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This paper describes a new expectation-based scan statistic that is robust to outliers (individual anomalies at the store level that are not indicative of outbreaks). We apply this method to prospective monitoring of over-the-counter (OTC) drug sales data, and demonstrate that the robust... Read more

Content type: Abstract

The spatial scan statistic detects significant spatial clusters of disease by maximizing a likelihood ratio statistic over a large set of spatial regions. Several recent approaches have extended spatial scan to multiple data streams. Burkom aggregates actual and expected counts across streams... Read more

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We present a systematic empirical comparison of five recently proposed expectation-based scan statistics, in order to determine which methods are most successful for which spatial disease surveillance tasks.

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The multivariate Bayesian scan statistic (MBSS) enables timely detection and characterization of emerging events by integrating multiple data streams. MBSS can model and differentiate between multiple event types: it uses Bayes’ Theorem to compute the posterior probability that each event type... Read more

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This paper describes a new class of space-time scan statistics designed for rapid detection of emerging disease clusters. We evaluate these methods on the task of prospective disease surveillance, and show that our methods consistently outperform the standard space-time scan statistic approach... Read more

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Traditionally, surveillance systems for dengue and other infectious diseases locate each individual case by home address, aggregate these locations to small areas, and monitor the number of cases in each area over time. However, human mobility plays a key role in dengue transmission, especially... Read more

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We propose a new method for detecting patterns of disease cases that correspond to emerging outbreaks. Our Anomaly Pattern Detector (APD) first uses a "local anomaly detector" to identify individually anomalous records and then searches over subsets of the data to detect self-similar patterns of... Read more

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An interdisciplinary team convened by ISDS to translate public health use-case needs into well-defined technical problems recently identified the need for new pre-syndromic surveillance methods that do not rely on existing syndromes or pre-defined illness categories1. Our group has recently... Read more

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We apply recently developed spatial biosurveillance techniques to the law enforcement domain, with the goal of helping local police departments to rapidly detect and respond to (or better yet, to predict and prevent) emerging spatial patterns of crime.

Content type: Abstract

The spatial scan statistic [1] detects significant spatial clusters of disease by maximizing a likelihood ratio statistic over a large set of spatial regions. Typical spatial scan approaches either constrain the search regions to a given shape, reducing power to detect patterns that do not... Read more

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