Innovative approaches to Outbreak Detection and Control

Current biothreat surveillance systems are vulnerable to incomplete and delayed reporting, and recent outbreaks are characterised by slow recognition or response. They successfully detect large outbreaks but show significant delays and low sensitivity for moderate and small epidemics. Such delays diminish the opportunity respond effectively. In Canada, a one-week delay in SARS control measures resulted in a 2.6-fold increase in mean epidemic size and four-week extension of mean epidemic duration. Decision-making, resource utilisation and management are major problem areas for decisions about biothreats and there is lack of close-to-real time decision support. New syndromic surveillance systems monitor health utilisation patterns in real time and aim to detect infectious outbreaks ahead of laboratory diagnosis. Data sources include emergency department records (eg. presenting complaint) and hospital admission/discharge systems but these are not direct measures of disease outbreak. Further, syndromic surveillance is focused on detection, not control. Adding new visualisation modes eg geospatial displays of outbreak data, may provide powerful additional DSS modes to SSS and integrate detection and response. We are aiming at building an integrated infectious disease outbreak detection and response systems, measured by outcomes including accuracy and timeliness of outbreak detection and response.