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Principal Investigators: Richard Rothman, MD, PhD

Research Question:

The research question is will coupling either traditional and/or novel internet-based influenza surveillance signals with a strategically focused response plan result in significant improvements in our ability to match care demands with resources (as measured by medical surge indices in the Emergency Department [ED]) compared to baseline and control sites). The value of bio-surveillance systems lies in the potential to warn and trigger early responses that could potentially prevent spread of disease and offset surge in medical facility operations. While extensive research and investment has been directed towards developing syndromic surveillance systems for infectious disease preparedness (including novel internet-based surveillance systems, e.g. Google Flu) there is a conspicuous absence of studies demonstrating improved outcomes in medical systems as a result of syndromic surveillance. This study will evaluate reliability of traditional and novel syndromic surveillance systems for influenza at the local level, and develop, and determine the impact of specific sets of strategically planned interventions that will be activated in response to syndromic surveillance triggers. In so doing, this study will provide a first time evaluation of the real-world utility of traditional and novel internet-based surveillance methods for targeted disaster response planning with potential impact on medical and public health outcomes. This work is directly aligned with one Homeland Security Presidential Directive (HSPD-21) to create “nationwide, robust, and integrated biosurveillance capability, to provide early warning and ongoing characterization of disease outbreaks in near real-time.”

Analytic Approach:

Our analytic approach is to first perform retrospective analysis to define the precise temporal relation between surveillance data (both internet-based and traditional) and confirmed local influenza outbreaks, using culture data and influenza reporting from each site. In year 2 we will test the hypothesis that coupling surveillance signals with a strategic response plan will result in significant improvements in the ability to handle surges in demand (as measured by ED-based medical surge indices) compared to baseline and control sites. Studies of hospital preparedness have raised considerable concern regarding the potential for EDs (and hospitals) to handle the massive patient surge that would result from a severe influenza pandemic. Annual influenza events represent a “dress rehearsal” of sorts for the medical system’s capability to respond to larger catastrophic events, such as pandemic influenza or SARS. While concerted efforts by both the public health and medical systems directed toward preparedness and response to infectious disease threats have been forged (including Pan Flu Implementation Plans; educational programs for increasing clinician awareness; improved methods for rapid diagnostic testing; and syndromic surveillance), translating these measures into demonstrable outcomes has been challenging.

With respect to syndromic surveillance, the value to early warning is lost if warning is not sufficiently timely and/or if the signal is not tightly linked to a response plan. With the advent of novel internet-based surveillance methods (which appear to provide earlier warning than traditional methods) and increased experience and appreciation of the operational systems required for offsetting medical surge, the possibility of linking response with an early signal to offset measures of medical surge associated with an infectious disease outbreak is now possible. Research in the arena of infectious disease outbreak and medical infrastructure vulnerability, while limited to date requires a cross-cutting interdisciplinary approach. We have assembled a team and project to address this challenge.