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Bias analysis quantifies the influence of systematic error on an epidemiology study’s estimate of association. The fundamental methods of bias analysis in epi- miology have been well described for decades, yet are seldom applied in published presentations of epidemiologic research. More recent advances in bias analysis, such as probabilistic bias analysis, appear even more rarely. We suspect that there are both supply-side and demand-side explanations for the scarcity of bias analysis. On the demand side, journal reviewers and editors seldom request that authors address systematic error aside from listing them as limitations of their particular study. This listing is often accompanied by explanations for why the limitations should not pose much concern. On the supply side, methods for bias analysis receive little attention in most epidemiology curriculums, are often scattered throughout textbooks or absent from them altogether, and cannot be implemented easily using standard statistical computing software. Our objective in this text is to reduce these supply-side barriers, with the hope that demand for quantitative bias analysis will follow.
This textbook and guide focuses on methodologies for bias analysis in epidemiology and public health, not only providing updates to the first edition but also further developing methods and adding new advanced methods. As computational power available to analysts has improved and epidemiologic problems have become more advanced, missing data, Bayes, and empirical methods have become more commonly used. This new edition features updated examples throughout and adds coverage addressing: Measurement error pertaining to continuous and polytomous variables Methods surrounding person-time (rate) data Bias analysis using missing data, empirical (likelihood), and Bayes methods A unique feature of th...
As well as being a reference for the design, analysis, and interpretation of vaccine studies, the text covers all design and analysis stages, from vaccine development to post-licensure surveillance, presenting likelihood, frequentists, and Bayesian approaches.
This book presents a comprehensive theory of the ethics and political philosophy of public health surveillance based on reciprocal obligations among surveillers, those under surveillance, and others potentially affected by surveillance practices. Public health surveillance aims to identify emerging health trends, population health trends, treatment efficacy, and methods of health promotion--all apparently laudatory goals. Nonetheless, as with anti-terrorism surveillance, public health surveillance raises complex questions about privacy, political liberty, and justice both of and in data use. Individuals and groups can be chilled in their personal lives, stigmatized or threatened, and used fo...
Cystic Fibrosis (CF) is a multisystem disease whose symptoms and signs involve the gastrointestinal tract (thus affecting nutritional status), endocrine system, reproductive system and the respiratory tract (nose, sinuses and lungs). Despite new treatments, the median survival for patients with CF is less than optimal, primarily due to complications of obstructive lung disease. Currently there are approximately 60,000-80,000 people worldwide with CF. The clinical manifestations of CF are caused by dysfunction of CFTR (cystic fibrosis transmembrane conductance regulator), a multifunctional cyclic-AMP regulated ion channel protein. Over time, there has been dramatic improvement in CF patient l...
A practical action plan for reinventing healthcare in a post-pandemic world—from a physician-entrepreneur who works with Fortune 500 companies. If the healthcare system were an emperor, Covid-19 tragically revealed that it had no clothes. Healthcare had to adapt, and quickly―sparking a dramatic acceleration of virtual care, drive-through testing, and home-based services. In the process, old rules were rewritten and, perhaps surprisingly, largely in a good way for patients. To succeed in the post-pandemic world, all of us―patients, caregivers, providers, employers, investors, technologists, and policymakers―need to understand the new healthcare landscape and change our strategies and ...
Get a quick, expert overview of the many key facets of heart failure research with this concise, practical resource by Dr. Longjian Liu. This easy-to-read reference focuses on the incidence, distribution, and possible control of this significant clinical and public health problem which is often associated with higher mortality and morbidity, as well as increased healthcare expenditures. This practical resource brings you up to date with what's new in the field and how it can benefit your patients. - Features a wealth of information on epidemiology and research methods related to heart failure. - Discusses pathophysiology and risk profile of heart failure, research and design, biostatistical basis of inference in heart failure study, advanced biostatistics and epidemiology applied in heart failure study, and precision medicine and areas of future research. - Consolidates today's available information and guidance in this timely area into one convenient resource.
Gene delivery is a transport of genes of therapeutic values into the chromosomes of the cells or tissues which can be targeted to replace the faulty genes. In last two decades lot of research efforts are dedicated to gene delivery for therapeutic applications. Today gene therapy is promising approach in treatment of genetic diseases including mitochondrial related diseases like blindness, muscular dystrophy, cystic fibrosis, and some cancers. Gene Delivery Systems: Nano Delivery Technologies observes the exploration of nanotechnology for gene therapy and gene delivery. Written by prominent authors in the field, this book covers various aspects of gene delivery including challenges in deliver...