From 2023-2024, CSTE partnered with several academic and industry groups to develop analytic tools for public health outbreak response. In August, 2024, Signature Science’s VP Nagraj delivered a presentation CTSE-hosted webinar series on the PLANES approach and rplanes software developed through this collaboration.
Register to watch the presentation and presentations from other CTSE funded teams here.
The team published PLANES: Plausibility analysis of epidemiological signals in PLoS One in March, 2025.
Abstract:
Methods for reviewing epidemiological signals are necessary to building and maintaining data-driven public health capabilities. We have developed a novel approach for assessing the plausibility of infectious disease forecasts and surveillance data. The PLANES (PLausibility ANalysis of Epidemiological Signals) methodology is designed to be multi-dimensional and flexible, yielding an overall score based on individual component assessments that can be applied at various temporal and spatial granularities. Here we describe PLANES, provide a demonstration analysis, and discuss how to use the open-source rplanes R package. PLANES aims to enable modelers and public health end-users to evaluate forecast plausibility and surveillance data integrity, ultimately improving early warning systems and informing evidence-based decision-making.
Authors:
V.P. Nagraj1, Amy E. Benefield1, Desiree Williams1, Stephen D. Turner1
1 Signature Science, LLC, 1670 Discovery Drive, Charlottesville, VA, 22901