorial is focused on a medical problem, has been fully peer-reviewed and edited, and is authored by leading researchers in biostatistics. Many articles include an appendix on the latest developments since publication in the journal and additional references.

This will appeal to statisticians working in medical research, as well as statistically-minded clinicians, biologists, epidemiologists and geneticists. It will also appeal to graduate students of biostatistics.

As evidenced by the anthrax attacks in 2001, the SARS outbreak in 2003, and the H1N1 influenza pandemic in 2009, a pathogen does not recognize geographic or national boundaries, often leading to devastating consequences. Automated biosurveillance systems have emerged as key solutions for mitigating current and future health-related events. Focusing on this promising public health innovation, Biosurveillance: Methods and Case Studies discusses how these systems churn through vast amounts of health-related data to support epidemiologists and public health officials in the early identification, situation awareness, and response management of natural and man-made health-related events. The book follows a natural sequence from theory to application. The initial chapters build a foundation while subsequent chapters present more applied case studies from around the world, including China, the United States, Denmark, and the Asia-Pacific region. The contributors share candid, first-hand insights on lessons learned and unresolved issues that will help chart the future of biosurveillance. As this book illustrates, biosurveillance operates in a complex, multidimensional problem space that incorporates varied data. Capturing the progress of modern-day pioneers who are walking in John Snow's footsteps, this volume shows how contemporary information technology can be applied to the age-old challenge of combating the spread of disease and illness.