Characterising information gains and losses when collecting multiple epidemic model outputs

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 probabilisti...

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Autors principals:	Katharine Sherratt, Ajitesh Srivastava, Kylie Ainslie, David E. Singh, Aymar Cublier, Maria Cristina Marinescu, Jesus Carretero, Alberto Cascajo Garcia, Nicolas Franco, Lander Willem, Steven Abrams, Christel Faes, Philippe Beutels, Niel Hens, Sebastian Müller, Billy Charlton, Ricardo Ewert, Sydney Paltra, Christian Rakow, Jakob Rehmann, Tim Conrad, Christof Schütte, Kai Nagel, Sam Abbott, Rok Grah, Rene Niehus, Bastian Prasse, Frank Sandmann, Sebastian Funk
Format:	Artigo
Idioma:	Inglês
Publicat:	Elsevier 2024-06-01
Col·lecció:	Epidemics
Matèries:	Information Scenarios Uncertainty Aggregation Modelling
Accés en línia:	http://www.sciencedirect.com/science/article/pii/S1755436524000264
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