Thompson Michael

Although rare in the US, the CDC reports 13-14 drinking-water-related disease outbreaks per year, affecting an average of about 1000 people. The US EPA has determined that the distribution system is the most vulnerable component of a drinking water system. Recognizing this vulnerability, water utilities are increasingly measuring disinfectant levels and other parameters in their distribution systems. The US EPA is sponsoring an initiative to fuse this distribution system water quality data with health data to improve surveillance by providing an assessment of the likelihood of the occurrence of a waterborne disease outbreak. This fused analysis capability will be available via a prototype water security module within a population-based public health syndromic surveillance system.

Objective

The objective of this paper is to illustrate a technique for combining water quality and population-based health data to monitor for water-borne disease outbreaks.

The purpose of this study is to investigate the use of electronic medical record (EMR) data sources to improve the detection performance of a syndromic surveillance system. This analysis involves examining the temporal correlation between alerts generated from the EMR data sources and alerts generated from the more traditional data sources already being used by the surveillance system.

This abstract describes a suite of software utilities that have been developed for systematically evaluating the detection performance and robustness of univariate temporal alerting algorithms used in syndromic surveillance systems.