This is a recorded presentation from the 9th Annual GIS Day: GIS and Public Health Surveillance, held at the University at Albany School of Public Health on April 30, 2013.
Presenter:
Martin Kulldorf, Professor, Department of Population Medicine
Harvard Medical School and Harvard Pilgrim Health Care Institute
Using reportable disease data or electronic health records, the prospective space-time permutation scan statistics and the free SaTScan software can be used for disease outbreak detection. Importantly, it automatically adjust for any purely spatial and any purely temporal variation of the disease counts, as well as for the multiple testing inherent in the many potential outbreak location and sizes evaluated. After describing the method, it is illustrated for food-borne disease outbreak detection using 22 different types of data from Kaiser Permanente Northern California.
Likely disease outbreaks detected included a Salmonella cluster with five cases of the same rare serotype.