| Literature DB >> 22195067 |
David L Buckeridge1, Christian Jauvin, Anya Okhmatovskaia, Aman D Verma.
Abstract
Increasingly, researchers use simulation to generate realistic population health data to evaluate surveillance and disease control methods. This evaluation approach is attractive because real data are often not available to describe the full range of population health trajectories that may occur. Simulation models, especially agent-based models, tend to have many parameters and it is often difficult for researchers to evaluate the effect of the multiple parameter values on model outcomes. In this paper, we describe Simulation Analysis Platform (SnAP) - a software infrastructure for automatically deploying and analyzing multiple runs of a simulation model in a manner that efficiently explores the influence of parameter uncertainty and random error on model outcomes. SnAP is designed to be efficient, scalable, extensible, and portable. We describe the design decisions taken to meet these requirements, present the design of the platform, and describe results from an example application of SnAP.Mesh:
Year: 2011 PMID: 22195067 PMCID: PMC3243283
Source DB: PubMed Journal: AMIA Annu Symp Proc ISSN: 1559-4076