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Books on the topic 'Data surveillance'

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Author: Grafiati
Published: 4 June 2021
Last updated: 31 January 2023

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1

Program, Hawaii Health Surveillance. 1986 survey data. Honolulu, Hawaii (P.O. Box 3378, Honolulu 96801-9990): Hawaii State Dept. of Health, Research and Statistics Office, Office of Health Monitoring, 1989.

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2

Flach, James Dominic. River basin surveillance using remotely sensed data. Birmingham: Aston University. Department of Civil Engineering, 1989.

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3

Wilson, Sue. Assessing the utility of cancer surveillance data. Birmingham: University of Birmingham, 1997.

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4

Canada, Public Health Agency of. Inventory of injury data sources and surveillance activities. Ottawa, Ont: Public Health Agency of Canada, 2005.

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5

Xinyu, Wu, Xu Yangsheng, and SpringerLink (Online service), eds. Intelligent Surveillance Systems. Dordrecht: Springer Science+Business Media B.V., 2011.

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6

Levin, Robert E. Space Surveillance Network: Appropriate controls needed over data access. Washington, D.C: United States General Accounting Office., 2002.

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7

Fraser, Graham, and Gianfranco Spiteri. Annual epidemiological report reporting on 2009 surveillance data and 2010 epidemic intelligence data. Stockholm: European Centre for Disease Prevention and Control, 2011.

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8

Mathisen, Johan. Using the balance sheet approach in surveillance: Framework, data sources, and data availability. [Washington, D.C.]: International Monetary Fund, Policy Development and Review Dept. and Statistics Dept, 2006.

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9

Unit, Great Britain Consumer Safety. Home accident surveillance system: Ninth annual report - 1985 data. London: The Unit, 1986.

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10

Basile, Kathleen C. Sexual violence surveillance: Uniform definitions and recommended data elements. Atlanta, Ga: Centers for Disase Control and Prevention, National Center for Injury Prevention and Control, 2009.

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11

Great Britain. Department of Trade and Industry. Consumer Safety Unit. Home accident surveillance system: Tenth annual report : 1986 data. London: Consumer Safety Unit, Department of Trade and Industry, 1987.

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12

Basile, Kathleen C. Sexual violence surveillance: Uniform definitions and recommended data elements. Atlanta, Ga: Centers for Disase Control and Prevention, National Center for Injury Prevention and Control, 2009.

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13

Basile, Kathleen C. Sexual violence surveillance: Uniform definitions and recommended data elements. Atlanta, Ga: Centers for Disase Control and Prevention, National Center for Injury Prevention and Control, 2009.

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14

Basile, Kathleen C. Sexual violence surveillance: Uniform definitions and recommended data elements. Atlanta, Ga: Centers for Disase Control and Prevention, National Center for Injury Prevention and Control, 2009.

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15

Jennings, Kirk E. Design guidelines for a rule-based passive surveillance system. Monterey, Calif: Naval Postgraduate School, 1986.

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16

Programme, Malawi AIDS Control. Estimating national HIV prevalence in Malawi from sentinel surveillance data. Lilongwe: National AIDS Control Programme, 1999.

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17

Services, Nevada Bureau of Family Health. An analysis of the injury surveillance data system in Nevada. Harrisburg, Pa: Research Applications, 2003.

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18

1965-, Foresti Gian Luca, Regazzoni Carlo S, and Varshney Pramod K, eds. Multisensor surveillance systems: The fusion perspective. Boston: Kluwer Academic, 2003.

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19

Simon, Chong, and Nevada. Bureau of Family Health Services., eds. Nevada's injury data surveillance project. [Nevada]: Nevada Bureau of Family Health Services, 2002.

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20

Yan, Wei Qi. Introduction to Intelligent Surveillance: Surveillance Data Capture, Transmission, and Analytics. Springer, 2017.

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21

Yan, Wei Qi. Introduction to Intelligent Surveillance: Surveillance Data Capture, Transmission, and Analytics. Springer, 2018.

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22

Yan, Wei Qi. Introduction to Intelligent Surveillance: Surveillance Data Capture, Transmission, and Analytics. Springer, 2019.

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23

Patsy, Myers, and South Carolina. Dept. of Health and Environmental Control., eds. South Carolina perinatal regionalization surveillance data. [Columbia, S.C.]: South Carolina Dept. of Health and Environmental Control, 2001.

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24

Boersma, Kees, and Chiara Fonio. Big Data, Surveillance and Crisis Management. Taylor & Francis Group, 2017.

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25

Big Data, Surveillance and Crisis Management. Taylor & Francis Group, 2017.

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26

Boersma, Kees, and Chiara Fonio. Big Data, Surveillance and Crisis Management. Taylor & Francis Group, 2017.

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27

Organizing and analyzing surveillance data: Module 1. [Atlanta, Ga.?]: U.S. Dept. of Health and Human Services, Public Health Service, Centers for Disease Control, 1988.

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28

Hu, Margaret. Pandemic Surveillance: Privacy, Security, and Data Ethics. Elgar Publishing Limited, Edward, 2022.

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29

Improving data quality in pesticide illness surveillance. [Olympia, Wash.]: State of Washington Dept. of Health, 2004.

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30

Sanders, Rebecca. Surveillance. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780190870553.003.0005.

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This chapter explores shifting patterns of intelligence surveillance in the United States. The Fourth Amendment protects Americans from unreasonable search and seizure without a warrant, but foreign spying is subject to few constraints. During the Cold War, surveillance power was abused for political purposes. Operating in a culture of secrecy, American intelligence agencies engaged in extensive illegal domestic spying. The intelligence scandals of the 1970s revealed these abuses, prompting new laws, notably the Foreign Intelligence Surveillance Act. Fearing further recrimination, the national security establishment increasingly demanded legal cover. After 9/11, Congress expanded lawful surveillance powers with the PATRIOT Act. Meanwhile, the Bush administration directed the National Security Agency to conduct warrantless domestic wiretapping. To justify this program, officials sought to redefine unconstrained foreign surveillance to subsume previously protected communications. The Obama administration continued to authorize mass surveillance and data mining programs and legally rationalize bulk collection of Americans’ data.
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31

EventDriven Surveillance Springerbriefs in Computer Science. Springer, 2012.

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32

World Health Organization (WHO). Understanding and Using Tuberculosis Data. World Health Organization, 2014.

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33

Maryland. Local and Family Health Administration., ed. Surveillance data book 1990: Health indicators in Maryland. [Baltimore]: Local and Family Health Administration, Maryland Dept. of Health and Mental Hygiene, 1990.

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34

Fund, International Monetary. Data Provision to the Fund for Surveillance Purposes. International Monetary Fund, 2002.

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35

Company, Teaching, ed. The surveillance state: Big data, freedom, and you. The Teaching Company, 2016.

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36

Fund, International Monetary. Data Provision to the Fund for Surveillance Purposes. International Monetary Fund, 2002.

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37

Fund, International Monetary. Data Provision to the Fund for Surveillance Purposes. International Monetary Fund, 2002.

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38

Monahan, Torin, and David Murakami Wood. Surveillance Studies: A Reader. Oxford University Press, Incorporated, 2018.

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39

Surveillance Studies: A Reader. Oxford University Press, Incorporated, 2018.

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40

Surveillance Technologies And Early Warning Systems Data Mining Applications For Risk Detection. Information Science Publishing, 2010.

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41

Lyon, David. Surveillance Studies: An Overview. Polity Press, 2007.

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42

Surveillance Studies: An Overview. Polity Press, 2007.

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43

Lyon, David. Surveillance Studies: An Overview. Polity Press, 2007.

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44

Xu, Yangsheng, Xinyu Wu, and Huihuan Qian. Intelligent Surveillance Systems. Springer, 2013.

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45

National Center for Chronic Disease Prevention and Health Promotion (U.S.). Division of Chronic Disease Control and Community Intervention. and Centers for Disease Control and Prevention (U.S.), eds. Cardiovascular disease surveillance: Stroke, 1980-1989. Atlanta, Ga: U.S. DHHS, PHS, Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, 1994.

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46

Vivancos, Roberto, Giovanni Leonardi, and Alex J. Elliott. Health protection surveillance. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780198745471.003.0021.

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This chapter provides a broad definition of surveillance in relation to health protection, including infections, environmental hazards, and health delivery. Surveillance systems include active, passive, and sentinel surveillance, and guidelines are provided for assessing the quality of surveillance data. Surveillance tools include the statutory notification of diseases, laboratory reporting, and prevalence surveys. In addition, syndromic surveillance, the (near) real-time collection of data has become increasingly used, facilitated by increasing use of digital data collection within health care settings and the availability of other digital data sources (e.g. social media). Other surveillance types include event-based surveillance (e.g. during major sporting events), and environmental surveillance, including food related disease, air pollution and chemical hazards. The chapter finally brings these together in integrated surveillance and the use of such surveillance in health planning and assessment.
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47

Pellechio, Anthony J., and Johan Mathisen. Using the Balance Sheet Approach in Surveillance: Framework, Data Sources, and Data Availability. International Monetary Fund, 2006.

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48

Pellechio, Anthony J., and Johan Mathisen. Using the Balance Sheet Approach in Surveillance: Framework, Data Sources, and Data Availability. International Monetary Fund, 2006.

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49

Pellechio, Anthony J., and Johan Mathisen. Using the Balance Sheet Approach in Surveillance: Framework, Data Sources, and Data Availability. International Monetary Fund, 2006.

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50

Farivar, Cyrus. Habeas Data: Privacy vs. the Rise of Surveillance Tech. Melville House, 2019.

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