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Displaying results 1 - 8 of 15
  • Virtual Speed Networking with the Analytic Solutions Committee (ASC)

    Content Type: Webinar

    Presented January 11, 2018. The purpose of the event was to stimulate and facilitate constructive communication and collaboration among analytic method developers and practitioners charged with routine public health surveillance, ranging from… read more
    … Twitter engagement and topical forums on  http://www.healthsurveillance.org/forums/ . The talks were intended … HIV, HCV, and HBV datasets in order to get accurate co-infection information along with finding record … E-mail: daniel.neill@nyu.edu Personal Website: http://www.cs.cmu.edu/~neill EPD Lab Website: …
  • 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
    … impressive results under simulated environments, but the com- plex behavior of real-world data and high costs asso- … can access alerts online on the SSS website, add and view com- ments on each alert, and select which alerts they want … Maheshkumar R. Sabhnani, sabhnani+@cs.cmu.edu www.autonlab.org Advances in Disease Surveillance 2006;1:62 …
  • 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.
    … tant statistical tools for cluster detection, and is com- monly used in the public health community for detec- … Further Information: Daniel B. Neill, neill@cs.cmu.edu www.cs.cmu.edu/~neill and www.autonlab.org Advances in Disease Surveillance 2006;1:55 …
  • 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
    … Statis- tical significance of each detected cluster was com- puted by randomization testing, and all significant … Further Information: Daniel B. Neill, neill@cs.cmu.edu www.cs.cmu.edu/~neill Advances in Disease Surveillance …
  • 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
    … GI). In order to determine if the subset of the test data cor- responding to rule R has an unexpectedly high con- centration of anomalies, we compare it to the corres- … Further Information: Daniel B. Neill, neill@cs.cmu.edu www.cs.cmu.edu/~neill and www.autonlab.org Advances in …
  • Scalable Detection of Irregular Disease Clusters Using Soft Compactness Constraints

    Content Type: Abstract

    The spatial scan statistic [1] detects significant spatial clusters of disease by maximizing a likelihood ratio statistic F(S) over a large set of spatial regions, typically constrained by shape. The fast localized scan [2] enables scalable… read more
    … appear. *Skyler Speakman E-mail: skylerspeakman@gmail.com (page number not for citation purpose) Fig. 1. …
  • 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
    … Further Information: Daniel B. Neill, neill@cs.cmu.edu www.cs.cmu.edu/~neill and www.autonlab.org Advances in Disease Surveillance 2007;2:61 mailto:neill@cs.cmu.edu http://www.cs.cmu.edu/%7Eneill http://www.autonlab.org/ A Robust …
  • 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
    … Further Information: Daniel B. Neill, neill@cs.cmu.edu www.cs.cmu.edu/~neill and www.autonlab.org Advances in Disease Surveillance 2007;2:60 mailto:neill@cs.cmu.edu http://www.cs.cmu.edu/%7Eneill A Multivariate Bayesian Scan …