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dc.contributor.authorCoughlan de Perez, Erin
dc.contributor.authorStephens, Elisabeth
dc.contributor.authorvan Aalst, Maarten
dc.contributor.authorBazo, Juan
dc.contributor.authorFournier Tombs, Eleonore
dc.contributor.authorFunk, Sebastian
dc.contributor.authorHess, Jeremy J.
dc.contributor.authorRanger, Nicola
dc.contributor.authorLowe, Rachel
dc.contributor.otherBarcelona Supercomputing Center
dc.date.accessioned2021-10-27T14:42:07Z
dc.date.available2021-10-27T14:42:07Z
dc.date.issued2021
dc.identifier.citationCoughlan de Perez, E. [et al.]. Epidemiological versus meteorological forecasts: Best practice for linking models to policymaking. "International Journal of Forecasting", 2021,
dc.identifier.issn0169-2070
dc.identifier.urihttp://hdl.handle.net/2117/354772
dc.description.abstractWeather forecasts, climate change projections, and epidemiological predictions all represent domains that are using forecast data to take early action for risk management. However, the methods and applications of the modeling efforts in each of these three fields have been developed and applied with little cross-fertilization. This perspective identifies best practices in each domain that can be adopted by the others, which can be used to inform each field separately as well as to facilitate a more effective combined use for the management of compound and evolving risks. In light of increased attention to predictive modeling during the COVID-19 pandemic, we identify three major areas that all three of these modeling fields should prioritize for future investment and improvement: (1) decision support, (2) conveying uncertainty, and (3) capturing vulnerability.
dc.description.sponsorshipE Stephens and E Coughlan de Perez acknowledge support from the UK’s Natural Environment Research Council (NERC) and Foreign, Commonwealth and Development Office through the FATHUM (Forecasts for AnTicipatory HUManitarian action, grant number NE/P000525/1) project, part of the Science for Humanitarian Emergencies and Resilience (SHEAR) research programme. R Lowe was supported by a Royal Society Dorothy Hodgkin Fellowship. S Funk is funded by the Wellcome Trust (210758/Z/18/Z).
dc.format.extent6 p.
dc.language.isoeng
dc.publisherElsevier
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Spain
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectÀrees temàtiques de la UPC::Enginyeria agroalimentària::Ciències de la terra i de la vida::Climatologia i meteorologia
dc.subject.lcshCOVID-19 (Disease)
dc.subject.lcshPolicymaking
dc.subject.lcshClimate change--Health aspects
dc.subject.otherForecasting
dc.subject.otherCOVID-19
dc.subject.otherWeather
dc.subject.otherClimate
dc.subject.otherDisasters
dc.subject.otherRisk
dc.subject.otherCommunication
dc.subject.otherVulnerability
dc.subject.otherUncertainty
dc.titleEpidemiological versus meteorological forecasts: Best practice for linking models to policymaking
dc.typeArticle
dc.subject.lemacCOVID-19 (Malaltia)
dc.identifier.doi10.1016/j.ijforecast.2021.08.003
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/pii/S0169207021001254?via%3Dihub#!
dc.rights.accessOpen Access
dc.description.versionPostprint (published version)
local.citation.publicationNameInternational Journal of Forecasting


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