Displaying results 25 - 32 of 33
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Automated Time Series Forecasting for Biosurveillance
Content Type: Abstract
The statistical process control (SPC) community has developed a wealth of robust, sensitive monitoring methods in the form of control charts [1]. Although such charts have been implemented for a wide variety of health monitoring purposes [2], some… read more… The mean-based criterion was less conclusive due to the effects of poor forecasts on a small number of … -
An Exploration of New Uses of Traditional Data within an Ecological Study: Air Quality Effects on Pediatric Asthma Exacerbation Analysis
Content Type: Abstract
Under a grant from the Centers for Disease Control and Prevention (CDC), the DC DOH established the Environmental Public Health Tracking Program (EPHTP) to monitor specific environmental and public health indicators and to investigate any… read more… 2 views Submitted by elamb on Tue, 03/26/2019 - 16:22 … were seen mostly in the 5-12 age group. However, PM2.5 did not appear to be a risk factor, perhaps because … -
A Pilot Study of Aberration Detection Algorithms with Simulated Data
Content Type: Abstract
To evaluate four algorithms with varying baseline periods and adjustment for day of week for anomaly detection in syndromic surveillance data. read more… Introducing Outbreaks into Time Series Data, Adv Dis Surveillance 2007; 2:199. Advances in Disease … -
Incorporating Water Security into Syndromic Surveillance
Content Type: Abstract
Although rare in the US, the CDC reports 13-14 drinking-water-related disease outbreaks per year, affecting an average of about 1000 people. The US EPA has determined that the distribution system is the most vulnerable component… read more… 5 views Submitted by elamb on Tue, 03/26/2019 - 16:22 … system sectors that have similar water characteristics de- pending on the hydrostatic pressure and distance from … Health and WQ BBNs to assess the degree of belief that de- graded WQ is or is not associated with illnesses. The … -
Performance Characteristics of Control Chart Detection Methods
Content Type: Abstract
To recognize outbreaks so that early interventions can be applied, BioSense uses a modification of the EARS C2 method, stratifying days used to calculate the expected value by weekend vs weekday, and including a rate-based method… read more… syndrome/days with the standard deviation (SD) ≥0.5 by all methods were included. For calculating expected values, … vs rate methods, the latter accounting for total visits (i.e., both visits assigned and not assigned to a syndrome); … -
Minimizing False Alarms in Syndromic Surveillance
Content Type: Abstract
This paper describes a method of avoiding false alerts in automated syndromic surveillance algorithms which monitor the temporal relationship between a particular monitored syndrome (the ìtargetî) in relationship to other reference healthcare data… read more… is to use suitably-normalized syndromic counts (i.e., ratios or proportions) instead of the individual … is not obvious. One recent approach [2] has been to use all possible pair-wise ratios in an epidemiological network … -
Essential Requirements for Effective Advanced Disease Surveillance
Content Type: Abstract
Advanced surveillance systems require expertise from the fields of medicine, epidemiology, biostatistics, and information technology to develop a surveillance application that will automatically acquire, archive, process and present data to the user… read more… tra- ditionally relies on diagnosis, must be altered to de- velop an interpretation of less specific health indica- … tools must take into ac- count the normal deviations of all of the variables that comprise the background for the … and evidence-based decisions. Combining the trends of all available indicators can provide and earlier … -
Evaluation of Spatial Estimation Methods for Cluster Detection
Content Type: Abstract
CDC’s BioSense system provides near-real time situational awareness for public health monitoring through analysis of electronic health data. Determination of anomalous spatial and temporal disease clusters is a crucial part of… read more… data, we then applied our program to determine 1-day (i.e., spatial) clusters significant at a p-value threshold …