Evaluation of Syndromic Surveillance

Singapore's syndromic surveillance programmes include the monitoring of polyclinics and emergency departments (ED) attendances for acute diarrheal illness, acute respiratory infections, influenza-like illness, acute conjunctivitis and chickenpox.

Objective

We evaluated these syndromic surveillance systems for its representativeness, usefulness and data quality and identified areas for improvement.

The evaluation of outbreak detection performance remained a major challenge to every syndromic surveillance system. Owing to the scarcity and uncertainty of infectious disease outbreaks in the real world, simulated outbreak datasets have been commonly used by scholars for performance evaluation. Although this method was powerful in estimating the performance of syndromic surveillance across a variety of outbreak scenarios, the inevitable differences between simulation and authentic outbreak event limited its external validity.

Objective

Our study aimed to conduct high-fidelity simulations based on real-world outbreaks for evaluating the performance of syndromic surveillance system.

Completeness of public health information is essential for the accurate assessment of community health progress and disease surveillance. Yet challenges persist with respect to the level of completeness that public health agencies receive in reports submitted by health care providers. Missing and incomplete data can jeopardize information reliability and quality resulting in inaccurate disease evaluation and management (1). Additionally, incomplete data can prolong the time required for disease investigators to complete their work on a reported case. Thus, it is important to determine where the scarcity of information is coming from to recognize the characteristics of provider reporting.

Objective

To examine the completeness of data elements required for notifiable disease surveillance from official, provider-based reports submitted to a local health department.

We conducted a study to examine the suitability of the data collected at the local emergency departments for use in syndromic surveillance.

This paper assesses the possible interest of using of a syndromic surveillance system based on emergency departments (ED) and crude mortality for monitoring health effects of climate changes (CC).

The syndromic surveillance system “2SE FAG” has been installed within the French Armed Forces in French Guiana (3000 people) in October 2004 [1-2]. During the conception and the deployment of such a system, ergonomic issues were highlighted and training of stakeholders as well [3]. Daily exchanges with users have already permitted to enhance the system. An standardized and quantified evaluation among the users had to be done after 18 months of functioning. The objectives of this work were to evaluate the knowledge, the attitude and the practice of the stakeholders of the system.

Objective

This paper describes an evaluation survey made within the users of a real time surveillance system in French Guiana.

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.

One of the first county-wide syndromic surveillance systems in the nation, the Syndromic Tracking and Reporting System (STARS) has been in operation since 11/01/2001, and now covers Hillsborough, Pinellas and Collier counties. STARS uses hospital emergency department visit data to detect aberrations of non-specific syndromes and serves as an earlier warning system for public health threats. Patient’s syndrome is collected upon arrival, separately from routine collection of clinical and administrative data; but in some hospitals the process is being streamlined with routine data collection. Aberration detection is done twice daily using the statistical system EARS developed by the CDC. Upon flagging of an aberration, follow-up investigation is conducted to verify cases, and identify source of exposure following a sequence of decision procedure. After several years of operation and some instituted enhancements, a systematic evaluation was called to (1) assess if STARS has met the operation specifications and (2) characterize system efficacy and effectiveness.

Objective

To evaluate STARS with respect to quality of syndrome diagnoses, timeliness and completeness of data collection and processing, performance of aberration detection methods, and aberration investigation.