Displaying results 1 - 3 of 3
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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… criteria of connected hot zip codes and then determines top 5 clusters using maximum log likelihood ratio (MLLR). We … starting from one-year baseline query to the search of top 5 clusters. RESULTS WAV analyzed total 494 zip codes … web service model. Proc AMIA Symp 2005. 3. Zhang J, Tsui FC, Wagner MM, Hogan WR. Detection of out- breaks from time … -
A data simulation model using NRDM pharmaceutical sales counts
Content Type: Abstract
In disease surveillance, an outbreak is often present in more than one data type. If each data type is analyzed separately rather than combined, the statistical power to detect an outbreak may suffer because no single data source… read more… may suffer because no single data source captures all the individuals in the outbreak. Researchers, thus, … medication sales, such as thermometer sales from all ZIP code areas in a study region that include the areas … medication sales, such as thermo- meter sales from all ZIP code areas in a study region that include the areas … -
Modeling Baseline Shifts in Multivariate Disease Outbreak Detection
Content Type: Abstract
Population surges or large events may cause shift of data collected by biosurveillance systems [1]. For example, the Cherry Blossom Festival brings hundreds of thousands of people to DC every year, which results in simultaneous elevations in… read more… data streams may be prone to false alarms due to baseline shifts. In this paper, we propose a … data streams may be prone to false alarms due to baseline shifts. In this paper, we propose a …