Work

PLANES: Plausibility analysis of epidemiological signals

Year: 2025

Type: article

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.

Source: PLoS ONE

DOI: 10.1371/journal.pone.0320442

Authors: VP Nagraj, Amy E. Benefield, Desiree Williams, Stephen D. Turner

Language: English

Topic: Data-Driven Disease Surveillance

Subfield: Epidemiology

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $2,382

Funder: Council of State and Territorial Epidemiologists