Download or read book Data Science for Infectious Disease Data Analytics written by Lily Wang and published by CRC Press. This book was released on 2022-12-05 with total page 424 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Science for Infectious Disease Data Analytics: An Introduction with R provides an overview of modern data science tools and methods that have been developed specifically to analyze infectious disease data. With a quick start guide to epidemiological data visualization and analysis in R, this book spans the gulf between academia and practices providing many lively, instructive data analysis examples using the most up-to-date data, such as the newly discovered coronavirus disease (COVID-19). The primary emphasis of this book is the data science procedures in epidemiological studies, including data wrangling, visualization, interpretation, predictive modeling, and inference, which is of immense importance due to increasingly diverse and nonexperimental data across a wide range of fields. The knowledge and skills readers gain from this book are also transferable to other areas, such as public health, business analytics, environmental studies, or spatio-temporal data visualization and analysis in general. Aimed at readers with an undergraduate knowledge of mathematics and statistics, this book is an ideal introduction to the development and implementation of data science in epidemiology. Features Describes the entire data science procedure of how the infectious disease data are collected, curated, visualized, and fed to predictive models, which facilitates effective communication between data sources, scientists, and decision-makers. Explains practical concepts of infectious disease data and provides particular data science perspectives. Overview of the unique features and issues of infectious disease data and how they impact epidemic modeling and projection. Introduces various classes of models and state-of-the-art learning methods to analyze infectious diseases data with valuable insights on how different models and methods could be connected.

Download or read book Big Data and Analytics for Infectious Disease Research Operations and Policy written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2016-12-30 with total page 99 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the amount of data in the world exploding, big data could generate significant value in the field of infectious disease. The increased use of social media provides an opportunity to improve public health surveillance systems and to develop predictive models. Advances in machine learning and crowdsourcing may also offer the possibility to gather information about disease dynamics, such as contact patterns and the impact of the social environment. New, rapid, point-of-care diagnostics may make it possible to capture not only diagnostic information but also other potentially epidemiologically relevant information in real time. With a wide range of data available for analysis, decision-making and policy-making processes could be improved. While there are many opportunities for big data to be used for infectious disease research, operations, and policy, many challenges remain before it is possible to capture the full potential of big data. In order to explore some of the opportunities and issues associated with the scientific, policy, and operational aspects of big data in relation to microbial threats and public health, the National Academies of Sciences, Engineering, and Medicine convened a workshop in May 2016. Participants discussed a range of topics including preventing, detecting, and responding to infectious disease threats using big data and related analytics; varieties of data (including demographic, geospatial, behavioral, syndromic, and laboratory) and their broader applications; means to improve their collection, processing, utility, and validation; and approaches that can be learned from other sectors to inform big data strategies for infectious disease research, operations, and policy. This publication summarizes the presentations and discussions from the workshop.

Download or read book Data Science for Infectious Disease Data Analytics written by Lily Wang and published by CRC Press. This book was released on 2022-12-05 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Science for Infectious Disease Data Analytics: An Introduction with R provides an overview of modern data science tools and methods that have been developed specifically to analyze infectious disease data. With a quick start guide to epidemiological data visualization and analysis in R, this book spans the gulf between academia and practices providing many lively, instructive data analysis examples using the most up-to-date data, such as the newly discovered coronavirus disease (COVID-19). The primary emphasis of this book is the data science procedures in epidemiological studies, including data wrangling, visualization, interpretation, predictive modeling, and inference, which is of immense importance due to increasingly diverse and nonexperimental data across a wide range of fields. The knowledge and skills readers gain from this book are also transferable to other areas, such as public health, business analytics, environmental studies, or spatio-temporal data visualization and analysis in general. Aimed at readers with an undergraduate knowledge of mathematics and statistics, this book is an ideal introduction to the development and implementation of data science in epidemiology. Features Describes the entire data science procedure of how the infectious disease data are collected, curated, visualized, and fed to predictive models, which facilitates effective communication between data sources, scientists, and decision-makers. Explains practical concepts of infectious disease data and provides particular data science perspectives. Overview of the unique features and issues of infectious disease data and how they impact epidemic modeling and projection. Introduces various classes of models and state-of-the-art learning methods to analyze infectious diseases data with valuable insights on how different models and methods could be connected.

Download or read book Handbook of Infectious Disease Data Analysis written by Leonhard Held and published by CRC Press. This book was released on 2019-11-07 with total page 472 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent years have seen an explosion in new kinds of data on infectious diseases, including data on social contacts, whole genome sequences of pathogens, biomarkers for susceptibility to infection, serological panel data, and surveillance data. The Handbook of Infectious Disease Data Analysis provides an overview of many key statistical methods that have been developed in response to such new data streams and the associated ability to address key scientific and epidemiological questions. A unique feature of the Handbook is the wide range of topics covered. Key features Contributors include many leading researchers in the field Divided into four main sections: Basic concepts, Analysis of Outbreak Data, Analysis of Seroprevalence Data, Analysis of Surveillance Data Numerous case studies and examples throughout Provides both introductory material and key reference material

Download or read book Charting the Next Pandemic written by Ana Pastore y Piontti and published by Springer. This book was released on 2018-11-07 with total page 221 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an introduction to the computational and complex systems modeling of the global spreading of infectious diseases. The latest developments in the area of contagion processes modeling are discussed, and readers are exposed to real world examples of data-model integration impacting the decision-making process. Recent advances in computational science and the increasing availability of real-world data are making it possible to develop realistic scenarios and real-time forecasts of the global spreading of emerging health threats. The first part of the book guides the reader through sophisticated complex systems modeling techniques with a non-technical and visual approach, explaining and illustrating the construction of the modern framework used to project the spread of pandemics and epidemics. Models can be used to transform data to knowledge that is intuitively communicated by powerful infographics and for this reason, the second part of the book focuses on a set of charts that illustrate possible scenarios of future pandemics. The visual atlas contained allows the reader to identify commonalities and patterns in emerging health threats, as well as explore the wide range of models and data that can be used by policy makers to anticipate trends, evaluate risks and eventually manage future events. Charting the Next Pandemic puts the reader in the position to explore different pandemic scenarios and to understand the potential impact of available containment and prevention strategies. This book emphasizes the importance of a global perspective in the assessment of emerging health threats and captures the possible evolution of the next pandemic, while at the same time providing the intelligence needed to fight it. The text will appeal to a wide range of audiences with diverse technical backgrounds.

Download or read book Leveraging Data Science for Global Health written by Leo Anthony Celi and published by Springer Nature. This book was released on 2020-07-31 with total page 471 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book explores ways to leverage information technology and machine learning to combat disease and promote health, especially in resource-constrained settings. It focuses on digital disease surveillance through the application of machine learning to non-traditional data sources. Developing countries are uniquely prone to large-scale emerging infectious disease outbreaks due to disruption of ecosystems, civil unrest, and poor healthcare infrastructure – and without comprehensive surveillance, delays in outbreak identification, resource deployment, and case management can be catastrophic. In combination with context-informed analytics, students will learn how non-traditional digital disease data sources – including news media, social media, Google Trends, and Google Street View – can fill critical knowledge gaps and help inform on-the-ground decision-making when formal surveillance systems are insufficient.

Download or read book Analysis of Infectious Disease Data written by N.G. Becker and published by CRC Press. This book was released on 2017-11-22 with total page 234 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book gives an up-to-date account of various approaches availablefor the analysis of infectious disease data. Most of the methods havebeen developed only recently, and for those based on particularlymodern mathematics, details of the computation are carefullyillustrated. Interpretation is discussed at some length and the emphasisthroughout is on making statistical inferences about epidemiologicallyimportant parameters.Niels G. Becker is Reader in Statistics at La Trobe University,Australia.

Download or read book Handbook of Research on Disease Prediction Through Data Analytics and Machine Learning written by Rani, Geeta and published by IGI Global. This book was released on 2020-10-16 with total page 586 pages. Available in PDF, EPUB and Kindle. Book excerpt: By applying data analytics techniques and machine learning algorithms to predict disease, medical practitioners can more accurately diagnose and treat patients. However, researchers face problems in identifying suitable algorithms for pre-processing, transformations, and the integration of clinical data in a single module, as well as seeking different ways to build and evaluate models. The Handbook of Research on Disease Prediction Through Data Analytics and Machine Learning is a pivotal reference source that explores the application of algorithms to making disease predictions through the identification of symptoms and information retrieval from images such as MRIs, ECGs, EEGs, etc. Highlighting a wide range of topics including clinical decision support systems, biomedical image analysis, and prediction models, this book is ideally designed for clinicians, physicians, programmers, computer engineers, IT specialists, data analysts, hospital administrators, researchers, academicians, and graduate and post-graduate students.

Download or read book Big Data Analytics in HIV AIDS Research written by Al Mazari, Ali and published by IGI Global. This book was released on 2018-04-27 with total page 323 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the advent of new technologies in big data science, the study of medical problems has made significant progress. Connecting medical studies and computational methods is crucial for the advancement of the medical industry. Big Data Analytics in HIV/AIDS Research provides emerging research on the development and implementation of computational techniques in big data analysis for biological and medical practices. While highlighting topics such as deep learning, management software, and molecular modeling, this publication explores the various applications of data analysis in clinical decision making. This book is a vital resource for medical practitioners, nurses, scientists, researchers, and students seeking current research on the connections between data analytics in the field of medicine.

Download or read book Data Analytics for Pandemics written by Gitanjali Rahul Shinde and published by CRC Press. This book was released on 2020-08-30 with total page 85 pages. Available in PDF, EPUB and Kindle. Book excerpt: Epidemic trend analysis, timeline progression, prediction, and recommendation are critical for initiating effective public health control strategies, and AI and data analytics play an important role in epidemiology, diagnostic, and clinical fronts. The focus of this book is data analytics for COVID-19, which includes an overview of COVID-19 in terms of epidemic/pandemic, data processing and knowledge extraction. Data sources, storage and platforms are discussed along with discussions on data models, their performance, different big data techniques, tools and technologies. This book also addresses the challenges in applying analytics to pandemic scenarios, case studies and control strategies. Aimed at Data Analysts, Epidemiologists and associated researchers, this book: discusses challenges of AI model for big data analytics in pandemic scenarios; explains how different big data analytics techniques can be implemented; provides a set of recommendations to minimize infection rate of COVID-19; summarizes various techniques of data processing and knowledge extraction; enables users to understand big data analytics techniques required for prediction purposes.

Download or read book Modeling Infectious Disease Parameters Based on Serological and Social Contact Data written by Niel Hens and published by Springer Science & Business Media. This book was released on 2012-10-24 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mathematical epidemiology of infectious diseases usually involves describing the flow of individuals between mutually exclusive infection states. One of the key parameters describing the transition from the susceptible to the infected class is the hazard of infection, often referred to as the force of infection. The force of infection reflects the degree of contact with potential for transmission between infected and susceptible individuals. The mathematical relation between the force of infection and effective contact patterns is generally assumed to be subjected to the mass action principle, which yields the necessary information to estimate the basic reproduction number, another key parameter in infectious disease epidemiology. It is within this context that the Center for Statistics (CenStat, I-Biostat, Hasselt University) and the Centre for the Evaluation of Vaccination and the Centre for Health Economic Research and Modelling Infectious Diseases (CEV, CHERMID, Vaccine and Infectious Disease Institute, University of Antwerp) have collaborated over the past 15 years. This book demonstrates the past and current research activities of these institutes and can be considered to be a milestone in this collaboration. This book is focused on the application of modern statistical methods and models to estimate infectious disease parameters. We want to provide the readers with software guidance, such as R packages, and with data, as far as they can be made publicly available.

Download or read book Infectious Disease Informatics written by Hsinchun Chen and published by Springer Science & Business Media. This book was released on 2010-03-12 with total page 210 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computer-based infectious disease surveillance systems are capable of real-time or near real-time detection of serious illnesses and potential bioterrorism agent exposures and represent a major step forward in disease surveillance. Infectious Disease Informatics: Syndromic Surveillance for Public Health and Bio-Defense is an in-depth monograph that analyzes and evaluates the outbreak modeling and detection capabilities of existing surveillance systems under a unified framework, and presents the first book-length coverage of the subject from an informatics-driven perspective. Individual chapters consider the state of the art, including the facilitation of data collection, sharing and transmission; a focus on various outbreak detection methods; data visualization and information dissemination issues; and system assessment and other policy issues. Eight chapters then report on several real-world case studies, summarizing and comparing eight syndromic surveillance systems, including those that have been adopted by many public health agencies (e.g., RODS and BioSense). The book concludes with a discussion of critical issues and challenges, with a look to future directions. This book is an excellent source of current information for researchers in public health and IT. Government public health officials and private-sector practitioners in both public health and IT will find the most up-to-date information available, and students from a variety of disciplines, including public health, biostatistics, information systems, computer science, and public administration and policy will get a comprehensive look at the concepts, techniques, and practices of syndromic surveillance.

Download or read book Analysis of Infectious Disease Data written by N.G. (La Trobe University) Becker and published by Chapman & Hall/CRC Monographs on Statistics and Applied Probability. This book was released on 2019-12-03 with total page 234 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book gives an up-to-date account of various approaches availablefor the analysis of infectious disease data. Most of the methods havebeen developed only recently, and for those based on particularlymodern mathematics, details of the computation are carefullyillustrated. Interpretation is discussed at some length and the emphasisthroughout is on making statistical inferences about epidemiologicallyimportant parameters.Niels G. Becker is Reader in Statistics at La Trobe University, Australia

Download or read book Leveraging Data Science for Global Health written by Leo Anthony Celi and published by Springer. This book was released on 2020-09-18 with total page 475 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book explores ways to leverage information technology and machine learning to combat disease and promote health, especially in resource-constrained settings. It focuses on digital disease surveillance through the application of machine learning to non-traditional data sources. Developing countries are uniquely prone to large-scale emerging infectious disease outbreaks due to disruption of ecosystems, civil unrest, and poor healthcare infrastructure – and without comprehensive surveillance, delays in outbreak identification, resource deployment, and case management can be catastrophic. In combination with context-informed analytics, students will learn how non-traditional digital disease data sources – including news media, social media, Google Trends, and Google Street View – can fill critical knowledge gaps and help inform on-the-ground decision-making when formal surveillance systems are insufficient.

Download or read book Global Infectious Disease Surveillance and Detection written by Institute of Medicine and published by National Academies Press. This book was released on 2007-11-11 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt: Early detection is essential to the control of emerging, reemerging, and novel infectious diseases, whether naturally occurring or intentionally introduced. Containing the spread of such diseases in a profoundly interconnected world requires active vigilance for signs of an outbreak, rapid recognition of its presence, and diagnosis of its microbial cause, in addition to strategies and resources for an appropriate and efficient response. Although these actions are often viewed in terms of human public health, they also challenge the plant and animal health communities. Surveillance, defined as "the continual scrutiny of all aspects of occurrence and spread of a disease that are pertinent to effective control", involves the "systematic collection, analysis, interpretation, and dissemination of health data." Disease detection and diagnosis is the act of discovering a novel, emerging, or reemerging disease or disease event and identifying its cause. Diagnosis is "the cornerstone of effective disease control and prevention efforts, including surveillance." Disease surveillance and detection relies heavily on the astute individual: the clinician, veterinarian, plant pathologist, farmer, livestock manager, or agricultural extension agent who notices something unusual, atypical, or suspicious and brings this discovery in a timely way to the attention of an appropriate representative of human public health, veterinary medicine, or agriculture. Most developed countries have the ability to detect and diagnose human, animal, and plant diseases. Global Infectious Disease Surveillance and Detection: Assessing the Challenges-Finding Solutions, Workshop Summary is part of a 10 book series and summarizes the recommendations and presentations of the workshop.

Download or read book Introduction to Data Science written by Rafael A. Irizarry and published by CRC Press. This book was released on 2019-11-20 with total page 794 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction to Data Science: Data Analysis and Prediction Algorithms with R introduces concepts and skills that can help you tackle real-world data analysis challenges. It covers concepts from probability, statistical inference, linear regression, and machine learning. It also helps you develop skills such as R programming, data wrangling, data visualization, predictive algorithm building, file organization with UNIX/Linux shell, version control with Git and GitHub, and reproducible document preparation. This book is a textbook for a first course in data science. No previous knowledge of R is necessary, although some experience with programming may be helpful. The book is divided into six parts: R, data visualization, statistics with R, data wrangling, machine learning, and productivity tools. Each part has several chapters meant to be presented as one lecture. The author uses motivating case studies that realistically mimic a data scientist’s experience. He starts by asking specific questions and answers these through data analysis so concepts are learned as a means to answering the questions. Examples of the case studies included are: US murder rates by state, self-reported student heights, trends in world health and economics, the impact of vaccines on infectious disease rates, the financial crisis of 2007-2008, election forecasting, building a baseball team, image processing of hand-written digits, and movie recommendation systems. The statistical concepts used to answer the case study questions are only briefly introduced, so complementing with a probability and statistics textbook is highly recommended for in-depth understanding of these concepts. If you read and understand the chapters and complete the exercises, you will be prepared to learn the more advanced concepts and skills needed to become an expert.

Download or read book Infectious Disease Surveillance written by Nkuchia M. M'ikanatha and published by John Wiley & Sons. This book was released on 2013-03-11 with total page 1139 pages. Available in PDF, EPUB and Kindle. Book excerpt: This fully updated edition of Infectious Disease Surveillance is for frontline public health practitioners, epidemiologists, and clinical microbiologists who are engaged in communicable disease control. It is also a foundational text for trainees in public health, applied epidemiology, postgraduate medicine and nursing programs. The second edition portrays both the conceptual framework and practical aspects of infectious disease surveillance. It is a comprehensive resource designed to improve the tracking of infectious diseases and to serve as a starting point in the development of new surveillance systems. Infectious Disease Surveillance includes over 45 chapters from over 100 contributors, and topics organized into six sections based on major themes. Section One highlights the critical role surveillance plays in public health and it provides an overview of the current International Health Regulations (2005) in addition to successes and challenges in infectious disease eradication. Section Two describes surveillance systems based on logical program areas such as foodborne illnesses, vector-borne diseases, sexually transmitted diseases, viral hepatitis healthcare and transplantation associated infections. Attention is devoted to programs for monitoring unexplained deaths, agents of bioterrorism, mass gatherings, and disease associated with international travel. Sections Three and Four explore the uses of the Internet and wireless technologies to advance infectious disease surveillance in various settings with emphasis on best practices based on deployed systems. They also address molecular laboratory methods, and statistical and geospatial analysis, and evaluation of systems for early epidemic detection. Sections Five and Six discuss legal and ethical considerations, communication strategies and applied epidemiology-training programs. The rest of the chapters offer public-private partnerships, as well lessons from the 2009-2010 H1N1 influenza pandemic and future directions for infectious disease surveillance.