This book introduces flood inundation area and flood risks assessment based on a comprehensive monitoring system using remote sensing and geographic information system technologies. Taking the 2011 flood disaster of Ayutthaya in Thailand as an example, it presents a flood intrusion zone identification method based on remote sensing technology, spatial information technology and geographic information system for flood disaster monitoring and early warning system. It introduces the study area and data, vegetation index, improved support vector machine and flood intrusion zone identification method. It also analyzes the flood remote sensing parameters and waterborne diseases, method of risk assessment of waterborne disease outbreak, waterborne disease outbreak risk monitoring based on backpropagation neural network and its expert system. It not only promotes a new interdisciplinary approach both in public health and space information technology, but also greatly supports decision makers in disaster reduction.

The get-it-over-with-quickly approach to statistics has been encouraged - and often necessitated - by the short time allotted to it in most curriculums. If included at all, statistics is presented briefly, as a task to be endured mainly because pertinent questions may appear in subsequent examinations for licensure or other certifications. However, in later professional activities, clinicians and biomedical researchers will constantly be confronted with reports containing statistical expressions and analyses.

Not just a set of cookbook recipes, Principles of Medical Statistics is designed to get you thinking about data and statistical procedures. It covers many new statistical methods and approaches like box plots, stem and leaf plots, concepts of stability, the bootstrap, and the jackknife methods of resampling. The book is arranged in a logical sequence that advances from simple to more elaborate results. The text describes all the conventional statistical procedures, and offers reasonably rigorous accounts of many of their mathematical justifications. Although the conventional mathematical principles are given a respectful account, the book provides a distinctly clinical orientation with examples and teaching exercises drawn from real world medical phenomena.

Statistical procedures are an integral part of the basic background needed by biomedical researchers, students, and clinicians. Containing much more than most elementary texts, Principles of Medical Statistics fills the gap often found in the current curriculum. It repairs the imbalance that gives so little attention to the role of statistics as a prime component of basic biomedical education.

This book includes research articles and expository papers on the applications of artificial intelligence and big data analytics to battle the pandemic. In the context of COVID-19, this book focuses on how big data analytic and artificial intelligence help fight COVID-19. The book is divided into four parts. The first part discusses the forecasting and visualization of the COVID-19 data. The second part describes applications of artificial intelligence in the COVID-19 diagnosis of chest X-Ray imaging. The third part discusses the insights of artificial intelligence to stop spread of COVID-19, while the last part presents deep learning and big data analytics which help fight the COVID-19.

This widely used text provides a clear and critical summary of research approaches to the epidemiological study of workplace hazards. It describes the historical development of occupational epidemiology, methods for characterizing occupational exposures, and techniques for designing and implementing epidemiologic studies in this area. The relative strengths and limitations of various study designs for investigating specific health outcomes are emphasized. Also included are more advanced discussions of statistical analysis, exposure and dose modeling, and subsequent applications of data derived from epidemiologic research, as in meta-analysis, pooled analysis, and statistical analysis, exposure and dose modeling, and risk assessment. Since the first edition was published 15 years ago, there have been numerous advances in epidemiologic methods to accommodate a broadened scope of investigations of occupational exposures and associated adverse health outcomes. Thus, in this Second Edition the authors have updated their discussions of methodology to include such topics as case-cohort and case-crossover designs and statistical analysis of repeated measures data, and have expanded the examples they use throughout the book to demonstrate the applications of these methods to a wide range of acute and chronic health outcomes. They have also added a new chapter on occupational health sureillance. Their text is unique for its strong emphasis on the definition and assessment of exposures, the application of quantitative exposure data to epidemiologic models, and the recognition that improvements in workplace risk identification and quantification will come from careful integration of theseapproaches. This fine volume will serve both as a textbook for courses on occupational epidemiology and as a practical handbook of the design, implementation, and evaluation of research in this field.

This book takes a historical and anthropological approach to understanding how non-human hosts and vectors of diseases are understood, at a time when emerging infectious diseases are one of the central concerns of global health. The volume critically examines the ways in which animals have come to be framed as 'epidemic villains' since the turn of the nineteenth century. Providing epistemological and social histories of non-human epidemic blame, as well as ethnographic perspectives on its recent manifestations, the essays explore this cornerstone of modern epidemiology and public health alongside its continuing importance in today's world. Covering diverse regions, the book argues that framing animals as spreaders and reservoirs of infectious diseases - from plague to rabies to Ebola - is an integral aspect not only to scientific breakthroughs but also to the ideological and biopolitical apparatus of modern medicine. As the first book to consider the impact of the image of non-human disease hosts and vectors on medicine and public health, it offers a major contribution to our understanding of human-animal interaction under the shadow of global epidemic threat.

This book describes the variety of direct and indirect population size estimation (PSE) methods available along with their strengths and weaknesses. Direct estimation methods, such as enumeration and mapping, involve contact with members of hard-to-reach groups. Indirect methods have practical appeal because they require no contact with members of hard-to-reach groups. One indirect method in particular, network scale-up (NSU), has several strengths over other PSE methods: It can be applied at a province/country level, it can estimate size of several hard-to-reach population in a single study, and it is implemented with members of the general population rather than members of hard-to-reach groups. The book discusses methods to collect, analyze, and adjust results and presents methods to triangulate and finalize PSEs.

This book comprehensively reviews the 10 most influential epidemics in history, going beyond morbid accounts of symptoms and statistics to tell the often forgotten stories of what made these epidemics so calamitous. Unlike other books on epidemics, which either focus on the science behind how microbes cause disease or tell first-person accounts of one particular disease, Epidemics: The Impact of Germs and Their Power over Humanity takes a holistic approach to explaining how these diseases have shaped who we are as a society. Each of the worst epidemic diseases is discussed from the perspective of how it has been a causative agent of change with respect to our history, religious traditions, social interactions, and technology. In looking at world history through the lens of epidemic diseases, readers will come to appreciate how much we owe to the oldest and smallest parasites. Adults and students interested in science and history-and especially anyone who appreciates a good story and has a healthy curiosity for the lesser-known facts of life-will find this book of interest. Health-care workers will also benefit greatly from this text, as will college students majoring in biology or a pre-health field. Discusses epidemic disease as a major driving force in shaping our world Brings epidemic diseases out of the background of historical narratives and demonstrates how they have had an immensely important role in deciding wars, toppling empires, sparking major leaps in technology, and even changing the human genome Integrates science with history, sociology, religion, and other disciplines to provide the reader with a unique perspective not found in most other accounts of epidemic disease Shares fascinating insights such as how an epidemic of yellow fever helped to double the size of the United States and why tuberculosis was once considered a disease of the intellectual elite

Review of the First Edition: The authors strive to reduce theory to a minimum, which makes it a self-learning text that is comprehensible for biologists, physicians, etc. who lack an advanced mathematics background. Unlike in many other textbooks, R is not introduced with meaningless toy examples; instead the reader is taken by the hand and shown around some analyses, graphics, and simulations directly relating to meta-analysis... A useful hands-on guide for practitioners who want to familiarize themselves with the fundamentals of meta-analysis and get started without having to plough through theorems and proofs. -Journal of Applied Statistics Statistical Meta-Analysis with R and Stata, Second Edition provides a thorough presentation of statistical meta-analyses (MA) with step-by-step implementations using R/Stata. The authors develop analysis step by step using appropriate R/Stata functions, which enables readers to gain an understanding of meta-analysis methods and R/Stata implementation so that they can use these two popular software packages to analyze their own meta-data. Each chapter gives examples of real studies compiled from the literature. After presenting the data and necessary background for understanding the applications, various methods for analyzing meta-data are introduced. The authors then develop analysis code using the appropriate R/Stata packages and functions. What's New in the Second Edition: Adds Stata programs along with the R programs for meta-analysis Updates all the statistical meta-analyses with R/Stata programs Covers fixed-effects and random-effects MA, meta-regression, MA with rare-event, and MA-IPD vs MA-SS Adds five new chapters on multivariate MA, publication bias, missing data in MA, MA in evaluating diagnostic accuracy, and network MA Suitable as a graduate-level text for a meta-data analysis course, the book is also a valuable reference for practitioners and biostatisticians (even those with little or no experience in using R or Stata) in public health, medical research, governmental agencies, and the pharmaceutical industry.

This interdisciplinary volume gathers selected, refereed contributions on various aspects of public health from several disciplines and research fields, including the philosophy of science, epidemiology, statistics and ethics. The contributions were originally presented at the 1st Barcelona conference of "Philosophy of Public Health" (5th - 7th May 2016). This book is intended for researchers interested in public health and the contemporary debates surrounding it.

Covers statistical concepts, methods and applications related to all aspects of survival analysis with cure, integration of insights gained from statistical analysis to decision-marking and inference in cancer research Self-contained as sufficient the technical details and statistical background are provided to make its materials easy to grasp Timely book on most relevant and important issues on cure models by experienced statistical researchers Includes Applications to real-life problems Inclusion of R codes for some of the novel methods and high-impact studies

Ticks of the family Ixodidae, commonly known as hard ticks, occur worldwide and are second only to mosquitoes as vectors of agents pathogenic to humans. Of the 729 currently recognized hard tick species, 283 (39%) have been implicated as human parasites, but the literature on these species is both immense and scattered, with the result that health professionals are often unable to determine whether a particular tick specimen, once identified, represents a species that is an actual or potential threat to its human host. In this book, two leading tick specialists provide a list of the species of Ixodidae that have been reported to feed on humans, with emphasis on their geographical distribution, principal hosts, and the tick life history stages associated with human parasitism. Also included is a discussion of 21 ixodid species that, while having been found on humans, are either not known to have actually fed or may have been misidentified. Additionally, 107 tick names that have appeared in papers on tick parasitism of humans, and that might easily confuse non-taxonomists, are shown to be invalid under the rules of zoological nomenclature. Although the species of ticks that attack humans have long attracted the attention of researchers, few comprehensive studies of these species have been attempted. By gleaning and analyzing the results of over 1,100 scientific papers published worldwide, the authors have provided an invaluable survey of hard tick parasitism that is unprecedented in its scope and detail.

Recent critiques of air quality management approaches currently employed in developed and many developing countries have suggested that efficiencies could be achieved if air quality management practices shifted from pollutant-by-pollutant approaches to a comprehensive multipollutant approach in which emission reduction decisions are based on relative risk and evaluated on their effectiveness in meeting environmental and health goals. This book assesses our technical readiness to undertake such an approach, and it outlines the technical developments that will be needed to achieve a risk-based approach air quality management that includes means for measuring the effectiveness of management decisions.

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.

Ever since Edwina Currie's salmonella, Britain has seemed cursed by major food safety scares, with E.coli and BSE particularly prominent. Amidst tabloid frenzy and recrimination, the public is dependent upon sober scientific risk assessment and rational evaluation of what went wrong. Hugh Pennington has been at the forefront of this as a scientist, expert witness and commentator, and this book is his accessible but rigorous account of these diseases and the events surrounding them. This is a disaster book for the general reader giving authoritative but non-technical accounts of BSE/variant CJD and E.coli O157 - what happened, what went wrong, the human interest, and the science - all in the context of disasters (like Piper Alpha, Aberfan, and rail crashes), history and politics.

Introductory Medical Statistics, now in its third edition, is an introductory textbook on basic statistical techniques. It is written for physicians, surgeons, radiation oncologists, medical physicists, radiographers, hospital administrators, medical statisticians in training, biochemists, and other professionals allied to medicine. It is suitable as a teaching text for clinicians working towards their professional examinations. It is also suitable for Maters degree courses in medical physics.
The third edition has been extensively revised and expanded to include:
Clinical trial design and analysis]
Multivariate analysis
Cox proportional hazards model
McNemar, Wicoxon, Mann-Whitney, Kruskal-Wallis, Mantel-Haenszel, and Kappa tests
Kaplan-Meier survival rates
Sensitivity and Specificity
Specification of treatment success, cure, and quality of life
Risk specification
Case-control and cohort epidemiological studies
Glossary of terms
The major change has been the advent of personal computing, so people rely on the power of their machine, and its software to number crunch. What is missing is that the software may not use the appropriate statistical error standard - Dick Mould

Statistics for Bioinformatics: Methods for Multiple Sequence Alignment provides an in-depth introduction to the most widely used methods and software in the bioinformatics field. With the ever increasing flood of sequence information from genome sequencing projects, multiple sequence alignment has become one of the cornerstones of bioinformatics. Multiple sequence alignments are crucial for genome annotation, as well as the subsequent structural, functional, and evolutionary studies of genes and gene products. Consequently, there has been renewed interest in the development of novel multiple sequence alignment algorithms and more efficient programs.

Routine applications of advanced statistical methods on real data have become possible in the last ten years because desktop computers have become much more powerful and cheaper. However, proper understanding of the challenging statistical theory behind those methods remains essential for correct application and interpretation, and rarely seen in the medical literature. Modern Methods for Epidemiology provides a concise introduction to recent development in statistical methodologies for epidemiological and biomedical researchers. Many of these methods have become indispensible tools for researchers working in epidemiology and medicine but are rarely discussed in details by standard textbooks of biostatistics or epidemiology. Contributors of this book are experienced researchers and experts in their respective fields. This textbook provides a solid starting point for those who are new to epidemiology, and for those looking for guidance in more modern statistical approaches to observational epidemiology. Epidemiological and biomedical researchers who wish to overcome the mathematical barrier of applying those methods to their research will find this book an accessible and helpful reference for self-learning and research. This book is also a good source for teaching postgraduate students in medical statistics or epidemiology.

Viruses and Society is geared towards professionals and students in college-level introductory biology courses devoted to understanding viruses, vaccines, and their global impact. The beginning of the book introduces cells, DNA, and viruses themselves. There follows a review of how the immune system works and how scientists and physicians harness the immune system to protect people through vaccines. Specific chapters will focus on the 1918 influenza pandemic, the fight to eradicate polio, the HIV/AIDS pandemic, and our current COVID-19 crisis. Additionally, the book reviews the uses of viruses in genetic engineering and in gene therapy as well. The book will conclude by describing public health initiatives to keep emerging viruses in check and the role of scientific communication in how viruses are perceived and have an impact on our society. Key Features 1) The text employs approachable and simplified language 2) Provides all the essential elements for understanding virus biology 3) Includes details on how viruses affect individuals 4) Describes the ways public health decisions are made in light of how viral pathogens spread 5) Highlights up to date scientific findings on the features of emerging viruses that will always be with us

A global health catastrophe narrowly averted. A world unprepared for another outbreak. In December 2013, a young boy in a tiny West African village contracted the deadly Ebola virus. The virus spread to his relatives, then to neighbouring communities, then across international borders. The world's first urban Ebola outbreak quickly overwhelmed the global health system and threatened to kill millions. As we are currently seeing, in an increasingly interconnected world in which everyone is one or two flights away from New York or London or Beijing, a localized epidemic has become a pandemic. Ebola's spread through West Africa to Nigeria, the United Kingdom and the United States sounded global alarms that the next killer outbreak is right around the corner - and that the world is woefully unprepared to combat a new deadly disease. From the poorest villages of rural West Africa to the Oval Office itself, this book tells the story of a deadly virus that spun wildly out of control - and reveals the truth about how close the world came to a catastrophic global pandemic. It is a story that serves as a cautionary tale for the COVID-19 epidemic currently spreading throughout the world.

Provides researchers with a reproducible research workflow for using R/RStudio to make the entire researchprocess reproducible; from data gathering, to analysis, to presentation Includes instructions not only for creating reproducible research in R, but also extensively discusses how to take advantage of recent developments in RStudio. Emphasizes the presentation of reproducible research with non-print formats such as HTML5 slideshows, blogs, and other web-based content. Covers a range of techniques to organize and remotely store files at all stages of the research process. These techniques both streamline the research process, especially by making revisions easier, and enhance The book itself will be reproducible, as all of the data, analysis, and markup files will be made available online.

Informed and Healthy: Theoretical and Applied Perspectives on the Value of Information to Health Care focuses on two major issues: the value attributed to information by users and its effect on health care; and, a new model of information behavior in which the value of information drives various information activities (unlike many information models which tend to give prominence to information needs). The inductive development of the model is explained, with associated implications for theory and transferability or applicability elsewhere. The book uses a case study of the health information system in Uganda and expands the analysis by comparing it to other systems utilized by different countries in diverse levels of development. Topics such as access and use of information; value attribution and effect on health outcomes; and modelling information behavior and its implications on health informatics are discussed in detail. This book is a valuable resource for health professionals, planners, and policy makers, as well as researchers interested in health information systems and their applicability in different environments.

Provides a step-by-step approach to statistical procedures to analyze data and conduct research, with detailed sections in each chapter explaining SPSS(R) and Excel(R) applications This book identifies connections between statistical applications and research design using cases, examples, and discussion of specific topics from the social and health sciences. Researched and class-tested to ensure an accessible presentation, the book combines clear, step-by-step explanations for both the novice and professional alike to understand the fundamental statistical practices for organizing, analyzing, and drawing conclusions from research data in their field. The book begins with an introduction to descriptive and inferential statistics and then acquaints readers with important features of statistical applications (SPSS and Excel) that support statistical analysis and decision making. Subsequent chapters treat the procedures commonly employed when working with data across various fields of social science research. Individual chapters are devoted to specific statistical procedures, each ending with lab application exercises that pose research questions, examine the questions through their application in SPSS and Excel, and conclude with a brief research report that outlines key findings drawn from the results. Real-world examples and data from social and health sciences research are used throughout the book, allowing readers to reinforce their comprehension of the material. Using Statistics in the Social and Health Sciences with SPSS(R) and Excel(R) includes: Use of straightforward procedures and examples that help students focus on understanding of analysis and interpretation of findings Inclusion of a data lab section in each chapter that provides relevant, clear examples Introduction to advanced statistical procedures in chapter sections (e.g., regression diagnostics) and separate chapters (e.g., multiple linear regression) for greater relevance to real-world research needs Emphasizing applied statistical analyses, this book can serve as the primary text in undergraduate and graduate university courses within departments of sociology, psychology, urban studies, health sciences, and public health, as well as other related departments. It will also be useful to statistics practitioners through extended sections using SPSS(R) and Excel(R) for analyzing data. Martin Lee Abbott, PhD, is Professor of Sociology at Seattle Pacific University, where he has served as Executive Director of the Washington School Research Center, an independent research and data analysis center funded by the Bill & Melinda Gates Foundation. Dr. Abbott has held positions in both academia and industry, focusing his consulting and teaching in the areas of statistical procedures, program evaluation, applied sociology, and research methods. He is the author of Understanding Educational Statistics Using Microsoft Excel(R) and SPSS(R), The Program Evaluation Prism: Using Statistical Methods to Discover Patterns, and Understanding and Applying Research Design, also from Wiley.

In diesem Open-Access-Tagungsband werden die Erfahrungen mit der Corona-Pandemie durch renommierte Forscherinnen und Forscher wissenschaftlich reflektiert. Neben dem gesellschaftlichen und politischen Umgang mit Covid-19, geht es um vergangene Pandemien sowie zukunftige Infektionsgefahren.Die Akademie der Wissenschaften in Hamburg veranstaltete im April 2022 das Symposium "Infektionen und Gesellschaft - was haben wir gelernt?". Im interdisziplinaren Diskurs ging es darum, die Bedrohung durch Infektionserreger zu eruieren und die Reaktionsmoeglichkeiten der Gesellschaft auszuloten. Das Symposium wurde von der Arbeitsgruppe "Infektionsforschung und Gesellschaft" der Akademie der Wissenschaften in Hamburg konzipiert.

This book examines statistical methods and models used in the fields of global health and epidemiology. It includes methods such as innovative probability sampling, data harmonization and encryption, and advanced descriptive, analytical and monitory methods. Program codes using R are included as well as real data examples. Contemporary global health and epidemiology involves a myriad of medical and health challenges, including inequality of treatment, the HIV/AIDS epidemic and its subsequent control, the flu, cancer, tobacco control, drug use, and environmental pollution. In addition to its vast scales and telescopic perspective; addressing global health concerns often involves examining resource-limited populations with large geographic, socioeconomic diversities. Therefore, advancing global health requires new epidemiological design, new data, and new methods for sampling, data processing, and statistical analysis. This book provides global health researchers with methods that will enable access to and utilization of existing data. Featuring contributions from both epidemiological and biostatistical scholars, this book is a practical resource for researchers, practitioners, and students in solving global health problems in research, education, training, and consultation.