Characterising information gains and losses when collecting multiple epidemic model outputs.

ABSTRACT:

Background

Collaborative comparisons and combinations of epidemic models are used as policy-relevant evidence during epidemic outbreaks. In the process of collecting multiple model projections, such collaborations may gain or lose relevant information. Typically, modellers contribute a probabilistic summary at each time-step. We compared this to directly collecting simulated trajectories. We aimed to explore information on key epidemic quantities; ensemble uncertainty; and performance against data, investigating potential to continuously gain information from a single cross-sectional collection of model results.

Methods

We compared projections from the European COVID-19 Scenario Modelling Hub. Five teams modelled incidence in Belgium, the Netherlands, and Spain. We compared

SUBMITTER: Sherratt K 

PROVIDER: S-EPMC11196924 | biostudies-literature | 2024 Jun

REPOSITORIES: biostudies-literature