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  • Content Type: Abstract

    We developed a probabilistic model of how clinicians are expected to detect a disease outbreak due to an outdoor release of anthrax spores, when the clinicians only have access to traditional clinical information (e.g., no computer-based alerts). We… read more
    … how clinicians are expected to detect a disease outbreak due to an outdoor release of anthrax spores, when the … Modeling_Clinician_Detection_Time_Of_A_Disease_Outbreak_Due_To_Inhalational_Anthrax.pdf 2 views Submitted by elamb … Modeling Clinician Detection Time of a Disease Outbreak Due to Inhalational Anthrax Christina Adamou, Gregory F. …
  • Content Type: Abstract

    Many disease-outbreak detection algorithms, such as control chart methods, use frequentist statistical techniques. We describe a Bayesian algorithm that uses data D consisting of current day counts of some event (e.g., emergency department (ED)… read more
    … performs complete Bayesian Model Averaging (BMA) over all possible spatial distributions of disease, yet runs in … fficiently_Performs_Complete_Bayesian_Model_Averaging_Over_All_Possible_Spatial_Distributions_Of_Disease.pdf 5 views … Performs Complete Bayesian Model Averaging Over All Possible Spatial Distributions of Disease Yanna Shen1,2, …
  • Content Type: Abstract

    The Activity Monitoring Operating Characteristic (AMOC) curve is a useful and popular method for assessing the performance of algorithms that detect outbreaks of disease [1]. As it is typically applied in biosurveillance, the AMOC curve plots the… read more
    … type of outbreak of some disease D (e.g., an outbreak due to outdoor, airborne release of anthrax spores). The … provide a promising new approach for analyzing outbreak de- tection algorithms. REFERENCES [1] Fawcett T, Provost F. … Proceed- ings of International Conference on Knowledge Dis- covery and Data Mining (1999) 53-62. [2] Cooper GF, …