1.

Record Nr.

UNINA9910143721203321

Titolo

Disease surveillance [[electronic resource] ] : a public health informatics approach / / edited by Joseph S. Lombardo, David L. Buckeridge

Pubbl/distr/stampa

Hoboken, N.J., : Wiley-Interscience, c2007

ISBN

1-118-56905-9

1-280-85517-7

9786610855179

0-470-13188-8

0-470-13187-X

Descrizione fisica

1 online resource (484 p.)

Altri autori (Persone)

LombardoJoseph S. <1946->

BuckeridgeDavid Llewellyn <1970->

Disciplina

362.1

614.4072

Soggetti

Public health surveillance

Medical informatics

Electronic books.

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Description based upon print version of record.

Nota di bibliografia

Includes bibliographical references and index.

Nota di contenuto

DISEASE SURVEILLANCE : A Public Health Informatics Approach; Contents; Contributors; Preface; Acknowledgments; 1 Disease Surveillance, a Public Health Priority; 1.1 Introduction; 1.2 The Emerging Role of Informatics in Public Health Practice; 1.3 Early Use of Technology for Public Health Practice; 1.3.1 Early Use of Analytics, Visualization, and Communications; 1.3.2 Early Informatics Applications in Medicine & Public Health; 1.3.3 Public Health Records Archiving; 1.4 Guiding Principles for Development of Public Health Applications

1 .5 Information Requirements for Automated Disease Surveillance1.6 Historical Impact of Infectious Disease Outbreaks; 1.6.1 Smallpox; 1.6.2 Plague; 1.6.3 Spanish Influenza, 1918; 1.6.4 Influenza Pandemics after 1918; 1.7 Disease as a Weapon; 1.7.1 Bioterrorism; 1.8 Modern Disease Surveillance Applications; 1.8.1 Components of an Early Recognition Disease Surveillance System; 1.8.2 Modern Surveillance



Applications for Use by State and Local Health Departments; 1.8.3 National Disease Surveillance Initiatives; 1.9 Summary; References; Part I: System Design and Implementation

2 Understanding the Data: Health Indicators in Disease Surveillance2.1 Data Source Concepts; 2.2 Data from Pharmacy Chains; 2.3 Data from EMS and 911; 2.4 Data from Telephone Triage Hotlines; 2.5 Data from School Absenteeism and School Nurses; 2.6 Data from Hospital Visits; 2.7 Data from Physicians' Office Visits; 2.8 Laboratories Role in pre-diagnostic Surveillance; 2.9 Other Health Indicator Data; 2.9.1 Environmental Data; 2.9.2 Animal Health Data; 2.10 Data Source Evaluation; 2.10.1 Approach and Methodology; 2.10.2 Example: Wildfires (October 2003)

2.10.3 Example: Influenza Outbreak (December 2003)2.10.4 Example: Gastrointestinal Illness (January-February 2004); 2.10.5 Conclusions; 2.11 Study Questions; References; 3 Obtaining the Data; 3.1 Introduction to Data Collection and Archiving; 3.1.1 The Internet: Universal Connectivity; 3.1.2 Databases: Flexible Data Storage; 3.1.3 Summary; 3.2 Obtaining Access to Surveillance Data; 3.2.1 Sharing Health Indicator Data; 3.2.2 Data-Sharing Issues; 3.2.3 HIPAA and Disease Surveillance; 3.2.4 Summary of Data Sharing; 3.3 The Role of Standards in Data Exchange; 3.3.1 Types of Standards

3.3.2 Standards Development3.3.3 Standards for Health Indicator Data in Biosurveillence; 3.3.4 National Health Information Systems - Implementing Standards; 3.4 Establishing the Data Feeds; 3.4.1 Information Systems of the Data Provider or Source; 3.4.2 Setting Up the Data Feed; 3.4.3 Data Characteristics; 3.4.4 Data Fields or Elements; 3.4.5 Data Transfer Format; 3.4.6 Data Transfer Protocol; 3.4.7 Security Considerations; 3.4.8 Data Import Methods; 3.4.9 Data Cleaning; 3.4.10 Data Quality; 3.4.11 Summary; 3.5 Study Questions; References; 4 Alerting Algorithms for Biosurveillance

4.1 Statistical Alerting Algorithms

Sommario/riassunto

An up-to-date and comprehensive treatment of biosurveillance techniques With the worldwide awareness of bioterrorism and drug-resistant infectious diseases, the need for surveillance systems to accurately detect emerging epidemicsis essential for maintaining global safety. Responding to these issues, Disease Surveillance brings together fifteen eminent researchers in the fields of medicine, epidemiology, biostatistics, and medical informatics to define the necessary elements of an effective disease surveillance program, including research, development, implementation, and operations. The sur



2.

Record Nr.

UNINA9910796535803321

Autore

Manish Kumar

Titolo

Building data streaming applications with Apache Kafka : designing and deploying enterprise messaging queues / / Manish Kumar, Chanchal Singh

Pubbl/distr/stampa

Birmingham : , : Packt, , 2017

Edizione

[1st edition]

Descrizione fisica

1 online resource (269 pages) : color illustrations

Disciplina

006.8

Soggetti

Information storage and retrieval systems

Telecommunication - Message processing

Web sites - Design

Agile software development

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Includes index.

Sommario/riassunto

Design and administer fast, reliable enterprise messaging systems with Apache Kafka About This Book Build efficient real-time streaming applications in Apache Kafka to process data streams of data Master the core Kafka APIs to set up Apache Kafka clusters and start writing message producers and consumers A comprehensive guide to help you get a solid grasp of the Apache Kafka concepts in Apache Kafka with pracitcalpractical examples Who This Book Is For If you want to learn how to use Apache Kafka and the different tools in the Kafka ecosystem in the easiest possible manner, this book is for you. Some programming experience with Java is required to get the most out of this book What You Will Learn Learn the basics of Apache Kafka from scratch Use the basic building blocks of a streaming application Design effective streaming applications with Kafka using Spark, Storm &, and Heron Understand the importance of a low -latency , high- throughput, and fault-tolerant messaging system Make effective capacity planning while deploying your Kafka Application Understand and implement the best security practices In Detail Apache Kafka is a popular distributed streaming platform that acts as a messaging queue or an enterprise



messaging system. It lets you publish and subscribe to a stream of records, and process them in a fault-tolerant way as they occur. This book is a comprehensive guide to designing and architecting enterprise-grade streaming applications using Apache Kafka and other big data tools. It includes best practices for building such applications, and tackles some common challenges such as how to use Kafka efficiently and handle high data volumes with ease. This book first takes you through understanding the type messaging system and then provides a thorough introduction to Apache Kafka and its internal details. The second part of the book takes you through designing streaming application using various frameworks and tools such as Apache Spark, Apache Storm, and more. Once you grasp the basics, we will take you through more advanced concepts in Apache Kafka such as capacity planning and security. By the end of this book, you will have all the information you need to be comfortable with using Apache Kafka, and to design efficient streaming data applications with it. Style and approach A step-by –step, comprehensive guide filled with practical and real- world examples Downloading the example code for this book. You can download the example code f...