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SBE 2020: Submission Detail
| ID Number: |
300 |
| Title: |
A Self-Organizing Ontology for Surveillance of Disease Outbreaks |
| Lead Author: |
Greene, Marjorie |
| Abstract: |
A vast amount of real-time information about infectious disease outbreaks is found in various forms of Internet-based data streams. However, there is concern that as this volume of information increases, social networking will give consumers an ability to quickly spread information on outbreaks which may be false, resulting in mass panic before health authorities have had an opportunity to verify reports. This paper proposes a research effort to address the flow and growth of disease surveillance using the Internet. It builds initially on an infrastructure developed by the International Society for Infectious Diseases and introduces a unique self-organizing ontology that can be used to increase the relevance of disease outbreak reports and to classify outbreaks as they evolve in real time. Techniques for understanding how to effectively exploit consumer behavior in disease surveillance are still at their initial stages and need to be generalized at the level of academic research. Further inquiry into this research area may eventually be applied to prevention of information overload in international surveillance systems, minimizing global health security threats. |
| PDF: |
Greene_Marjorie_300.pdf |
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