Displaying results 1 - 8 of 11
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A Method for Detecting and Characterizing Multiple Outbreaks of Infectious Diseases
Content Type: Abstract
We describe an automated system that can detect multiple outbreaks of infectious diseases from emergency department reports. A case detection system obtains data from electronic medical records, extracts features using natural language… read more -
Detecting Overlapping Outbreaks of Influenza
Content Type: Abstract
Influenza is a contagious disease that causes epidemics in many parts of the world. The World Health Organization estimates that influenza causes three to five million severe illnesses each year and 250,000-500,000 deaths. Predicting and… read more -
Evaluation of Microbiology Orders from a Veterinary Diagnostic Laboratory as a Potential Data Source for Early Outbreak Detection
Content Type: Abstract
Animals continue to be recognized as a potential source of surveillance data for detecting emerging infectious diseases, bioterrorism preparedness, pandemic influenza preparedness, and detection of other zoonotic diseases. Detection of disease… read more -
Evaluation of Veterinary Diagnostic Laboratories as a Possible Data Source for Prospective Outbreak Surveillance
Content Type: Abstract
Current veterinary surveillance systems may be ineffective for timely detection of outbreaks involving non-targeted disease. Earlier detection could enable quicker intervention that might prevent the spread of disease and limit lost revenue. Data… read more -
Ellipse-Based Clustering Analysis Using a Time Series Algorithm
Content Type: Abstract
Many cities in the US and the Center for Disease Control and Prevention have deployed biosurveillance systems to monitor regional health status. Biosurveillance systems rely on algorithms that analyze data in temporal domain… read more -
Student Rotation in a Veterinary Teaching Hospital as a Potential Surveillance Confounder
Content Type: Abstract
Identifying potential biases and confounders that may affect data quality is an important consideration when evaluating surveillance systems. Having the benefit of predictable temporal trends is a key requirement to improve upon… read more -
SyCo: A Probabilistic Machine Learning Method for Classifying Chief Complaints into Symptom and Syndrome Categories
Content Type: Abstract
Scientists have utilized many chief complaint (CC) classification techniques in biosurveillance including keyword search, weighted keyword search, and naïve Bayes. These techniques may utilize CC-to-syndrome or CC-… read more -
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