Displaying results 33 - 40 of 41
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Hybrid Probabilistic Modeling and Automated Data Fusion for Biosurveillance Applications
Content Type: Abstract
The increased threat of bioterrorism and naturally occurring diseases, such as pandemic influenza, continually forces public health authorities to review methods for evaluating data and reports. The objective of bio-surveillance is to automatically… read more… chief complaints, ICD-9 diagnosis codes, physician office visits, and pharmacy data. In addition, information such as … -
A collaboration to enhance detection of disease outbreaks clustered by time of patient arrival
Content Type: Abstract
One objective of public health surveillance is detecting disease outbreaks by looking for changes in the disease occurrence, so that control measures can be implemented and the spread of disease minimized. For this purpose, the… read more… Results This method was tested and validated on ED visit count data covering over 6 years and aggregated at … -
Utility of Syndromic Surveillance for Investigating Morbidity Resulting from a Severe Weather Event
Content Type: Abstract
On 12/14/06, a windstorm in western Washington caused 4 million residents to lose power; within 24 hours, a surge in patients presented to emergency departments (EDs) with carbon monoxide (CO) poisoning. As previously described, records of… read more… our syndromic surveillance system captured 16,982 ED visits. Most of the 169 ED patients with CO-related illness … -
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… for detecting anomalies in daily emergency depart- ment visit data for 130 hospitals with 6 syndrome categories. … -
The Tradeoffs Driving Policy and Research Decisions in Biosurveillance
Content Type: Abstract
Every public health monitoring operation faces important decisions in its design phase. These include information sources to be used, the aggregation of data in space and time, the filtering of data records for required… read more… alerting methods, we used 3 years of outpatient clinic visit data in which records were classified by syndrome and … -
Data-Adapted Temporal Alerting Algorithms for Routine Health Monitoring
Content Type: Abstract
This paper discusses selection of temporal alerting algorithms for syndromic surveillance to achieve reliable detection performance based on statistical properties and the epidemiological context of the input data. We used quantities calculated from… read more… alerting algorithms involve four steps: preconditioning, com- putation of expected values, computation of test sta- … From these results, simple data classification schemes may be automated to choose an effective algorithm for a … streams.” Mor- bidity Mortality Weekly Report 2005 Aug 26;54 Suppl:55-62. Further Info.: Howard Burkom, … -
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… model networks of Reis, Kohane, and Mandl [2], and may be used to decide which target/context ratios will add … -
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… to more appropriately categorize an individual into mul- tiple groups so as to not limit the data utility. Simi- …