Murray Erin

The New York City Department of Health and Mental Hygiene (NYC DOHMH) collects data daily from 50 of 61 (82%) emergency departments (EDs) in NYC representing 94% of all ED visits (avg daily visits ~10,000). The information collected includes the date and time of visit, age, sex, home zip code and chief complaint of each patient. Observations are assigned to syndromes based on the chief complaint field and are analyzed using SaTScan to identify statistically significant clusters of syndromes at the zip code and hospital level. SaTScan employs a circular spatial scan statistic and clusters that are not circular in nature may be more difficult to detect. FlexScan employs a flexible scan statistic using an adjacency matrix design.

Objective

To use the NYC DOHMH's ED syndromic surveillance data to evaluate FleXScan’s flexible scan statistic and compare it to results from the SaTScan circular scan. A second objective is to improve cluster detection in by improving geographic characteristics of the input files.

Emergency Department (ED) syndromic surveillance data for influenza-like illness (ILI) have been found to provide timely and representative information about current influenza activity in NYC. DOHMH monitors visits daily from 50 of 61 EDs, capturing about 94% of all ED visits in NYC. Since January 1, 2007, DOHMH has been receiving disposition data (e.g., hospitalized, discharged) from a subset of EDs. Currently, disposition data is received from 37 EDs (approximately 1/3 of all visits by the next day and >60% of all visits within 1 week).

More detailed hospitalization data, including date, demographics, and diagnosis on all NYC hospitalizations are routinely collected by the New York State Department of Health Statewide Planning and Research Cooperative System (SPARCS). SPARCS is subject to a 2-3 year reporting lag, thus limiting its timeliness and prospective use. However, SPARCS data from prior to January 1, 2007 can supplement the ED syndromic data to develop a model for ILI hospitalizations and calculate excess hospitalizations attributable to influenza that can be used in near realtime, particularly in the event of a pandemic.

Objective

To use ED syndromic surveillance data to monitor hospitalizations for ILI and calculate excess hospitalizations attributable to influenza.

On June 22, 2007 increases in over-the-counter (OTC) electrolyte and child anti-fever medication sales were detected through routine OTC surveillance. Increases in emergency department (ED) data for gastrointestinal (GI) illness among <5 year olds were observed on June 23 and 24. Further analyses indicated clustering within one borough of NYC, with three EDs having most of the visits. Because NYC has had limited success in detecting spatial outbreaks using syndromic surveillance in the past, an investigation was not immediately initiated.

DOHMH was notified of a multi-state outbreak of S. wandsworth suspected to be associated with the snack food Veggie Booty® on June 26. Cases were predominantly young children and included 8 confirmed cases among NYC residents with onset dates from March 4 – May 19.

Objective

To determine whether increases in GI illness detected through OTC drug sales and ED syndromic surveillance were linked to a multi-state outbreak of S. wandsworth associated with the consumption of Veggie Booty® snack food.

On August 29, 2005, Hurricane Katrina made landfall just east of New Orleans, LA at 6:10AM CST and again at the LA/MS border at 10:00AM CST as a Category 3 hurricane, causing mass destruction along their coastlines. The devastation in LA and MS forced many residents to evacuate. Outside of the hurricane affected areas of LA, MS, and AL, GA received the second largest number of evacuees (approximately 125,000).

Objective

To describe the victims of Hurricane Katrina who evacuated to GA and to assess their impact on emergency departments enrolled in GA’s syndromic surveillance system.

There are multiple sources of influenza and influenza-like illness (ILI) surveillance data within the state of Georgia. These include laboratory surveillance for influenza viruses, sentinel providers that report ILI, pneumonia and influenza mortality, influenza-associated hospitalizations, and influenza-associated pediatric deaths. The usefulness of emergency department-based (ED) syndromic surveillance (SS) data as an additional source of ILI surveillance data is currently being evaluated at national, state, and local levels.

Objective

To describe Georgia’s experience using ED-based SS as a source of influenza-like illness surveillance data.

As the Georgia Division of Public Health began constructing a systems interface for its syndromic surveillance program, the nature and intended use of these data inspired new approaches to interface design. With the temporal and spatial components of these data serving as fundamental determinants within common aberration detection methods (e.g., Early Aberration Reporting System, SaTScan™), it became apparent that an interface technique that could present a synthesis of the two might better facilitate the visualization, interpretation and analysis of these data.

Typical presentations of data spatially oriented at the zip code level use a color gradient applied to a zip code polygon to represent the differences in magnitude of events within a given region across a particular time span. Typical presentations of temporally oriented data use time series graphs and tabular formats. Visualizations that present both aspects of spatially and temporally rich datasets within a single visualization are noticeably absent.

Objective

This paper describes an approach to the visualization of disease surveillance data through the use of animation techniques applied to datasets with both temporal and geospatial components.

Although many syndromic surveillance (SS) systems have been developed and implemented, few have included response protocols to guide local health jurisdictions when alerts occur [1,2]. SS was first implemented in GA during the 2004 G-8 Summit. Six EDs in the Coastal Public Health District (PHD), 1 of 18 GA PHDs (Figure 1), conducted SS during that “national security special event.” Since that time, EDs in other PHDs have been actively recruited to participate in GA’s SS system. In GA, the PHD has the responsibility for monitoring SS data. Likewise, the PHD responds to alerts and initiates public health investigations and interventions; the state Division of Public Health (DPH) assists, if requested. To address these responsibilities, the Coastal PHD informally developed their own response practices.

Objective

To develop a template protocol to guide local response to syndromic surveillance alerts generated through analyses of emergency department (ED) visit data.

The City of Atlanta, volunteer organizations, and the faith community operate several homeless shelters throughout the city. Services available at these shelters vary, ranging from day services, such as meals, mail collection, and medical clinics, to overnight shelter accommodations. In addition to the medical clinics available at these facilities, the Atlanta homeless population also utilizes emergency departments in Fulton County for their health care needs.

Objective

This paper describes a cluster of Streptococcus pneumoniae infections identified through emergency department syndromic surveillance.

To compare age-group-specific correlation of influenza-like syndrome (ILS) emergency department (ED) visits with influenza laboratory data in Boston and NYC using locally defined ILS definitions.

To compare locally-developed influenza-like syndrome definitions (derived from emergency department (ED) chief complaints) when applied to data from two ISDS DiSTRIBuTE Project participants: Boston and New York City (NYC) [1].