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The first textbook on public health intelligence presents in depth the key concepts, methods, and objectives of this increasingly important competency. It systematically reviews types of evidence and data that comprise intelligence, effective techniques for assessment, analysis, and interpretation, and the role of this knowledge in quality health service delivery. The book’s learner-centered approach gives readers interactive context for mastering the processes of gathering and working with intelligence as well as its uses in informing public health decision-making. And its pragmatic framework will help establish standards for training, practice, and policy, leading to continued improvements in population health. This path-breaking resource: Offers a comprehensive, up-to-date introduction to public health intelligence, a core area of public health competency. Is suitable for both graduates’ and healthcare professionals’ training and development for national and international contexts. Helps readers apply theory to real-life scenarios, from multi-professional perspectives. Features activities, case studies, and discussion tasks for easy reader engagement. Anticipates and examines emerging developments in the field. Public Health Intelligence - Issues of Measure and Method is bedrock reading for postgraduate and advanced undergraduate students in public health, global health, health policy, health service management, nursing, medicine, statistics, epidemiology, quantitative methods, health intelligence, health inequality, and other allied healthcare fields. It is also a salient text for public health practitioners and health policymakers. "This book is a 'must-read' for students contemplating a career in Public Health or for anyone who is already in practice. The breadth of chapters from respected authors provide a detailed overview and critique of issues related to public health intelligence. A key strength of the book is that it is written with both students and practitioners in mind." Gurch Randhawa, PhD, FFPH, Professor of Diversity in Public Health & Director, Institute for Health Research, University of Bedfordshire, UK.

Hygiene. Public health. Protection --- Epidemiology --- volksgezondheid --- epidemiologie

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Voor de verbetering van de preventieve en curatieve gezondheidszorg, in zowel de medische als de paramedische sector, is epidemiologisch onderzoek van wezenlijk belang. Een goede opzet en uitvoering van het onderzoek is daarbij essentieel en het interpreteren van de resultaten dient zorgvuldig te gebeuren.Het Leerboek Epidemiologie biedt een leidraad voor de uitvoering en interpretatie van toegepast medisch-wetenschappelijk onderzoek. Epidemiologie wordt in dit boek vooral gezien als de methodeleer van onderzoek naar gezondheid en ziekte in menselijke populaties. Het boek weerspiegelt de veelzijdigheid van het vakgebied en behandelt zowel etiologie, diagnostiek, prognostiek en interventie. De nadruk ligt op het opzetten van onderzoek en op het interpreteren van de resultaten ervan.Deze zevende druk is grondig herzien. Het taalgebruik is vereenvoudigd, er zijn meer illustraties toegevoegd en er is voor eenduidiger terminologie gekozen. Ook is de inhoud aangepast aan de laatste ontwikkelingen van het vakgebied.Het Leerboek Epidemiologie is primair bedoeld als leerboek voor studenten aan universitaire opleidingen (zoals geneeskunde, biomedische wetenschappen,gezondheidswetenschappen, bewegingswetenschappen) en hbo-opleidingen (zoals fysiotherapie, diëtetiek en andere paramedische beroepen). Daarnaast is dit boek geschikt voor individuele bestudering en als naslagwerk.

Epidemiologie --- 616.9 --- Epidemiology --- Disease --- epidemiology --- Social Epidemiology --- Epidemiologies, Social --- Epidemiology, Social --- Social Epidemiologies

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Applied Survival Analysis Using R covers the main principles of survival analysis, gives examples of how it is applied, and teaches how to put those principles to use to analyze data using R as a vehicle. Survival data, where the primary outcome is time to a specific event, arise in many areas of biomedical research, including clinical trials, epidemiological studies, and studies of animals. Many survival methods are extensions of techniques used in linear regression and categorical data, while other aspects of this field are unique to survival data. This text employs numerous actual examples to illustrate survival curve estimation, comparison of survivals of different groups, proper accounting for censoring and truncation, model variable selection, and residual analysis. Because explaining survival analysis requires more advanced mathematics than many other statistical topics, this book is organized with basic concepts and most frequently used procedures covered in earlier chapters, with more advanced topics near the end and in the appendices. A background in basic linear regression and categorical data analysis, as well as a basic knowledge of calculus and the R system, will help the reader to fully appreciate the information presented. Examples are simple and straightforward while still illustrating key points, shedding light on the application of survival analysis in a way that is useful for graduate students, researchers, and practitioners in biostatistics. Clearly illustrates concepts of survival analysis principles and analyzes actual survival data using R, in addition to including an appendix with a basic introduction to R Organized via basic concepts and most frequently used procedures, with advanced topics toward the end of the book and in appendices Includes multiple original data sets that have not appeared in other textbooks Dirk F. Moore is Associate Professor of Biostatistics at the Rutgers School of Public Health and the Rutgers Cancer Institute of New Jersey. He received a Ph.D. in biostatistics from the University of Washington in Seattle and, prior to joining Rutgers, was a faculty member in the Statistics Department at Temple University. He has published numerous papers on the theory and application of survival analysis and other biostatistics methods to clinical trials and epidemiology studies.

Statistical science --- Mathematical statistics --- Biomathematics. Biometry. Biostatistics --- Epidemiology --- medische statistiek --- biostatistiek --- statistiek --- epidemiologie --- biometrie --- statistisch onderzoek

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This book will be of interest to readers active in the fields of survival analysis, genetics, ecology, biology, demography, reliability and quality control. Since Sir David Cox’s pioneering work in 1972, the proportional hazards model has become the most important model in survival analysis. The success of the Cox model stimulated further studies in semiparametric and nonparametric theories, counting process models, study designs in epidemiology, and the development of many other regression models that could offer more flexible or more suitable approaches in data analysis. Flexible semiparametric regression models are increasingly being used to relate lifetime distributions to time-dependent explanatory variables. Throughout the book, various recent statistical models are developed in close connection with specific data from experimental studies in clinical trials or from observational studies.

Statistical science --- Biomathematics. Biometry. Biostatistics --- Epidemiology --- medische statistiek --- biostatistiek --- statistiek --- epidemiologie --- biometrie --- statistisch onderzoek

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Brucellosis --- Milk --- Meat --- Occupational exposure --- Goats. --- Humans. --- Cattle. --- Brucellose chez les animaux --- Lait --- Viande --- Chèvre domestique --- Bovins --- epidemiology. --- microbiology. --- Epidémiologie --- Microbiologie --- Ecuador. --- Occupational Exposure. --- Brucellose --- Chez les animaux --- Epidémiologie. --- Microbiologie. --- Chèvre domestique. --- Bovins. --- Occupational Exposure --- Goats --- Humans --- Cattle --- epidemiology --- microbiology