Prospective time-periodic geographical disease surveillance using a scan statistic

By Martin Kulldorff. 2001

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In Epidemiology

Citations in the corpus

The Use of Control Charts in Health-Care and Public-Health Surveillance (2006, methodology): “Related work was given by Järpe (1999), who proposed a method based on the Ising model, and Kulldorff (2001), who proposed a method based on a space–time scan statistic.”
A Space–Time Permutation Scan Statistic for Disease Outbreak Detection (2005, methodology): “As with the Poisson- and Bernoulli-based prospective space–time scan statistics [27], the space–time permutation scan statistic utilizes thousands or millions of overlapping cylinders to define the scanning window, each being a possible candidate for an outbreak.”
Spatial Scan Statistics Adjusted for Multiple Clusters (2010, background): “14, 15 (cid:4) , or scan statistics that are designed to detect areas with lower rather than higher rates of disease, and we do not know how well a sequential procedure would work in such a setting.”
Mathematical modeling of infectious disease dynamics (2013, methodology): “70 The SatScan software is based on the spatial scan statistic 71, 72 and the Bernoulli spatial model.”
Upper level set scan statistic for detecting arbitrarily shaped hotspots (2004, unknown): “When applied in space-time, the scan statistic approach can provide early warning of disease outbreaks and can monitor the spatial spread of an outbreak (Kulldorff, 2001; Mostashari et al., 2002; Waller, 2002).”
EARLY DETECTION OF A CHANGE IN POISSON RATE AFTER ACCOUNTING FOR POPULATION SIZE EFFECTS (2011, background): “The specific data motivating this article concerns male thyroid cancer cases (with malignant behavior) in New Mexico during 1973-2005; the data have been studied before in the biosurveillance literature in other contexts, see, for example, Kulldorff (2001) and Sonesson (2007).”
Spatial Epidemiology: Current Approaches and Future Challenges (2004, unknown): “…outcome data for disease prevention and control purposes (Thacker and Berkelman 1992), can be applied to the problem of disease clusters through the use of space, time, and space-time pattern detection methods (Kulldorff et al. 1997; Kulldorff 1997, 2001; Rogerson 1997, 2001; Rushton et al. 1996).”