IBM T. J. Watson Research Center © 2004 IBM Corporation Site Surveillance Using Differential Detection Murray Campbell

IBM T. J. Watson Research Center © 2004 IBM Corporation 2Site Surveillance Using Differential Detection Acknowledgements  Based on work of Vijay Iyengar, Ed Pednault  This material is based upon work supported by the Air Force Research Laboratory(AFRL)/Defense Advanced Research Projects Agency (DARPA) under AFRL Contract No. F C Any opinions, findings, conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the AFRL and/or DARPA. Approved for Public Release, Distribution Unlimited (5/3/2004).

IBM T. J. Watson Research Center © 2004 IBM Corporation 3Site Surveillance Using Differential Detection Site-Based Bio-Surveillance The monitoring of a geographically constrained site with a relatively stable population for signs of disease outbreak.  Example of sites could include work sites, university campuses, or military bases  The population need not be present 24 hours a day

IBM T. J. Watson Research Center © 2004 IBM Corporation 4Site Surveillance Using Differential Detection What makes “Site-Based” Bio-Surveillance Different?  Increased data availability –Central authority for permissions –Centralized data collection  “Permissive” –“Sensitive” data more likely to be available  Relatively stable population –May be more homogenous than general population  Geographically constrained –Spatial considerations are greatly reduced or eliminated

IBM T. J. Watson Research Center © 2004 IBM Corporation 5Site Surveillance Using Differential Detection Differential Detection Approach  Define sites (regions) that normally track each other –Determine appropriate model for measured quantities Quantify normal variation in the tracking  Detect significant deviations in the tracking –Signifies event affecting one of the sites

IBM T. J. Watson Research Center © 2004 IBM Corporation 6Site Surveillance Using Differential Detection Differential Detection Approach Target Site Reference Site

IBM T. J. Watson Research Center © 2004 IBM Corporation 7Site Surveillance Using Differential Detection Experiments  Monitor phone calling patterns at two IBM sites –Yorktown, Hawthorne (10 miles apart) –Counts of calls/callers to medical facilities –Counts of all calls/callers –Currently being collected on a daily basis –Privacy ensured through Anonymization of calling number No reporting of called number

IBM T. J. Watson Research Center © 2004 IBM Corporation 8Site Surveillance Using Differential Detection Method  Assume underlying Poisson process  Define two time windows –History, Test  Model ratio of counts in a window  Use Chi-squared statistic to detect deviations –Empirical variance estimate

IBM T. J. Watson Research Center © 2004 IBM Corporation 9Site Surveillance Using Differential Detection Medically-Related Calls

IBM T. J. Watson Research Center © 2004 IBM Corporation 10Site Surveillance Using Differential Detection All Calls

IBM T. J. Watson Research Center © 2004 IBM Corporation 11Site Surveillance Using Differential Detection Issues  Requires –Good tracking –Significant volumes  Can use –Raw counts –Counts adjusted by domain knowledge If sites respond differently to some phenomenon