Bioterrorism is not a new threat, but in an increasingly interconnected world, the potential for catastrophic outcomes is greater today than ever. The medical and public health communities are establishing biosurveillance systems designed to proactively monitor populations for possible disease outbreaks as a first line of defense. The ideal biosurveillance system should identify trends not visible to individual physicians and clinicians in near-real time. Many of these systems use statistical algorithms to look for anomalies and to trigger epidemiologic investigation, quantification, localization and outbreak management. This book discusses the design and evaluation of statistical methods for effective biosurveillance for readers with minimal statistical training. Weaving public health and statistics together, it presents basic and more advanced methods, with a focus on empirically demonstrating added value. Although the emphasis is on epidemiologic and syndromic surveillance, the statistical methods can be applied to a broad class of public health surveillance problems.
This is the first three chapters of a textbook for data scientists who want to improve how they work with, analyze, and extract information from data. The focus of the textbook is how to appropriately apply statistical methods, both simple and sophisticated, to 21st century data and problems. This book contains the first three chapters: Introduction -- Data Science and Statistics, Descriptive Statistics, and Data Visualization -- as well as the book front matter. Subsequent chapters will be published in 3- to 5-chapter sets as they become available.The textbook is intended for current and future data scientists, and for anyone interested in deriving information from data. It requires some mathematical sophistication on the part of the reader, as well as comfort using computers and statistical software.Data science is a new field that has arisen to exploit the proliferation of data in the modern world. Mathematical statistics dates back to the mid-18th century, where the field began as the systematic collection of population and economic data by nations. The modern practice of statistics – which includes the collection, summarization, and analysis of data – dates to the early 20th century. Today statistical methods are widely used by governments, businesses and other organizations, as well as by all scientific disciplines.It has been said that a data scientist must have a better grasp of statistics than the average computer scientist and a better grasp of programming than the average statistician. This book will give data scientists a firm foundation in statistics.
With COVID-19 sweeping across the globe with near impunity, it is thwarting governments and health organizations efforts to contain it. Not since the 1918 Spanish Flu have citizens of developed countries experienced such a large-scale disease outbreak that is having devastating health and economic impacts. One reason such outbreaks are not more common has been the success of the public health community, including epidemiologists and biostatisticians, in identifying and then mitigating or eliminating the outbreaks. Monitoring the Health of Populations by Tracking Disease Outbreaks: Saving Humanity from the Next Plague is the story of the application of statistics for disease detection and tracking. The work of public health officials often crucially depends on statistical methods to help discern whether an outbreak may be occurring and, if there is sufficient evidence of an outbreak, then to locate and track it. Statisticians also help collect critical information, and they analyze the resulting data to help investigators zero in on a cause for a disease. With the recent outbreaks of diseases such as swine and bird flu, Ebola, and now COVID-19, the role that epidemiologists and biostatisticians play is more important than ever. Features: · Discusses the crucial roles of statistics in early disease detection. · Outlines the concepts and methods of disease surveillance. · Covers surveillance techniques for communicable diseases like Zika and chronic diseases such as cancer. · Gives real world examples of disease investigations including smallpox, syphilis, anthrax, yellow fever, and microcephaly (and its relationship to the Zika virus). Via the process of identifying an outbreak, finding its cause, and developing a plan to prevent its reoccurrence, this book tells the story of how medical and public health professionals use statistics to help mitigate the effects of disease. This book will help readers understand how statisticians and epidemiologists help combat the spread of such diseases in order to improve public health across the world.
Describes RAND's evaluation of performance of a prototype military recruiting station located in an outlet mall in northern Virginia during its first year of operation. Evaluation includes statistical information on performance indicators, description of services' use of station, conclusions on MERS concept potential, and recommendations for experimental use of prototype station.
Internet-based surveys, although still in their infancy, are becomingincreasingly popular because they are believed to be faster, better,cheaper, and easier to conduct than surveys using more-traditional telephoneor mail methods. Based on evidence in the literature and real-life casestudies, this book examines the validity of those claims. The authorsdiscuss the advantages and disadvantages of using e-mail and the Web toconduct research surveys, and also offer practical suggestions for designing and implementing Internet surveys most effectively.Among other findings, the authors determined that Internet surveys may bepreferable to mail or telephone surveys when a list of e-mail addresses forthe target population is available, thus eliminating the need for mail orphone invitations to potential respondents. Internet surveys also arewell-suited for larger survey efforts and for some target populations thatare difficult to reach by traditional survey methods. Web surveys areconducted more quickly than mail or phone surveys when respondents arecontacted initially by e-mail, as is often the case when a representativepanel of respondents has been assembled in advance. And, although surveysincur virtually no coding or data-entry costs because the data are capturedelectronically, the labor costs for design and programming can be high.
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