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In recent public workshops and working group meetings, the Forum on Microbial Threats of the Institute of Medicine (IOM) has examined a variety of infectious disease outbreaks with pandemic potential, including those caused by influenza (IOM, 2005) and severe acute respiratory syndrome (SARS) (IOM, 2004). Particular attention has been paid to the potential pandemic threat posed by the H5N1 strain of avian influenza, which is now endemic in many Southeast Asian bird populations. Since 2003, the H5N1 subtype of avian influenza has caused 185 confirmed human deaths in 11 countries, including some cases of viral transmission from human to human (WHO, 2007). But as worrisome as these developments are, at least they are caused by known pathogens. The next pandemic could well be caused by the emergence of a microbe that is still unknown, much as happened in the 1980s with the emergence of the human immunodeficiency virus (HIV) and in 2003 with the appearance of the SARS coronavirus. Previous Forum meetings on pandemic disease have discussed the scientific and logistical challenges associated with pandemic disease recognition, identification, and response. Participants in these earlier meetings also recognized the difficulty of implementing disease control strategies effectively. Ethical and Legal Considerations in Mitigating Pandemic Disease: Workshop Summary as a factual summary of what occurred at the workshop.
Interest in the role that decision making plays in adolescents' involvement in high-risk behaviors led the Office of the Assistant Secretary of Planning and Evaluation of the U.S. Department of Health and Human Services to request the Board on Children, Youth, and Families to convene a workshop on adolescent decision making. The Board on Children, Youth, and Families is a joint activity of the National Research Council (NRC) and the Institute of Medicine. A workshop was held on January 6-7, 1998, to examine what is known about adolescents' decision-making skills and the implications of that knowledge for programs to further their healthy development.
"This booklet is written for managers and supervisors in industries that involve the manual handling of containers. It offers suggestions to improve the handling of rectangular, square, and cylindrical containers, sacks, and bags. "Improving Manual Material Handling in Your Workplace" lists the benefits of improving your work tasks. It also contains information on risk factors, types of ergonomic improvements, and effective training and sets out a four-step proactive action plan. The plan helps you identify problems, set priorities, make changes, and follow up. Sections 1 and 2 of "Improvement Options" provide ways to improve lifting, lowering, filling, emptying, or carrying tasks by changing work practices and/or the use of equipment. Guidelines for safer work practices are also included. Section 3 of "Improvement Options" provides ideas for using equipment instead of manually handling individual containers. Guidelines for safer equipment use are also included. For more help the "Resources" section contains additional information on administrative improvements, work assessment tools and comprehensive analysis methods. This section also includes an improvement evaluation tool and a list of professional and trade organizations related to material handling."--Page 6.
Urban slum dwellers—especially in emerging-economy countries—are often poor, live in squalor, and suffer unnecessarily from disease, disability, premature death, and reduced life expectancy. Yet living in a city can and should be healthy. Slum Health exposes how and why slums can be unhealthy; reveals that not all slums are equal in terms of the hazards and health issues faced by residents; and suggests how slum dwellers, scientists, and social movements can come together to make slum life safer, more just, and healthier. Editors Jason Corburn and Lee Riley argue that valuing both new biologic and “street” science—professional and lay knowledge—is crucial for improving the well-being of the millions of urban poor living in slums.
Topics in Mathematical Modeling is an introductory textbook on mathematical modeling. The book teaches how simple mathematics can help formulate and solve real problems of current research interest in a wide range of fields, including biology, ecology, computer science, geophysics, engineering, and the social sciences. Yet the prerequisites are minimal: calculus and elementary differential equations. Among the many topics addressed are HIV; plant phyllotaxis; global warming; the World Wide Web; plant and animal vascular networks; social networks; chaos and fractals; marriage and divorce; and El Niño. Traditional modeling topics such as predator-prey interaction, harvesting, and wars of attrition are also included. Most chapters begin with the history of a problem, follow with a demonstration of how it can be modeled using various mathematical tools, and close with a discussion of its remaining unsolved aspects. Designed for a one-semester course, the book progresses from problems that can be solved with relatively simple mathematics to ones that require more sophisticated methods. The math techniques are taught as needed to solve the problem being addressed, and each chapter is designed to be largely independent to give teachers flexibility. The book, which can be used as an overview and introduction to applied mathematics, is particularly suitable for sophomore, junior, and senior students in math, science, and engineering.
This book grew out of the discussions and presentations that began during the Workshop on Emerging and Reemerging Diseases (May 17-21, 1999) sponsored by the Institute for Mathematics and its Application (IMA) at the University of Minnesota with the support of NIH and NSF. The workshop started with a two-day tutorial session directed at ecologists, epidemiologists, immunologists, mathematicians, and scientists interested in the study of disease dynamics. The core of this first volume, Volume 125, covers tutorial and research contributions on the use of dynamical systems (deterministic discrete, delay, PDEs, and ODEs models) and stochastic models in disease dynamics. The volume includes the study of cancer, HIV, pertussis, and tuberculosis. Beginning graduate students in applied mathematics, scientists in the natural, social, or health sciences or mathematicians who want to enter the fields of mathematical and theoretical epidemiology will find this book useful.
Bullshit isn’t what it used to be. Now, two science professors give us the tools to dismantle misinformation and think clearly in a world of fake news and bad data. “A modern classic . . . a straight-talking survival guide to the mean streets of a dying democracy and a global pandemic.”—Wired Misinformation, disinformation, and fake news abound and it’s increasingly difficult to know what’s true. Our media environment has become hyperpartisan. Science is conducted by press release. Startup culture elevates bullshit to high art. We are fairly well equipped to spot the sort of old-school bullshit that is based in fancy rhetoric and weasel words, but most of us don’t feel qualified to challenge the avalanche of new-school bullshit presented in the language of math, science, or statistics. In Calling Bullshit, Professors Carl Bergstrom and Jevin West give us a set of powerful tools to cut through the most intimidating data. You don’t need a lot of technical expertise to call out problems with data. Are the numbers or results too good or too dramatic to be true? Is the claim comparing like with like? Is it confirming your personal bias? Drawing on a deep well of expertise in statistics and computational biology, Bergstrom and West exuberantly unpack examples of selection bias and muddled data visualization, distinguish between correlation and causation, and examine the susceptibility of science to modern bullshit. We have always needed people who call bullshit when necessary, whether within a circle of friends, a community of scholars, or the citizenry of a nation. Now that bullshit has evolved, we need to relearn the art of skepticism.
In 1918-1919 influenza raged around the globe in the worst pandemic in recorded history. Focusing on those closest to the crisis--patients, families, communities, public health officials, nurses and doctors--this book explores the epidemic in the United States.
This SpringerBrief discusses the characteristics of spatiotemporal movement data, including uncertainty and scale. It investigates three core aspects of Computational Movement Analysis: Conceptual modeling of movement and movement spaces, spatiotemporal analysis methods aiming at a better understanding of movement processes (with a focus on data mining for movement patterns), and using decentralized spatial computing methods in movement analysis. The author presents Computational Movement Analysis as an interdisciplinary umbrella for analyzing movement processes with methods from a range of fields including GIScience, spatiotemporal databases and data mining. Key challenges in Computational Movement Analysis include bridging the semantic gap, privacy issues when movement data involves people, incorporating big and open data, and opportunities for decentralized movement analysis arising from the internet of things. The interdisciplinary concepts of Computational Movement Analysis make this an important book for professionals and students in computer science, geographic information science and its application areas, especially movement ecology and transportation research.