SaTScan on a Cloud: On-Demand Large Scale Spatial Analysis of Epidemics

Ronald C Price, Warren Pettey, Tim Freeman, Kate Keahey, Molly Leecaster, Matthew Samore, James Tobias, Julio C Facelli


By using cloud computing it is possible to provision on- demand resources for epidemic analysis using computer intensive applications like SaTScan. Using 15 virtual machines (VM) on the Nimbus cloud we were able to reduce the total execution time for the same ensemble run from 8896 seconds in a single machine to 842 seconds in the cloud. Using the caBIG tools and our iterative software development methodology the time required to complete the implementation of the SaTScan cloud system took approximately 200 man-hours, which represents an effort that can be secured within the resources available at State Health Departments. The approach proposed here is technically advantageous and practically possible.

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Online Journal of Public Health Informatics * ISSN 1947-2579 *