Spatial and temporal aberration detection methods for disease outbreaks in syndromic surveillance systems

Abstract

Early surveillance of notifiable infectious diseases is a key element for their control by public health agencies. The goal of syndromic disease surveillance is to identify emerging infectious risks to public health in real or near real time as a method of early detection, trend monitoring, and false-alarm avoidance. This article reviews temporal, spatial, and spatial-temporal aberration detection techniques that can be used to facilitate the early detection of infectious disease outbreaks that can occur in nonrandom yet clustered distributions in geographic information systems (GIS)-based syndromic surveillance systems. The focus is on the approaches appropriate for prospective surveillance data. In addition, this article discusses the impact of data privacy, security, and data quality on detection algorithms and explores what the future GIS-based syndromic surveillance systems may hold. © 2011 Copyright Taylor and Francis Group, LLC.