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Waterborne

Description

The EPA Water Security initiative contamination warning system (CWS) detection strategy involves the use of multiple monitoring and surveillance components for timely detection of drinking water contamination in the distribution system. The public health surveillance (PHS) component of the contamination warning system involves the analysis of health-related data to identify disease events that may stem from drinking water contamination. Public health data include hospital admission reports, infectious disease surveillance, emergency medical service reports, 911 calls and poison control center (PCC) calls. Automated analysis of these data streams results in alerts, which are investigated by health department epidemiologists. A comprehensive operational strategy was developed to describe the processes and procedures involved in the the initial investigation and validation of a PHS alert. The operational strategy established specific roles and responsibilities, and detailed procedural flow descriptions. The procedural flow concluded with the determination of whether or not an alert generated from surveillance of public health data streams is indicative of a possible water contamination incident.

Objective

To develop standard operating procedures (SOPs) to identify or rule out possible water contamination as a cause for a syndromic surveillance alarm.

Submitted by teresa.hamby@d… on
Description

The Public Health Surveillance (PHS) component (one of five monitoring and surveillance components deployed in the Cincinnati drinking water contamination warning system) functions to detect public health incidents resulting from exposure to toxic chemicals that produce a rapid onset of symptoms. Within the PHS component, four data streams were monitored: 911 calls, Emergency Medical Services (EMS) logs, Local Poison Control Center call data, as well as Emergency Department data (via EpiCenter). The focus of this paper centers on the 911 and EMS surveillance tools. The 911 data is dependent on information provided by the caller and the information entered by the dispatcher. EMS data, on the other hand, is recorded by a medical professional, and although not provided as rapidly as 911 data, provides more detailed information. The data included in 911 and EMS alerts, when utilized together, can provide timely and beneficial information during investigation of a possible drinking water contamination incident.

 

Objective

This paper describes the design, application and use of 911 and EMS data in a drinking water contamination warning system.

Submitted by hparton on
Description

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.

Submitted by elamb on
Description

Space-time scan statistics are often used to identify emerging spatial clusters of disease cases [1,2]. They operate by maximizing a score function (likelihood ratio statistic) over multiple spatio-temporal regions. The temporal component is typically incorporated by aggregating counts across a given time window, thus assuming that the affected region does not change over time. To relax this hard constraint on spatial-temporal “shape” and increase detection power and accuracy when tracking spreading outbreaks, we implement a new graph-based event detection approach which enables identification of dynamic clusters while enforcing temporal consistency constraints between temporally-adjacent spatial regions.

Objective:

We describe a novel graph-based event detection approach which can accurately identify and track dynamic outbreaks (where the affected region changes over time). Our approach enforces soft constraints on temporal consistency, allowing detected regions to grow, shrink, or move while penalizing implausible region dynamics. Using simulated contaminant plumes diffusing through a water distribution system, we demonstrate that our method improves both detection time and spatial-temporal accuracy when tracking dynamic waterborne outbreaks.

 

Submitted by Magou on
Description

The United States Environmental Protection Agency (U.S. EPA) has developed a prototype contamination warning system (CWS) for drinking water in response to Homeland Security Presidential Directive 9 (HSPD9). The goal of HSPD9 and the CWS is to expedite contamination containment and emergency response, thereby minimizing public health and economic impacts.

U.S. EPA’s conceptual CWS system, named WaterSentinel, is currently being pilot tested by U.S. EPA and its research partners. WaterSentinel is a multi-faceted approach involving water quality monitoring at optimal locations throughout the drinking water distribution system, enhanced security monitoring at key water utility infrastructure assets, consumer complaint surveillance, and innovative uses of public health surveillance data streams.

 

Objective

This paper summarizes the use and evaluation of various types of public health surveillance data for the early detection of chemical and biological contamination of drinking water.

Submitted by elamb on
Description

Safe drinking water is essential for all communities. Intentional or unintentional contamination of drinking water requires water utilities and local public health to act quickly. The Water Security (WS) initiative of the U.S. Environmental Protection Agency is a multi-faceted approach involving water utilities and local public health officials (LPH) to identify, communicate, contain, and mitigate a drinking water contamination event. Components of WS include: online water quality monitoring, enhanced security monitoring, consumer complaint surveillance, and innovative uses of public health surveillance data streams. LPH already use multiple surveillance data systems to recognize disease events in a timely manner. However, few of these systems can be integrated or specifically designed for detection of drinking water contamination incidents.

 

Objective

This poster describes the integration of public health surveillance data as a component of an early warning system for detection of a drinking water contamination incident.

Submitted by elamb on
Description

In February of 2007, the Bureau of Epidemiology (BOE) received a request from Houston Department of Public Works to investigate a possible rise in gastrointestinal (GI) illness associated with complaints about poor water quality in a Northeastern Houston neighborhood. To investigate this complaint, BOE combined case report data with syndromic data from our Real-Time Outbreak Disease Surveillance (RODS). The Houston RODS collects and synthesizes real-time chief complaint data from 34 area hospitals and health facilities, representing approximately 70% coverage of licensed ER beds in Harris County. The system uses a Naïve Bayes Classifier to categorize ER chief complaints into 7 different syndromes, including GI illness.

 

Objective

To investigate public concern over a possible increase in GI illness associated with water quality complaints in Northeast Houston.

Submitted by elamb on
Description

Outbreaks of waterborne gastrointestinal disease occur routinely in North America, resulting in considerable morbidity, mortality, and cost (Hrudey, Payment et al. 2003). Outbreak detection methods generally attempt to identify anomalies in time, but do not identify the type or source of an outbreak. We seek to develop a framework for both detection and classification of outbreaks using information in both space and time. Outbreak detection can be improved by using simulated outbreak data to build, validate, and evaluate models that aim to improve accuracy and timeliness of outbreak detection.

Objective

To develop a methodological framework for detecting and classifying outbreaks of gastrointestinal disease on the island of Montreal, with the goal of improving early outbreak detection using simulated surveillance data.

Submitted by rmathes on
Description

Canada experienced 92 waterborne diseases outbreaks between 1975 and 2001. In addition, at any one time about 1500 communities in Canada are unable to use their drinking water. The source of exposure in disease outbreaks is often not known, so the true disease burden attributable to water related exposure may be much higher. Researchers have investigated risk factors for waterborne disease. However, providing acces to surveiallance tools of use by frontline staff in the field as well as by surveillance professionals was key to making this type of system successful.

Objective

The objectives of this environmental health surveillance system were to provide a robust system for monitoring of water quality trends, and information to be used for mitigation of potential health problems, resource planning, risk analyses and decision making

Submitted by teresa.hamby@d… on

Cyanobacteria and marine algae are ubiquitous in the earth's freshwaters and oceans. Under the right circumstances, these organisms can proliferate, causing harmful algal blooms (HABs) which may produce toxins that threaten human and animal health as well as local and regional ecology. Animals may play in, swim in, or drink from ponds and lakes that have extensive blooms, even if the water bodies smell or look unpleasant to people; the first warning that a toxin-producing HAB exists may come from the death of a pet dog or livestock.

Submitted by uysz on