Motivated by the threat of bioterrorism, biosurveillance / syndromic surveillance systems are now in crisis: with the original purpose of early detection, and more than 10 years in existence, no health department has reported using them for this purpose. There seems to be almost a consensus in the biosurveillance community that syndromic surveillance systems, based on statistical algorithms, are likely of little value in early detection of bioterrorist outbreaks; but irrespective of whether biosurveillance systems could be useful for detecting bioterrorism or not, their most important contribution to public health practice is detecting and responding to natural disease outbreaks, such as seasonal and especially pandemic flu (see Fricker (2011a and 2011b)).This has led to a shift away from only early detection of bioterrorist attacks. The goal has been expanded in two directions: firstly, to switch the emphasis from bioterrorism only to detecting and responding to natural disease outbreaks; and secondly, to include both early event detection and situational awareness, so that the focus is not simply on detection, but also on timely response and consequence management including vaccination and hospitalization strategies. Even with this expansion, early detection capacity is problematic. There are several reasons for that. One of them is uncontrolled alert rates: there is an alarm nearly every day and most health monitors learned to ignore alarms. It results in distrust in statistical methods and in biosurveillance itself. That is why Fricker, the most outspoken critic of the current state of biosurveillance, concludes in his recent review article  in such a pessimistic way: “Returning to the original question of whether statistical methods are useful for early event detection, I suggest that we really don’t know yet. That is, whether the systems and their associated detection algorithms can be modified so that they appropriately minimize false positive signals while maintaining sufficient sensitivity to actual outbreaks is still an open question”. Thus, not only early detection of potentially unpredictable bioterrorist attacks is considered “mission impossible”, but also early detection in general, including natural disease outbreaks. In , the rejoinder to the discussion of article , Fricker wrote: “And, in spite of my research interest in EED (early event detection) methods, I would suggest that situational awareness is probably the more important function for biosurveillance, since it enhances public health surveillance and management before, during, and after an outbreak“.
In our paper  it is shown that the situation is not as bleak and that it is possible, at least in some cases, for example in the case of influenza pandemic, to develop an approach which allows to achieve simultaneously both goals: early detection and early situational awareness, which is a unique ability in biosurveillance. No existing biosurveillance systems are capable of doing this. Such unification of early detection and situational awareness can be possible only through fusion of syndromic surveillance with epidemiological predictive modeling. See more on integration in my next post.
 Fricker, R. D. (2011a). Some methodological issues in biosurveillance. Statistics in Medicine, [full text]
 Fricker, R. D. (2011b). Rejoinder: Some methodological issues in biosurveillance. Statistics in Medicine, [full text]
 Shtatland, E. and Shtatland, T. (2011). Statistical approach to biosurveillance in crisis: what is next. NESUG Proceedings, [full text]