4231.1 Statistical Monitoring of Water Quality Data for Population Health Surveillance

Tuesday, November 10, 2009: 12:30 PM
The US EPA has tested tools for the integration of public health data with water quality data. Behind this effort are Presidential Directives resulting from concerns over possible terrorist-motivated contamination of water distribution systems. Prototype contamination warning systems use geo-spatial and temporal analysis of water quality and human healthcare-seeking data from a variety of sources. Data from utilities include spatial characteristics of the distribution system as well as near real time water analysis or grab sample data. Examples of public health data resources include Poison Control Center calls and hospital emergency department data. Symptoms related to ingestion, inhalation, and dermal exposure to contaminated water have been evaluated. Patient record data filters have been derived from these categories for extraction and routine monitoring of relevant records. Pilot projects have demonstrated the feasibility and benefit of routine data sharing between the water sector and public health. Several statistical methods, such as Bayesian Networks, have been employed to synthesize results from disparate data types and operational responses. Alert responses from such tools can provide the user with a measure of likelihood of occurrence of a water-borne disease outbreak. These programs aim to foster communication, identify an event, analyze threat credibility through trigger validation, reduce response time, and mitigate community health effects while avoiding the economic burden of widespread disease.
Session Objectives: 1. Explain the public health threat of water-borne disease outbreaks and the role of the US EPA in monitoring this threat. 2. Describe approaches for the integration of public health surveillance data and water quality data for detection of a water-borne outbreak cause by a drinking water contamination incident. 3. Analyze the data streams comprising a water contamination warning system.

12:30 PM
An Accessible Approach for Fusion of Environmental and Human Health Data for Disease Surveillance
Howard S. Burkom, PhD, Liane Ramac-Thomas, Rekha Holtry and Steven Babin, MD, PhD
12:50 PM
Statistical Models and Water Quality Event Detection
Sean A. McKenna, PhD, David B. Hart, Mark W. Koch and Eric D. Vugrin

See individual abstracts for presenting author's disclosure statement and author's information.

Organized by: Statistics

CE Credits: Medical (CME), Health Education (CHES), Nursing (CNE), Public Health (CPH)

See more of: Statistics