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