Ophthalmic Epidemiology: Current Concepts to Digital Strategies provides a comprehensive guide to graduate students, ophthalmologists, and researchers in ophthalmic epidemiology. It covers recently developed new methodologies, technologies and resources in ocular epidemiological research, such as telemedicine, disease registries, EMR, bio-banks and omics. This book also summarizes recent epidemiological findings and provides up-to-date data on ocular diseases. Furthermore, it introduces and discusses the uses of epidemiology in the evaluation of health services and population screening programs and reviews the application of epidemiology in intervention trials in the communities. Key Features Comprehensive guide to the epidemiology of common eye diseases. Provides updates on the prevalence and risk factors of eye diseases. Outlines how epidemiological techniques can be utilized to evaluate ophthalmic health services and programs.

The National Centre for Infectious Diseases (NCID) is the result of many years in the planning, and it finally officially opened its doors in September 2019, just months before the entire world was tested by the COVID-19 pandemic. This book is the work of many people who represent an even larger pool of people from NCID, Singapore and the rest of the world in trying to understand and contain the SARS- CoV-2 virus. There are chapters on science, the public health response both locally and globally, as well as personal reflections from NCID and Tan Tock Seng Hospital staff and staff from other public healthcare institutions who were deployed to NCID which bring home the human impact of the pandemic. We are very grateful to all the authors for taking the time to put together their thoughtful chapters as well as the senior academics and public health leaders who have provided us with generous comments on the manuscript. We hope that the readers of the book will gain a better insight into the response to the virus from so many different perspectives. Although the pandemic has evolved far beyond the pages of this book globally, the lessons learned from the early days are still relevant. We hope that the chapters will be helpful as we review our experience of this pandemic and face the next emerging infectious disease in the years to come.This book provides a comprehensive look at many different aspects of response in Singapore to the pandemic in the crucial first several months, including clinical, laboratory, epidemiology, research, community engagement and the unprecedented challenge of outbreak involving migrant workers in dormitory settings. On a personal note, it has first-hand accounts of staff at the NCID who were at the forefront of battling COVID-19 in Singapore. It also gives a global perspective of the pandemic, together with insights into the unique Singapore experience of managing the pandemic. The Singapore response to the pandemic has been something which the global community has been very interested in and this book is the first to comprehensively describe that response from a number of different angles which will be useful to scientists, clinicians, public health professionals and policy makers.

- The first practical introduction to second-order and growth mixture models using Mplus 8.4 -Introduces simple and complex models through incremental steps with increasing complexity -Each model is presented with figures with associated syntax that highlight what the statistics mean, Mplus applications, and an interpretation of results, to maximize understanding. - Second-order and growth mixture modeling is increasingly being used in various disciplines to analyze changes in individual attributes such as personal behaviors and relationships over time

Towards a Digital Health Ecology : NHS Digital Adoption through the COVID-19 Looking Glass is about technology adoption in the UK's National Health Service (NHS) as told from the inflection point of a disaster. In 2020 the world lived through a disaster of epic proportions, devastating humanity around the globe. It took a microscopic virus to wreak havoc on our healthcare system and force the adoption of technology in a way that had never been seen before. This book tells the story of digital technology take-up in the NHS through the lens of that disaster. This book documents use of technology in the NHS through the lens of the first pandemic shock. Our healthcare system, paid for by general taxation and free at the point of demand, was conceived and developed in a firmly analogue world. Created in 1948, the NHS predates the invention of the World Wide Web by some forty years. This is not a book simply about technology, it is a study of the painful process of reengineering a mammoth and byzantine system that was built for a different era. The digital health sector is a microcosm of the wider healthcare system, through which grand themes of social inequality, public trust, private versus commercial interests, values and beliefs are played out. The sector is a clash of competing discourses: the civic and doing good for society; the market and wealth creation; the industrial creating more efficient and effective systems; the project expressed as innovation and experimentation; lastly the notion of vitality and leading a happier, healthy life. Each of these discourses exists in a state of flux and tension with the other. This book is offered as a critique of the role of digital technologies within healthcare. It is an examination of competing interests, approaches, and ideologies. It is a story of system complexity told through analysis and personal stories.

This book presents futuristic trends in computational intelligence including algorithms as applicable to different application domains in health informatics covering bio-medical, bioinformatics, and biological sciences. Latest evolutionary approaches to solve optimization problems under biomedical engineering field are discussed. It provides conceptual framework with a focus on application of computational intelligence techniques in the domain of biomedical engineering and health informatics including real-time issues.

This book provides a groundbreaking introduction to the likelihood inference for correlated survival data via the hierarchical (or h-) likelihood in order to obtain the (marginal) likelihood and to address the computational difficulties in inferences and extensions. The approach presented in the book overcomes shortcomings in the traditional likelihood-based methods for clustered survival data such as intractable integration. The text includes technical materials such as derivations and proofs in each chapter, as well as recently developed software programs in R ("frailtyHL"), while the real-world data examples together with an R package, "frailtyHL" in CRAN, provide readers with useful hands-on tools. Reviewing new developments since the introduction of the h-likelihood to survival analysis (methods for interval estimation of the individual frailty and for variable selection of the fixed effects in the general class of frailty models) and guiding future directions, the book is of interest to researchers in medical and genetics fields, graduate students, and PhD (bio) statisticians.

Coherent treatment of a variety of approaches to multiple comparisons Broad coverage of topics, with contributions by internationally leading experts Detailed treatment of applications in medicine and life sciences Suitable for researchers, lecturers / students, and practitioners

Measurement error arises ubiquitously in applications and has been of long-standing concern in a variety of fields, including medical research, epidemiological studies, economics, environmental studies, and survey research. While several research monographs are available to summarize methods and strategies of handling different measurement error problems, research in this area continues to attract extensive attention. The Handbook of Measurement Error Models provides overviews of various topics on measurement error problems. It collects carefully edited chapters concerning issues of measurement error and evolving statistical methods, with a good balance of methodology and applications. It is prepared for readers who wish to start research and gain insights into challenges, methods, and applications related to error-prone data. It also serves as a reference text on statistical methods and applications pertinent to measurement error models, for researchers and data analysts alike. Features: Provides an account of past development and modern advancement concerning measurement error problems Highlights the challenges induced by error-contaminated data Introduces off-the-shelf methods for mitigating deleterious impacts of measurement error Describes state-of-the-art strategies for conducting in-depth research

The cost for bringing new medicine from discovery to market has nearly doubled in the last decade and has now reached $2.6 billion. There is an urgent need to make drug development less time-consuming and less costly. Innovative trial designs/ analyses such as the Bayesian approach are essential to meet this need. This book will be the first to provide comprehensive coverage of Bayesian applications across the span of drug development, from discovery, to clinical trial, to manufacturing with practical examples. This book will have a wide appeal to statisticians, scientists, and physicians working in drug development who are motivated to accelerate and streamline the drug development process, as well as students who aspire to work in this field. The advantages of this book are: Provides motivating, worked, practical case examples with easy to grasp models, technical details, and computational codes to run the analyses Balances practical examples with best practices on trial simulation and reporting, as well as regulatory perspectives Chapters written by authors who are individual contributors in their respective topics Dr. Mani Lakshminarayanan is a researcher and statistical consultant with more than 30 years of experience in the pharmaceutical industry. He has published over 50 articles, technical reports, and book chapters besides serving as a referee for several journals. He has a PhD in Statistics from Southern Methodist University, Dallas, Texas and is a Fellow of the American Statistical Association. Dr. Fanni Natanegara has over 15 years of pharmaceutical experience and is currently Principal Research Scientist and Group Leader for the Early Phase Neuroscience Statistics team at Eli Lilly and Company. She played a key role in the Advanced Analytics team to provide Bayesian education and statistical consultation at Eli Lilly. Dr. Natanegara is the chair of the cross industry-regulatory-academic DIA BSWG to ensure that Bayesian methods are appropriately utilized for design and analysis throughout the drug-development process.

How to conduct clinical trials in an ethical and scientifically responsible manner
This book presents a methodology for clinical trials that produces improved health outcomes for patients while obtaining sound and unambiguous scientific data. It centers around a real-world test case--involving a treatment for hypertension after open heart surgery--and explains how to use Bayesian methods to accommodate both ethical and scientific imperatives.
The book grew out of the direct involvement in the project by a diverse group of experts in medicine, statistics, philosophy, and the law. Not only do they contribute essays on the scientific, technological, legal, and ethical aspects of clinical trials, but they also critique and debate each other's opinions, creating an interesting, personalized text.
Bayesian Methods and Ethics in a Clinical Trial Design
* Answers commonly raised questions about Bayesian methods
* Describes the advantages and disadvantages of this method compared with other methods
* Applies current ethical theory to a particular class of design for clinical trials
* Discusses issues of informed consent and how to serve a patient's best interest while still obtaining uncontaminated scientific data
* Shows how to use Bayesian probabilistic methods to create computer models from elicited prior opinions of medical experts on the best treatment for a type of patient
* Contains several chapters on the process, results, and computational aspects of the test case in question
* Explores American law and the legal ramifications of using human subjects

For statisticians and biostatisticians, and for anyone involved with medicine and public health, this book provides both a practical guide and a unique perspective on the connection between technological developments, human factors, and some of the larger ethical issues of our times.

The book offers comprehensive coverage of the most essential topics, including: A general overview of pandemics and their outbreak behavior. A detailed overview of CI techniques. Intelligent modeling, prediction and diagnostic measures for pandemics. Prognostic models. Post-pandemic socio-economic structure.

Healthcare is important to everyone, yet large variations in its quality have been well documented both between and within many countries. With demand and expenditure rising, it's more crucial than ever to know how well the healthcare system and all its components - from staff member to regional network - are performing. This requires data, which inevitably differ in form and quality. It also requires statistical methods, the output of which needs to be presented so that it can be understood by whoever needs it to make decisions. Statistical Methods for Healthcare Performance Monitoring covers measuring quality, types of data, risk adjustment, defining good and bad performance, statistical monitoring, presenting the results to different audiences and evaluating the monitoring system itself. Using examples from around the world, it brings all the issues and perspectives together in a largely non-technical way for clinicians, managers and methodologists. Statistical Methods for Healthcare Performance Monitoring is aimed at statisticians and researchers who need to know how to measure and compare performance, health service regulators, health service managers with responsibilities for monitoring performance, and quality improvement scientists, including those involved in clinical audits.

Insect-transmitted rickettsiales diseases are significant sources of morbidity and mortality all over the world. Their incidence has been increasing in recent years in large part due to climate change and the movement of animals carrying the insect vectors. Currently there are no effective vaccines against diseases caused by members of the order Rickettsiales. Rickettsiales diseases are often misdiagnosed; this book is intended to serve as a tool for their understanding and diagnosis. Rickettsiales covers the seven main genera: Anaplasma, Ehrlichia, Midichloria, Neorickettsia, Orientia, Rickettsia and Wolbachia. Discussion of each genus includes immunology and molecular biology of host-pathogen interactions, epidemiology and diagnosis, and vaccination strategies and therapies.

This title includes a number of Open Access chapters. The book provides a comprehensive perspective on the subject of obesity epidemiology, pathophysiology, and management of obesity. The chapters provide a better understanding of obesity and obesity-related diseases and offer an integrative framework for individualized dietary and exercise programs, behavior modification, pharmaceutical approaches, surgery, and population interventions to reduce the growing epidemic of obesity.

The Multiplayer Classroom: Game Plans is a companion to The Multiplayer Classroom: Designing Coursework as a Game, now in its second edition from CRC Press. This book covers four multiplayer classroom projects played in the real world in real time to teach and entertain. They were funded by grants or institutions, collaborations between Lee Sheldon, as writer/designer, and subject matter experts in various fields. They are written to be accessible to anyone--designer, educator, or layperson--interested in game-based learning. The subjects are increasingly relevant in this day and age: physical fitness, Mandarin, cybersecurity, and especially an online class exploring culture and identity on the internet that is unlike any online class you have ever seen. Read the annotated, often-suspenseful stories of how each game, with its unique challenges, thrills, and spills, was built. Lee Sheldon began his writing career in television as a writer-producer, eventually writing more than 200 shows ranging from Charlie's Angels (writer) to Edge of Night (head writer) to Star Trek: The Next Generation (writer-producer). Having written and designed more than forty commercial and applied video games, Lee spearheaded the first full writing for games concentration in North America at Rensselaer Polytechnic Institute and the second writing concentration at Worcester Polytechnic Institute. He is a regular lecturer and consultant on game design and writing in the United States and abroad. His most recent commercial game, the award-winning The Lion's Song, is currently on Steam. For the past two years he consulted on an "escape room in a box," funded by NASA, that gives visitors to hundreds of science museums and planetariums the opportunity to play colonizers on the moon. He is currently writing his second mystery novel.

"This is truly an outstanding book. [It] brings together all of the latest research in clinical trials methodology and how it can be applied to drug development.... Chang et al provide applications to industry-supported trials. This will allow statisticians in the industry community to take these methods seriously." Jay Herson, Johns Hopkins University The pharmaceutical industry's approach to drug discovery and development has rapidly transformed in the last decade from the more traditional Research and Development (R & D) approach to a more innovative approach in which strategies are employed to compress and optimize the clinical development plan and associated timelines. However, these strategies are generally being considered on an individual trial basis and not as part of a fully integrated overall development program. Such optimization at the trial level is somewhat near-sighted and does not ensure cost, time, or development efficiency of the overall program. This book seeks to address this imbalance by establishing a statistical framework for overall/global clinical development optimization and providing tactics and techniques to support such optimization, including clinical trial simulations. Provides a statistical framework for achieve global optimization in each phase of the drug development process. Describes specific techniques to support optimization including adaptive designs, precision medicine, survival-endpoints, dose finding and multiple testing. Gives practical approaches to handling missing data in clinical trials using SAS. Looks at key controversial issues from both a clinical and statistical perspective. Presents a generous number of case studies from multiple therapeutic areas that help motivate and illustrate the statistical methods introduced in the book. Puts great emphasis on software implementation of the statistical methods with multiple examples of software code (both SAS and R). It is important for statisticians to possess a deep knowledge of the drug development process beyond statistical considerations. For these reasons, this book incorporates both statistical and "clinical/medical" perspectives.

The world continues to lose more than a million lives each year to the HIV epidemic, and nearly two million individuals were infected with HIV in 2017 alone. The new Sustainable Development Goals, adopted by countries of the United Nations in September 2015, include a commitment to end the AIDS epidemic by 2030. Considerable emphasis on prevention of new infections and treatment of those living with HIV will be needed to make this goal achievable. With nearly 37 million people now living with HIV, it is a communicable disease that behaves like a noncommunicable disease. Nutritional management is integral to comprehensive HIV care and treatment. Improved nutritional status and weight gain can increase recovery and strength of individuals living with HIV/AIDS, improve dietary diversity and caloric intake, and improve quality of life. This book highlights evidence-based research linking nutrition and HIV and identifies research gaps to inform the development of guidelines and policies for the United Nations' Sustainable Development Goals. A comprehensive approach that includes nutritional interventions is likely to maximize the benefit of antiretroviral therapy in preventing HIV disease progression and other adverse outcomes in HIV-infected men and women. Modification of nutritional status has been shown to enhance the quality of life of those suffering HIV/AIDS, both physically in terms of improved body mass index and immunological markers, and psychologically, by improving symptoms of depression. While the primary focus for those infected should remain on antiretroviral treatment and increasing its availability and coverage, improvement of nutritional status plays a complementary role in the management of HIV infection.

Self-Controlled Case Series Studies: A Modelling Guide with R provides the first comprehensive account of the self-controlled case series (SCCS) method, a statistical technique for investigating associations between outcome events and time-varying exposures. The method only requires information from individuals who have experienced the event of interest, and automatically controls for multiplicative time-invariant confounders, even when these are unmeasured or unknown. It is increasingly being used in epidemiology, most frequently to study the safety of vaccines and pharmaceutical drugs. Key features of the book include: A thorough yet accessible description of the SCCS method, with mathematical details provided in separate starred sections. Comprehensive discussion of assumptions and how they may be verified. A detailed account of different SCCS models, extensions of the SCCS method, and the design of SCCS studies. Extensive practical illustrations and worked examples from epidemiology. Full computer code from the associated R package SCCS, which includes all the data sets used in the book. The book is aimed at a broad range of readers, including epidemiologists and medical statisticians who wish to use the SCCS method, and also researchers with an interest in statistical methodology. The three authors have been closely involved with the inception, development, popularisation and programming of the SCCS method.

Mendelian Randomization: Methods For Causal Inference Using Genetic Variants provides thorough coverage of the methods and practical elements of Mendelian randomization analysis. It brings together diverse aspects of Mendelian randomization from the fields of epidemiology, statistics, genetics, and bioinformatics. Through multiple examples, the first part of the book introduces the reader to the concept of Mendelian randomization, showing how to perform simple Mendelian randomization investigations and interpret the results. The second part of the book addresses specific methodological issues relevant to the practice of Mendelian randomization, including robust methods, weak instruments, multivariable methods, and power calculations. The authors present the theoretical aspects of these issues in an easy-to-understand way by using non-technical language. The last part of the book examines the potential for Mendelian randomization in the future, exploring both methodological and applied developments. Features Offers first-hand, in-depth guidance on Mendelian randomization from leaders in the field Makes the diverse aspects of Mendelian randomization understandable to newcomers Illustrates technical details using data from applied analyses Discusses possible future directions for research involving Mendelian randomization Software code is provided in the relevant chapters and is also available at the supplementary website This book gives epidemiologists, statisticians, geneticists, and bioinformaticians the foundation to understand how to use genetic variants as instrumental variables in observational data. New in Second Edition: The second edition of the book has been substantially re-written to reduce the amount of technical content, and emphasize practical consequences of theoretical issues. Extensive material on the use of two-sample Mendelian randomization and publicly-available summarized data has been added. The book now includes several real-world examples that show how Mendelian randomization can be used to address questions of disease aetiology, target validation, and drug development

Signal Detection for Medical Scientists: Likelihood Ratio Based Test-Based Methodology presents the data mining techniques with focus on likelihood ratio test (LRT) based methods for signal detection. It emphasizes computational aspect of LRT methodology and is pertinent for first-time researchers and graduate students venturing into this interesting field. The book is written as a reference book for professionals in pharmaceutical industry, manufactures of medical devices, and regulatory agencies. The book deals with the signal detection in drug/device evaluation, which is important in the post-market evaluation of medical products, and in the pre-market signal detection during clinical trials for monitoring procedures. It should also appeal to academic researchers, and faculty members in mathematics, statistics, biostatistics, data science, pharmacology, engineering, epidemiology, and public health. Therefore, this book is well suited for both research and teaching. Key Features: Includes a balanced discussion of art of data structure, issues in signal detection, statistical methods and analytics, and implementation of the methods. Provides a comprehensive summary of the LRT methods for signal detection including the basic theory and extensions for varying datasets that may be large post-market data or pre-market clinical trial data. Contains details of scientific background, statistical methods, and associated algorithms that a reader can quickly master the materials and apply methods in the book on one's own problems

This fascinating book gives readers an appreciation of how biomedical research should work and how the reality is all too often seriously flawed. Explaining the logical basis of the different research approaches used by biomedical research scientists and their relative merits, it will help readers to make more realistic appraisal of media reports linking aspects of lifestyle, environment or diet to health outcomes and thus judge whether such claims are a real effect worthy of consideration for behavior change or deserving of further research resources. Key features: increases awareness of research fraud and some of the characteristics of fraudulent science and scientific fraudsters shows that whilst outright fraud may be uncommon, fudging of results to help achieve statistical significance may be more prevalent incorporates real-life case studies highlighting some of the infamous cases of research fraud and major scientific mistakes and the impact that they have had provides a convenient overview of the research process in the biomedical sciences, with a focus on research strategy rather than individual methods find supplemental detail on the author's blog https://drgeoffnutrition.wordpress.com/about/ By raising awareness of the possibility that research data may have been dishonestly generated and outlining some of the signs and symptoms that might suggest data fabrication, Error and Fraud: The Dark Side of Biomedical Research will help students and researchers to identify the strengths and limitations of different research approaches and allow them to make a realistic evaluations of their own and others' research findings.

The U.S. healthcare system is in "complete chaos-disarray." Medical costs have increased significantly over the past 6 years with 70% increase for deductibles and 24% or more for health insurance premiums. All the while, workers earnings have either not increased or if they did, the pay raises were for less than the increase in the cost of medical care. The situation is unsustainable and the public wants the system fixed. This book offers ways of fixing the problems in healthcare. HEALTHCARE's OUT SICK - PREDICTING A CURE - Solutions that WORK !!!! first defines the "healthcare in crisis" problem. Through real patient experiences, the book describes the difficulties of getting through the maze of complexity among the plethora of "silo providers" which make up the industry. The heart of the book provides readers with a comprehensive solution that can work, a disruption that is necessary to provide Americans the medical care they need without the US public and healthcare providers and payors going into bankruptcy, insolvency or closure. This book delves into digitized medicine, payor and provider reimbursement models, and value-based healthcare delivery. It also includes a philosophy or mode of thinking and operation for the solutions that are needed for diagnosis-effective, cost-effective, and time-efficient healthcare delivery, of which digitized medicine, value-based care, and payor reimbursement modes are just some of the factors. The authors propose that the real solution involves having the patient at the center of the issues and changing from an archaic gold standard way of thinking to a "Predictive Analytic thinking" where one gets at the real truth by doing "real science" that in the end becomes effective not only for the population but for the individual person. This all leads to real person-centered and person-directed medicine and healthcare delivery.

The vector-borne Zika virus joins avian influenza, Ebola, and yellow fever as recent public health crises threatening pandemicity. By a combination of stochastic modeling and economic geography, this book proposes two key causes together explain the explosive spread of the worst of the vector-borne outbreaks. Ecosystems in which such pathogens are largely controlled by environmental stochasticity are being drastically streamlined by both agribusiness-led deforestation and deficits in public health and environmental sanitation. Consequently, a subset of infections that once burned out relatively quickly in local forests are now propagating across susceptible human populations whose vulnerability to infection is often exacerbated in structurally adjusted cities. The resulting outbreaks are characterized by greater global extent, duration, and momentum. As infectious diseases in an age of nation states and global health programs cannot, as much of the present modeling literature presumes, be described by interacting populations of host, vector, and pathogen alone, a series of control theory models is also introduced here. These models, useful to researchers and health officials alike, explicitly address interactions between government ministries and the pathogens they aim to control.

This book is a third-party evaluation of H1N1 prevention and control effects in China. Based on the characteristic of H1N1 pandemic around the world and current public health management system in China, this book evaluates the comprehensive effects by considering the countermeasures, joint prevent and control mechanism operated by central and local government, the cost and benefit effects and also the social influence during the whole process. Using the methods of interview and questionnaire, it investigates the central and local government, disease control and prevention center, hospital, community, school and enterprise in Beijing, Fujian, Henan, Guangdong and Sichuan provinces, and also presents the response from the public, patient and close contacts to evaluate the overall effects from different stakeholders. Assessment findings and policy suggestions are included in the book on the way to improve the efficiency of public health emergency system in China. This book provides a good reference to researchers and officials in public management, crisis management and public health studies.

"Accurate and fully explicit mathematical models and derivations make the proposed method truly universal irrespective of the geographical location and the kind of virus epidemic." Minvydas Ragulskis, Kaunas University of Technology, Lithuania The effects of a pandemic on public, personal and freight transport can be sudden and massive, and yet transport is vital to the functioning of an advanced economy and society. On the other hand, transport, due to social mobility, has a decisive influence on the speed and scope of epidemic spread. This book presents a complete methodology for assessing the hazards, and probability and risks of viral transmission on transport services, using as a detailed example the SARS-CoV-2 coronavirus pandemic. It gives proposals and recommendations for estimating human deaths caused by virus infection in transport. Significantly, it considers not only passenger transport but also freight transport, such as delivery or parcel services. The tools include a matrix of hazard assessment in various transportation services, with a methodology for estimating the probability of virus transmission through both droplets and surface contact. These allow estimation of the effects of infections and consequent epidemic risk in all kinds of transport services, including freight, and provide methods for forecasting and risk management which determine transport safety. Rafal Burdzik is a professor in the Faculty of Transport and Aviation Engineering at Silesian University of Technology, Poland, with more than 20 years of transport research experience.