A Discrete Application: Aberration Detection in Public Health Surveillance

• Activity Number: 83
• Type: Invited
• Date/Time: Monday, August 12, 2002 : 10:30 AM to 12:20 PM
• Sponsor: Section on Statistics in Epidemiology*
• Author(s): Lori Hutwagner*+
• Affiliation(s): Centers for Disease Control and Prevention
• Keywords: surveillance ; quality control ; aberration detection ; statistics in surveillance

Abstract

Public health surveillance data comes in all shapes and sizes. Likewise, the types of aberration detection methods that can be applied to public health surveillance data also vary. This presentation will be limited to methods which can be applied to single point source-type data for both traditional and non-traditional public health data. Aberration detection methods used for traditional data are published and applied to infectious diseases around the world. Illustrations of two methods, historical limits and a non-traditional CUSUM used for traditional public health data, will be demonstrated as they are applied to weekly 39 selected diseases from the Nationally Notifiable Diseases Surveillance System (NNDSS). Different methods, such as the traditional CUSUM, p chart, moving average, Chi Square and MILD , MEDIUM and ULTRA are appropriate for non-traditional public health surveillance data such as emergency department syndrome data or 911 call data. These methods have been applied to emergency department data collected through special surveillance surrounding large events. These methods are also being applied to non-traditional data collected at the county level in several states.