Displaying results 9 - 13 of 13
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Application of a Bayesian Spatiotemporal Surveillance Method to NYC Syndromic Data
Content Type: Abstract
As technology advances, the implementation of statistically and computationally intensive methods to detect unusual clusters of illness becomes increasingly feasible at the state and local level [2]. Bayesian methods allow for the incorporation of… read more -
Detecting Unanticipated Increases in Emergency Department Chief Complaint Keywords
Content Type: Abstract
The CC text field is a rich source of information, but its current use for syndromic surveillance is limited to a fixed set of syndromes that are routine, suspected, expected, or discovered by chance. In addition to syndromes that are routinely… read more -
Comparison between HL7 and Legacy Syndromic Surveillance Data in New York City
Content Type: Abstract
Data from the Emergency Departments (EDs) of 49 hospitals in New York City (NYC) is sent to the Department of Health and Mental Hygiene (DOHMH) daily as part of the syndromic surveillance system. Currently, thirty-four of the EDs transmit data as… read more -
Building a Better Syndromic Surveillance System: the New York City Experience
Content Type: Abstract
The New York City (NYC) syndromic surveillance system has monitored syndromes from NYC emergency department (ED) visits since 2001, using the temporal and spatial scan statistic in SaTScan for aberration detection. Since our syndromic system was… read more -
Tractable Use Cases for Collaboration in Public Health Surveillance
Content Type: Abstract
The mission of the ISDS TCC is to bridge the gap between the analytic needs of public health practitioners and the expertise of researchers from other fields for the enhancement of disease surveillance, including situational awareness of chronic as… read more