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Displaying results 1 - 8 of 16
  • A Bayesian Scan Statistic for Spatial Cluster Detection

    Content Type: Abstract

    This paper develops a new Bayesian method for cluster detection, the ìBayesian spatial scan statistic,î and compares this method to the standard (frequen-tist) scan statistic approach on the task of prospective disease surveillance.
  • Detecting and Preventing Emerging Epidemics of Crime

    Content Type: Abstract

    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… read more
  • A Multivariate Bayesian Scan Statistic

    Content Type: Abstract

    This paper develops a new method for multivariate spatial cluster detection, the ìmultivariate Bayesian scan statisticî (MBSS). MBSS combines information from multiple data streams in a Bayesian framework, enabling faster and more accurate… read more
  • A Nonparametric Scan Statistic for Multivariate Disease Surveillance

    Content Type: Abstract

    We present a new method for multivariate outbreak detection, the ìnonparametric scan statisticî (NPSS). NPSS enables fast and accurate detection of emerging space-time clusters using multiple disparate data streams, including nontraditional data… read more
  • A Robust Expectation-Based Spatial Scan Statistic

    Content Type: Abstract

    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… read more
  • Anomaly Pattern Detection for Biosurveillance

    Content Type: Abstract

    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… read more
  • Fast and Flexible Outbreak Detection by Linear-Time Subset Scanning

    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… read more
  • Monitoring Pharmacy Retail Data for Anomalous Space-Time Clusters

    Content Type: Abstract

    Bio-surveillance systems monitor multiple data streams (over-the-counter (OTC) sales, Emergency Department visits, etc.) to detect both natural disease outbreaks (e.g. influenza) and bio-terrorist attacks (e.g. anthrax re-lease). Many detection… read more