Displaying results 1 - 3 of 3
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Benchmark Data Generation from Discrete Event Contact Network Models
Content Type: Abstract
Historical data are essential for development of detection algorithms. Spatio-temporal data, however, are difficult to come by due to variety of issues concerning patient confidentiality. Several approaches have been used to … read more… Spatio-temporal data, however, are difficult to come by due to variety of issues concerning patient … Spatio-temporal data, however, are difficult to come by due to variety of issues concerning patient confi- … we demonstrate how to generate benchmark data using a dis- crete event model simulating inter- and intra-contact … -
High Performance Computing for Disease Surveillance
Content Type: Abstract
Space-time detection of disease clusters can be a computationally intensive task which defies the real time constraint for disease surveillance. At the same time, it has been shown that using exact patient locations, instead of their representative… read more… from 4 to 72 weeks spanning a period of ten years. The de- tection algorithm was thus parallelized by processing … using individual addresses is more efficient due to higher computational fidelity. When we utilize 32 or … -
Surveillance in the Cloud: A New Platform for Disease Search and Situational Awareness
Content Type: Abstract
Major challenges in syndromic surveillance today include lack of standardization in syndrome definitions and limited ability to detect outbreaks of specific and rare diseases. To generate situational awareness surveillance results… read more… in syndrome definitions and limited ability to de- tect outbreaks of specific and rare diseases. To … complaint data. We compute the power set over the set of all possible values contained in the data. For each subset, …