Biomedical subjects
Publications and source records attributed to G Matthew Seeman.
We compared aberration detection methods requiring historical data to those that require little background by using simulated data. Methods that require less historical data are as sensitive and specific as those that require 3-5 years of data. These simulations can determine which method produces appropriate sensitivity and specificity.
Data from public health surveillance systems can provide meaningful measures of population risks for disease, disability, and death. Analysis and evaluation of these surveillance data help public health practitioners react to important health events in a timely manner both locally and nationally. Aberration detection methods allow the rapid assessment of changes in frequencies and rates of different health outcomes and the characterization of unusual trends or clusters. The Early Aberration Reporting System (EARS) of the Centers for Disease Control and Prevention allows the analysis of public health surveillance data using available aberration detection methods. The primary purpose of EARS is to provide national, state, and local health departments with several alternative aberration detection methods. EARS helps assist local and state health officials to focus limited resources on appropriate activities during epidemiological investigations of important public health events. Finally, EARS allows end users to select validated aberration detection methods and modify sensitivity and specificity thresholds to values considered to be of public health importance by local and state health departments.
Local health departments concerned with early detection of potential terrorist threats are beginning to explore novel approaches to syndromic surveillance. Using the Early Aberration Reporting System (EARS) developed by the Centers for Disease Control and Prevention, a metropolitan health department in Tennessee and five community partners have agreed to exchange data in order to implement a multifaceted syndromic surveillance system for early detection of a biological attack. This article describes how we used EARS as the foundation for implementing a surveillance system that encompasses a rich variety of data sources. We address technical requirements for operating EARS, recommend staffing and training prerequisites, describe the involvement of our data partners, and provide details related to data transfer and analysis, review, and response protocol. Other health departments may find this information useful as a general model for implementing EARS-based syndromic surveillance systems in their own jurisdictions.