Simulation Analysis Platform (SnAP): a tool for evaluation of public health surveillance and disease control strategies.
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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. (+info)
Evaluation of HL7 v2.5.1 electronic case reports transmitted from a healthcare enterprise to public health.
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Public health surveillance is necessary to prevent and control communicable and non-communicable diseases. An electronic reporting system using HL7 v2.5.1 was implemented between Intermountain Healthcare and the Utah Department of Health. We conducted prospective and retrospective studies to evaluate the timeliness, completeness of content information, and completeness of the electronic reporting process, and compared these metrics against other reporting entities. The electronic reporting system was more timely than other clinical reporting facilities and included more complete information in initial case reports. During a four month period, the electronic reporting system captured 8% of the cases not reported by the paper-based reporting system but missed 5% of the cases reported by the paper-based reporting system. We believe it would be more efficient for Infection Preventionists at hospitals to use their resources to detect cases not captured by the electronic reporting system instead of manually re-reporting cases already transmitted to public health electronically. (+info)
The EpiCanvas infectious disease weather map: an interactive visual exploration of temporal and spatial correlations.
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