A SaTScan™ macro accessory for cartography (SMAC) package implemented with SAS® software

BackgroundSaTScan is a software program written to implement the scan statistic; it can be used to find clusters in space and/or time. It must often be run multiple times per day when doing disease surveillance. Running SaTScan frequently via its graphical user interface can be cumbersome, and the output can be difficult to visualize.ResultsThe SaTScan Macro Accessory for Cartography (SMAC) package consists of four SAS macros and was designed as an easier way to run SaTScan multiple times and add graphical output. The package contains individual macros which allow the user to make the necessary input files for SaTScan, run SaTScan, and create graphical output all from within SAS software. The macros can also be combined to do this all in one step.ConclusionThe SMAC package can make SaTScan easier to use and can make the output more informative.

[1]  Allyson M. Abrams,et al.  A model-adjusted space–time scan statistic with an application to syndromic surveillance , 2005, Epidemiology and Infection.

[2]  T. Tango,et al.  International Journal of Health Geographics a Flexibly Shaped Spatial Scan Statistic for Detecting Clusters , 2005 .

[3]  Joseph S. Lombardo,et al.  A systems overview of the Electronic Surveillance System for the Early Notification of Community-Based Epidemics (ESSENCE II) , 2003, Journal of Urban Health.

[4]  Andrew F. Nelson,et al.  Syndromic surveillance using minimum transfer of identifiable data: The example of the national bioterrorism syndromic surveillance demonstration program , 2003, Journal of Urban Health.

[5]  Martin Kulldorff,et al.  Prospective time periodic geographical disease surveillance using a scan statistic , 2001 .

[6]  William B. Lober,et al.  Review Paper: Implementing Syndromic Surveillance: A Practical Guide Informed by the Early Experience , 2003, J. Am. Medical Informatics Assoc..

[7]  Farzad Mostashari,et al.  Use of ambulance dispatch data as an early warning system for communitywide influenzalike illness, New York City , 2003, Journal of Urban Health.

[8]  M. Kulldorff,et al.  Syndromic surveillance in public health practice, New York City. , 2004, Emerging infectious diseases.

[9]  Farzad Mostashari,et al.  Evaluation of school absenteeism data for early outbreak detection, New York City , 2005, BMC public health.

[10]  M. Kulldorff A spatial scan statistic , 1997 .

[11]  Melanie C Besculides Richard Heffernan Farzad Mostashari J Weissman Evaluation of School Absenteeism Data for Early Outbreak Detection New York City 20012002 , 2004 .

[12]  F. Mostashari,et al.  Syndromic surveillance: A local perspective , 2003, Journal of Urban Health.

[13]  A Nelson,et al.  National Bioterrorism Syndromic Surveillance Demonstration Program. , 2004, MMWR supplements.

[14]  J. Marc Overhage,et al.  Research Paper: Detection of Pediatric Respiratory and Diarrheal Outbreaks from Sales of Over-the-counter Electrolyte Products , 2003, J. Am. Medical Informatics Assoc..

[15]  K. Henning,et al.  What is syndromic surveillance? , 2004, MMWR supplements.

[16]  Richard Platt,et al.  Use of Automated Ambulatory-Care Encounter Records for Detection of Acute Illness Clusters, Including Potential Bioterrorism Events , 2002, Emerging infectious diseases.