Research Article
Transparency and Documentation in Simulations of Infectious Disease Outbreaks: Towards Evidence-Based Public Health Decisions and Communications
@INPROCEEDINGS{10.1007/978-3-642-11745-9_6, author={Joakim Ekberg and Toomas Timpka and Magnus Morin and Johan Jenvald and James Nyce and Elin Gursky and Henrik Eriksson}, title={Transparency and Documentation in Simulations of Infectious Disease Outbreaks: Towards Evidence-Based Public Health Decisions and Communications}, proceedings={Electronic Healthcare. Second International ICST Conference, eHealth 2009, Istanbul, Turkey, September 23-15, 2009, Revised Selected Papers}, proceedings_a={E-HEALTH}, year={2012}, month={5}, keywords={outbreak simulation ontologies report generator}, doi={10.1007/978-3-642-11745-9_6} }- Joakim Ekberg
Toomas Timpka
Magnus Morin
Johan Jenvald
James Nyce
Elin Gursky
Henrik Eriksson
Year: 2012
Transparency and Documentation in Simulations of Infectious Disease Outbreaks: Towards Evidence-Based Public Health Decisions and Communications
E-HEALTH
Springer
DOI: 10.1007/978-3-642-11745-9_6
Abstract
Computer simulations have emerged as important tools in the preparation for outbreaks of infectious disease. To support the collaborative planning and responding to the outbreaks, reports from simulations need to be transparent (accessible) with regard to the underlying parametric settings. This paper presents a design for generation of simulation reports where the background settings used in the simulation models are automatically visualized. We extended the ontology-management system Protégé to tag different settings into categories, and included these in report generation in parallel to the simulation outcomes. The report generator takes advantage of an XSLT specification and collects the documentation of the particular simulation settings into abridged XMLs including also summarized results. We conclude that even though inclusion of critical background settings in reports may not increase the accuracy of infectious disease simulations, it can prevent misunderstandings and less than optimal public health decisions.