TY - JOUR
T1 - Generalized AMOC curves for evaluation and improvement of event surveillance.
AU - Jiang, Xia
AU - Cooper, Gregory F.
AU - Neill, Daniel B.
PY - 2009
Y1 - 2009
N2 - We introduce Generalized Activity Monitoring Operating Characteristic (G-AMOC) curves, a new framework for evaluation of outbreak detection systems. G-AMOC curves provide a new approach to evaluating and improving the timeliness of disease outbreak detection by taking the user's response protocol into account and considering when the user will initiate an investigation in response to the system's alerts. The standard AMOC curve is a special case of G-AMOC curves that assumes a trivial response protocol (initiating a new and separate investigation in response to each alert signal). Practical application of a surveillance system is often improved, however, by using more elaborate response protocols, such as grouping alerts or ignoring isolated signals. We present results of experiments demonstrating that we can use G-AMOC curves as 1) a descriptive tool, to provide a more accurate comparison of systems than the standard AMOC curve, and 2) as a prescriptive tool, to choose appropriate response protocols for a detection system, and thus improve its performance.
AB - We introduce Generalized Activity Monitoring Operating Characteristic (G-AMOC) curves, a new framework for evaluation of outbreak detection systems. G-AMOC curves provide a new approach to evaluating and improving the timeliness of disease outbreak detection by taking the user's response protocol into account and considering when the user will initiate an investigation in response to the system's alerts. The standard AMOC curve is a special case of G-AMOC curves that assumes a trivial response protocol (initiating a new and separate investigation in response to each alert signal). Practical application of a surveillance system is often improved, however, by using more elaborate response protocols, such as grouping alerts or ignoring isolated signals. We present results of experiments demonstrating that we can use G-AMOC curves as 1) a descriptive tool, to provide a more accurate comparison of systems than the standard AMOC curve, and 2) as a prescriptive tool, to choose appropriate response protocols for a detection system, and thus improve its performance.
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M3 - Article
C2 - 20351865
AN - SCOPUS:79953801655
SN - 1559-4076
VL - 2009
SP - 281
EP - 285
JO - AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium
JF - AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium
ER -