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Displaying results 9 - 16 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.
    … computable as a function of the aggregate count (i.e. number of disease cases) and aggregate baseline (i.e. … points are mapped to a uni- form grid, and searching over all rectangular regions on the grid) for the Bayesian … Communications in Sta- tistics: Theory and Methods, 1997, 26(6): 1481-1496. [2] Neill DB, Moore AW, Rapid detection of …
  • Identifying High-Risk Areas for Dengue Infection Using Mobility Patterns on Twitter

    Content Type: Abstract

    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… read more
    … plays a key role in dengue transmission, especially due to the mosquito day-biting habit, and relying solely on … plays a key role in dengue transmission, especially due to the mosquito day-biting habit, and relying solely on …
  • 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
    … common source of false positives. These outliers are not due to disease outbreaks, but instead reflect a variety of … method for reduc- ing the number of false positives due to outliers, thus increasing our power to detect true … Communications in Sta- tistics: Theory and Methods, 1997, 26(6): 1481-1496. [4] Kulldorff M, Prospective time-periodic …
  • 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
    … aggregation of cases (e.g. by month, by square mile), due to both computational considerations and the relatively … cluster was com- puted by randomization testing, and all significant primary and secondary clusters were … Communications in Sta- tistics: Theory and Methods, 1997, 26(6): 1481-1496. [6] Neill DB, Moore AW, Methods for …
  • Fast Graph Structure Learning from Unlabeled Data for Outbreak Detection

    Content Type: Abstract

    Disease surveillance data often has an underlying network structure (e.g. for outbreaks which spread by person-to-person contact). If the underlying graph structure is known, detection methods such as GraphScan (1) can be used to identify an… read more
    … We then compute the mean normalized score averaged over all training examples. If a given graph is close to the true … our method can successfully learn the additional edges due to travel patterns, substantially improving detection … ehtj11115 ehtj11120 ehtj11024 ehtj11060 ehtj11110 26-50 ehtj11034 ehtj11198 ehtj11174 ehtj11048 ehtj11154 …
  • Identifying Emerging Novel Outbreaks In Textual Emergency Department Data

    Content Type: Abstract

    Typical approaches to monitoring ED data classify cases into pre-defined syndromes and then monitor syndrome counts for anomalies. However, syndromes cannot be created to identify every possible cluster of cases of relevance to public health. To… read more
    … hospital location. The NC DPH dataset describes 198,511 de-identified ED visits over one year at 3 North Carolina … hospital location. The NC DPH dataset describes 198,511 de-identified ED visits over one year at 3 North Carolina …
  • 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
    … the most significant region by maximizing F(D, S, W) over all D, S, and W, and calculate the statisti- cal … Communications in Sta- tistics: Theory and Methods, 1997, 26(6): 1481-1496. [3] Kulldorff M, Prospective time-periodic …
  • Learning Outbreak Regions for Bayesian Spatial Biosurveillance

    Content Type: Abstract

    This work incorporates model learning into a Bayesian framework for outbreak detection. Our method learns the spatial characteristics of each outbreak type from a small number of labeled training examples, assuming a generative outbreak model with… read more
    … data prevent learning a multinomial distribution over all possible regions, while simpler models (e.g. uniform … of MBSS, with and without region learning, on simulated dis- ease outbreaks injected into real-world Emergency …