Displaying results 1 - 3 of 3
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Algorithms to Characterize Syndromic Surveillance Spatial Alerts
Content Type: Abstract
This paper explores some visualization methods for characterizing spatial signals detected by SaTScan and discusses how these maps might aid in deciding whether to investigate a signal, as well as the scope and focus of the investigation. -
Automated Creation of High-Quality Maps Using SAS and Python
Content Type: Abstract
New York City ED syndromic surveillance data uses SaTScan to detect spatial signals. SaTScan analysis has been integrated into SAS since 2002, and signal maps have been generated from SAS since 2003. Signal maps are created occasionally to… read more -
Visualization of Syndromic Surveillance Using GIS
Content Type: Abstract
Syndromic Surveillance has been in use in New York City since 2001, with 2.5 million visits reported from 39 participating emergency departments, covering an estimated 75% of annual visits. As syndromic surveillance becomes increasingly spatial and… read more