A framework for enhancing spatial and temporal granularity in report-based health surveillance systems
Open Access
- 12 January 2010
- journal article
- Published by Springer Science and Business Media LLC in BMC Medical Informatics and Decision Making
- Vol. 10 (1), 1
- https://doi.org/10.1186/1472-6947-10-1
Abstract
Current public concern over the spread of infectious diseases has underscored the importance of health surveillance systems for the speedy detection of disease outbreaks. Several international report-based monitoring systems have been developed, including GPHIN, Argus, HealthMap, and BioCaster. A vital feature of these report-based systems is the geo-temporal encoding of outbreak-related textual data. Until now, automated systems have tended to use an ad-hoc strategy for processing geo-temporal information, normally involving the detection of locations that match pre-determined criteria, and the use of document publication dates as a proxy for disease event dates. Although these strategies appear to be effective enough for reporting events at the country and province levels, they may be less effective at discovering geo-temporal information at more detailed levels of granularity. In order to improve the capabilities of current Web-based health surveillance systems, we introduce the design for a novel scheme called spatiotemporal zoning.This publication has 26 references indexed in Scilit:
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