Some methodological issues in biosurveillance

Abstract

This paper briefly summarizes a short course I gave at the 12th Biennial Centers for Disease Control and Prevention (CDC) and Agency for Toxic Substances and Disease Registry (ATSDR) Symposium held in Decatur, Georgia on April 6, 2009. The goal of this short course was to discuss various methodological issues of biosurveillance detection algorithms, with a focus on the issues related to developing, evaluating, and implementing such algorithms.

Using scan statistics for congenital anomalies surveillance: the EUROCAT methodology

“…Newer methods are also putting greater emphasis on the integration of multiple data sources, particularly for syndromic surveillance [17,18]. Prospective detection is necessary for the timely detection of outbreaks of disease or cases of bioterrorism and reliance on a single data source may not be sufficient [18]. In terms of congenital anomalies, the use of complete diagnostic data leads to a time lag before full case ascertainment is achieved, thereby necessitating a retrospective approach.…”

“…The focus is frequently on spatio-temporal clusters and early event detection (EED), with a view to pinpointing emerging clusters. Newer methods are also putting greater emphasis on the integration of multiple data sources, particularly for syndromic surveillance [17,18]. Prospective detection is necessary for the timely detection of outbreaks of disease or cases of bioterrorism and reliance on a single data source may not be sufficient [18].…”

Structural models used in real-time biosurveillance outbreak detection and outbreak curve isolation from noisy background morbidity levels

“…This represents a typical scenario in which statistically based biosurveillance methodologies are useful, as described by Fricker. 1 We thus anticipate an attack with some hundreds or thousands of individuals exposed simultaneously (by plume dispersal, for example) and eventually presenting symptoms. Similar scenarios have been investigated in Buckeridge et al 12 The data we have used to represent the background counts are a time series of daily International Classification of Disease, release 9 (ICD-9) codes obtained from hospitals in the greater Miami, Florida, area.…”

Spatial outbreak detection based on inference principles for multivariate surveillance

“…The urgent need for further discussion on metrics for evaluation of surveillance was stressed in Fricker (2011) as well as in the discussion and rejoinder.…”