For disease outbreak detection, the public health community has historically relied on the watchful eyes of doctors, who have reported individual cases or clusters of cases of particular diseases to the authorities. But these days, the availability of electronic health-care data should facilitate more automated and earlier outbreak detection and intervention. Besides diagnoses of known diseases, other indicators--such as primary complaints of patients coming to the emergency room or calling a nurse hotline--are being collected in electronic formats and could be analyzed if suitable methods existed.
Martin Kulldorff and colleagues have developed and operated real-time disease surveillance systems based on electronic records. In an article published in the open-access medical journal PLoS Medicine, they now report a new and very flexible approach for early disease outbreak detection.
The method, called the "space time permutation scan statistic," is an extension of a previous method of detecting outbreaks called scan statistic. The problem with this previous method is that it works only under certain circumstances, for example if there is a uniform population at risk (with the same number of expected disease cases in every square kilometer), or if quite a bit is known about the variation in factors such as age and disease susceptibility that occurs in that population. The new method doesn't need any of that: it can detect disease outbreaks when only the number of cases is available.
In their article, Kulldorff and colleagues illustrate the utility of the new method by applying it to data collected from hospital emergency departments in New York City. The researchers analyzed diarrhea records from 2002, and did both a "residential analysis" (based on the home address of the patients) and a "hospital analysis" (based on hospital locations). The former has more detailed geographical information, the latter maybe be better able to detect outbreaks not primarily related to place of residence but, for example, school or workplace. With their new "space time permutation scan statistic," they found four highly unusual clusters of diarrhea cases, three of which heralded citywide gastrointestinal outbreaks due to rotavirus and norovirus. This suggests that their method can detect outbreaks early, and--equally important--it isn't prone to false alarms.
Since November 2003, the method has been integrated by the New York City Emergency Department in its syndromic surveillance system (this system for monitoring outbreaks was established in 1995 to detect outbreaks of waterborne, diarrheal illnesses). To make the method more widely accessible, it has been implemented as a feature of the freely available SaTScan software (http://www.satscan.org).
Additional online information:
# Details on SaTScan and software for downloading: http://www.satscan.org/
# National Syndromic Surveillance Conference: http://www.syndromic.org/index.html
# National Bioterrorism Syndromic Surveillance Demonstration Program: http://btsurveillance.org/
# The Real-time Outbreak and Disease Surveillance Open Source Project: http://openrods.sourceforge.net/
Citation: Kulldorff M, Heffernan R, Hartman J, Assunciao R, Mostashari F (2005) A space-time permutation scan statistic for disease outbreak detection. PLoS Med 2(3): e59.
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