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Biosurveillance
As evidenced by the anthrax attacks in 2001, the SARS outbreak in 2003, and the H1N1 influenza pandemic in 2009, a pathogen does not recognize geographic or national boundaries, often leading to devastating consequences. Automated biosurveillance systems have emerged as key solutions for mitigating current and future health-related events. Focusing
Characteristics and Geographic Dispersion of Syndromic Surveillance Systems in the United States in 2008
To understand the characteristics, scope, and geographic dispersion of syndromic surveillance systems in the United States in 2008, we reviewed information about their existence and characteristics in each state. We abstracted and compiled data from peer-reviewed literature, public reports, news stories, press releases, and Internet sites; we then analyzed the data, using a systematic instrument. For systems that collected emergency department (ED) information, we estimated the percentage of annual ED visits whose data were reported to the system. In 2008, 39 states and the District of Columbia had syndromic surveillance systems. ED records (65 percent) and hospital admissions records (43 pe...
Data Action
How to use data as a tool for empowerment rather than oppression. Big data can be used for good, from tracking disease to exposing human rights violations, and for bad, implementing surveillance and control. Data inevitably represents the ideologies of those who control its use; data analytics and algorithms too often exclude women, the poor, and ethnic groups. In Data Action, Sarah Williams provides a guide for working with data in more ethical and responsible ways. Williams outlines a method that emphasizes collaboration among data scientists, policy experts, data designers, and the public. The approach generates policy debates, influences civic decisions, and informs design to help ensure that the voices of people represented in the data are neither marginalized nor left unheard.
AI for Disease Surveillance and Pandemic Intelligence
This book aims to highlight the latest achievements in the use of artificial intelligence for digital disease surveillance, pandemic intelligence, as well as public and clinical health surveillance. The edited book contains selected papers presented at the 2021 Health Intelligence workshop, co-located with the Association for the Advancement of Artificial Intelligence (AAAI) annual conference, and presents an overview of the issues, challenges, and potentials in the field, along with new research results. While disease surveillance has always been a crucial process, the recent global health crisis caused by COVID-19 has once again highlighted our dependence on intelligent surveillance infrastructures that provide support for making sound and timely decisions. This book provides information for researchers, students, industry professionals, and public health agencies interested in the applications of AI in population health and personalized medicine.
The Big Data Agenda
This book highlights that the capacity for gathering, analysing, and utilising vast amounts of digital (user) data raises significant ethical issues. Annika Richterich provides a systematic contemporary overview of the field of critical data studies that reflects on practices of digital data collection and analysis. The book assesses in detail one big data research area: biomedical studies, focused on epidemiological surveillance. Specific case studies explore how big data have been used in academic work. The Big Data Agenda concludes that the use of big data in research urgently needs to be considered from the vantage point of ethics and social justice. Drawing upon discourse ethics and critical data studies, Richterich argues that entanglements between big data research and technology/ internet corporations have emerged. In consequence, more opportunities for discussing and negotiating emerging research practices and their implications for societal values are needed.
Official Congressional Directory 114th Congress, 2015-2016, Convened January 2015
Directory includes directory information for Congress, including officers, committees, and Congressional advisory boards, commissions and other groups, and legislative agencies; for the Executive branch including the Executive office of the president, each Cabinet agency, independent agencies, commissions and boards; for the Judiciary; for the goverment of the District of Columbia; for selected international organizations; for foreign diplomatic Offices in the United States; and for the Congressional press galleries. Includes also a short statistical section and Congressional district maps.
Space Supporting Africa
This book addresses the need to support decision-makers across Africa by promoting awareness of the importance of space technologies and data to African development through the presentation of existing examples where space supports education and healthcare, and by making recommendations for further roll-out of these efforts. This is necessary because of the enduring misconception that space-related research and expenditure competes with other, more pressing, needs on the continent, when in truth space can play a major role in meeting these needs. Accordingly, the book unpacks the United Nations Sustainable Development Goals (SDGs) 2030 and the critical needs they address in the African co...
Artificial Intelligence and Natural Algorithms
This book informs the reader about applications of Artificial Intelligence (AI) and nature-inspired algorithms in different situations. Each chapter in this book is written by topic experts on AI, nature-inspired algorithms and data science. The basic concepts relevant to these topics are explained, including evolutionary computing (EC), artificial neural networks (ANN), swarm intelligence (SI), and fuzzy systems (FS). Additionally, the book also covers optimization algorithms for data analysis. The contents include algorithms that can be used in systems designed for plant science research, load balancing, environmental analysis and healthcare. The goal of the book is to equip the reader - students and data analysts - with the information needed to apply basic AI algorithms to resolve actual problems encountered in a professional environment.
Introduction to Statistical Methods for Biosurveillance
Presents basic and advanced methods with a focus on demonstrated added value for a broad class of public health surveillance problems.
The Ethics of Biomedical Big Data
This book presents cutting edge research on the new ethical challenges posed by biomedical Big Data technologies and practices. ‘Biomedical Big Data’ refers to the analysis of aggregated, very large datasets to improve medical knowledge and clinical care. The book describes the ethical problems posed by aggregation of biomedical datasets and re-use/re-purposing of data, in areas such as privacy, consent, professionalism, power relationships, and ethical governance of Big Data platforms. Approaches and methods are discussed that can be used to address these problems to achieve the appropriate balance between the social goods of biomedical Big Data research and the safety and privacy of individuals. Seventeen original contributions analyse the ethical, social and related policy implications of the analysis and curation of biomedical Big Data, written by leading experts in the areas of biomedical research, medical and technology ethics, privacy, governance and data protection. The book advances our understanding of the ethical conundrums posed by biomedical Big Data, and shows how practitioners and policy-makers can address these issues going forward.
