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Displaying results 57 - 64 of 121
  • The Implementation of an Outbreak Management Solution in New York State

    Content Type: Abstract

    Most outbreaks are small and localized in nature, although it is larger outbreaks that result in the most public attention. So a solution to manage an outbreak has to be able to accommodate a response to small outbreaks in a single jurisdiction… read more
    … common vocabulary where possible. The OMS user guide and training were provided to those who will be using it to … User acceptance testing was completed in July and webinar trainings to all users were completed in September 2011. The … consists of a combination of systems development, training and technical communications enhancements. The OMS …
  • Maximum Entropy Models in Chief Complaint Classification

    Content Type: Abstract

    This paper describes a novel approach to the statistical classification of free-text chief complaints for the purpose of syndromic surveillance.
    … hand-classified into one of eight categories was used to train both CoCo and the new Maximum Entropy classifier. A … low and highly variable due to the low availability of training data. Epidemiological and clinical assessment from … by CoCo because the word had not been observed in the training set. CONCLUSIONS Maximum Entropy classification …
  • Delineating Spatial Clusters with Artificial Neural Networks

    Content Type: Abstract

    Multiple or irregularly shaped spatial clusters are often found in disease or syndromic surveillance maps. We develop a novel method to delineate the contours of spatial clusters, especially when there is not a clearly dominating primary cluster,… read more
    … We start de- fining a MLP artificial neural network with training set size m. The geographic coordinates and the scan … backpropagation [2,3]. Follow- ing the training phase, the scan function evaluation is extended for … [2] M. H. Fun and M.T. Hagan, 1996. Levenberg-Marquardt training for modular networks. In Proceedings of the IEEE …
  • Mixture Likelihood Ratio Scan Statistic for Disease Outbreak Detection

    Content Type: Abstract

    This article describes the methodology and results of Team #134ís submission to the 2007 ISDS Technical Contest.
    … sales (OTC), and nurse hotline calls (TH)). The training data included 30 outbreak signatures for each … nent. Guided by the distinct outbreak signatures in the training data, we assumed parametric forms for the outbreak … 1 shows the result of the parametric fit for the first training outbreak. Our contest score was 5.58 for ED, 24.00 …
  • Tracking Community Naloxone Dispensing: Part of a Strategy to Reduce Overdose Deaths

    Content Type: Abstract

    The number of unintentional overdose deaths in New York City (NYC) has increased for seven consecutive years. In 2017, there were 1,487 unintentional drug overdose deaths in NYC. Over 80% of these deaths involved an opioid, including heroin,… read more
    … then dispense kits to individuals via community-based trainings. In this context, distribution refers to kits … then dispense kits to individuals via community-based trainings. In this context, distribution refers to kits …
  • Integrating Early Event Detection into Local Disease Surveillance and Response

    Content Type: Abstract

    This poster describes the practical integration of Early Event Detection (EED) into the daily operation of a medium sized public health department to improve surveillance for, and response to, outbreaks of communicable disease.
    … for simple and rapid checking by someone with limited training. Automated daily emergency department reports are …
  • 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
    … connected subgraph for each graph structure and each training example using GraphS- can. We normalize each score … by the maximum unconstrained subset score for that training example (computed efficiently using LTSS). We then compute the mean normalized score averaged over all training examples. If a given graph is close to the true …
  • Results from the BioSense Jurisdiction-Specific Wbinars

    Content Type: Abstract

    BioSense is a Centers for Disease Control and Prevention (CDC) national near real-time public health surveillance system. CDC’s BioIntelligence Center (BIC) analysts monitor, analyze, and interpret BioSense data daily and provide support to BioSense… read more
    … hospital utilization and mortality data. Identified training needs included the following: 1) how to use the … up during an event, and 2) self- paced, interactive training materials and tools that will enable users to … this level of dialogue, as well as develop additional training tools to provide ongoing support for our users. …