Paper
5 May 2010 Epidemiological monitoring for emerging infectious diseases
Author Affiliations +
Abstract
The Homeland Security News Wire has been reporting on new ways to fight epidemics using digital tools such as iPhone, social networks, Wikipedia, and other Internet sites. Instant two-way communication now gives consumers the ability to complement official reports on emerging infectious diseases from health authorities. However, there is increasing concern that these communications networks could open the door to mass panic from unreliable or false reports. There is thus an urgent need to ensure that epidemiological monitoring for emerging infectious diseases gives health authorities the capability to identify, analyze, and report disease outbreaks in as timely and efficient a manner as possible. One of the dilemmas in the global dissemination of information on infectious diseases is the possibility that information overload will create inefficiencies as the volume of Internet-based surveillance information increases. What is needed is a filtering mechanism that will retrieve relevant information for further analysis by epidemiologists, laboratories, and other health organizations so they are not overwhelmed with irrelevant information and will be able to respond quickly. This paper introduces a self-organizing ontology that could be used as a filtering mechanism to increase relevance and allow rapid analysis of disease outbreaks as they evolve in real time.
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Marjorie Greene "Epidemiological monitoring for emerging infectious diseases", Proc. SPIE 7666, Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense IX, 76661B (5 May 2010); https://doi.org/10.1117/12.849351
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Surveillance

Homeland security

Biological research

Information security

Social networks

Analytical research

Information fusion

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