Displaying results 1 - 6 of 6
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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… (over-the-counter (OTC) sales, Emergency Department visits, etc.) to detect both natural disease outbreaks (e.g. … impressive results under simulated environments, but the com- plex behavior of real-world data and high costs asso- … bio-surveillance system. REFERENCES [1] Wagner MM, Tsui F-C, et al., A national retail data monitor for public … -
T-Cube as an Enabling Technology in Surveillance Applications
Content Type: Abstract
T-Cube is especially useful for rapidly retrieving responses to ad-hoc queries against large datasets of additive time series labeled using a set of categorical attributes. It can be used as a general tool to support any task… read more… of over-the-counter medications and emergency department visits. In this paper we present efficiencies which can be … pairs of size = 1 and 2, the total number of such com- binations exceeding 4.3 million. The involved ana- … -
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… Communications in Sta- tistics: Theory and Methods, 1997, 26(6): 1481-1496. [4] Kulldorff M, Prospective time-periodic … Methods for Anomaly Detection, 2005. [6] Wagner MM, Tsui F-C, et al., A national retail data monitor for public … -
Rapid Processing of Ad-Hoc Queries against Large Sets of Time Series
Content Type: Abstract
Time series analysis is very common in syndromic surveillance. Large scale biosurveillance systems typically perform thousands of time series queries per day: for example, monitoring of nationwide over-thecounter (OTC) sales data may require… read more… monitoring of nationwide over-thecounter (OTC) sales data may require separate time series analyses on tens of … scans performed over all potential disease clusters) may require millions of distinct queries. Commercial OLAP … of nationwide over-the- counter (OTC) sales data may require separate time series analyses on tens of … -
Searching for Complex Patterns Using Disjunctive Anomaly Detection
Content Type: Abstract
Modern biosurveillance data contains thousands of unique time series defined across various categorical dimensions (zipcode, age groups, hospitals). Many algorithms are overly specific (tracking each time series independently would often miss early… read more… of outbreaks), or too general (detections at state level may lack specificity reflective of the actual process at … dimension. An example anomalous cluster detectable by DAD may identify zipcode = {z1 or z2 or z3 or z5} and age_group … of outbreaks), or too general (detections at state level may lack specificity reflective of the actual process at … -
Detection of multiple overlapping anomalous clusters in categorical data
Content Type: Abstract
Syndromic surveillance typically involves collecting time-stamped transactional data, such as patient triage or examination records or pharmacy sales. Such records usually span multiple categorical features, such as location, age… read more… Weekly Epidemiological Reports3. The data stores patient visits spanning 26 regions and 9 diseases reported over 2.5 years. We …