Displaying results 1 - 3 of 3
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Using Open-Source Grid-Computing Technology to Improve Processing Time for Geospatial Syndromic Surveillance Data
Content Type: Abstract
Outbreak detection algorithms for syndromic surveillance data are becoming increasingly complex. Initial algorithms focused on temporal data but newer methods incorporate geospatial dimensions. As methods evolve, it is important to understand the… read more… consist of 2 clusters, each containing 204 nodes. All computational nodes have two 2.4 GHz Pentium 4 Xeon … recorded. RESULTS Processing serially, as is typical in a PC environment, can be an inefficient way to handle large … -
Evaluating the Performance of a Spatial Scan Statistic Using Simulated Outbreak Characteristics
Content Type: Abstract
Research evaluating the use of spatial data for surveillance purposes is ongoing and evolving. As spatial methods evolve, it is important to characterize their effectiveness in real-world settings. Assessing the performance of… read more… cut-off. RESULTS Average sensitivity and PPV for all clusters was 0.97 ± 0.08 and 0.92 ± 0.10, respectively. … 1 shows averages for SaTScan sensitivity and PPV for all synthetic clusters stratified by syndrome. Table 1: … Anthrax Attacks and Syndromic Surveil- lance. Emerg Inf Dis 2005;11:1394-1398. 2. Mandl KD, et al. Measuring … -
A Novel, Context-Sensitive Approach to Anonymizing Spatial Surveillance Data: Impact on Outbreak Detection
Content Type: Abstract
The use of spatially-based methods and algorithms in epidemiology and surveillance presents privacy challenges for researchers and public health agencies. We describe a novel method for anonymizing individuals in public health datasets, by… read more… cases which resulted high values of dataset k- anonymity. De-identification that moves points an average distance of … that a k-anonymity value of 20 has been reached in 99% of all patients in a sam- ple dataset when the average distance …