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dc.contributor.authorPollett, Simon
dc.contributor.authorJohansson, Michael A
dc.contributor.authorReich, Nicholas G
dc.contributor.authorBrett-Major, David
dc.contributor.authorDel Valle, Sara Y
dc.contributor.authorVenkatramanan, Srinivasan
dc.contributor.authorLowe, Rachel
dc.contributor.authorPorco, Travis
dc.contributor.authorBerry, Irina Maljkovic
dc.contributor.authorDeshpande, Alina
dc.contributor.authorKraemer, Moritz U G
dc.contributor.authorBlazes, David L
dc.contributor.authorPan-Ngum, Wirichada
dc.contributor.authorVespigiani, Alessandro
dc.contributor.authorMate, Suzanne E
dc.contributor.authorSilal, Sheetal P
dc.contributor.authorKandula, Sasikiran
dc.contributor.authorSippy, Rachel
dc.contributor.authorQuandelacy, Talia M
dc.contributor.authorMorgan, Jeffrey J
dc.contributor.authorBall, Jacob
dc.contributor.authorMorton, Lindsay C
dc.contributor.authorAlthouse, Benjamin M
dc.contributor.authorPavlin, Julie
dc.contributor.authorvan Panhuis, Wilbert
dc.contributor.authorRiley, Steven
dc.contributor.authorBiggerstaff, Matthew
dc.contributor.authorViboud, Cecile
dc.contributor.authorBrady, Oliver
dc.contributor.authorRivers, Caitlin
dc.date.accessioned2022-01-20T15:30:04Z
dc.date.available2022-01-20T15:30:04Z
dc.date.issued2021-10-19
dc.identifier.citationPollett , S , Johansson , M A , Reich , N G , Brett-Major , D , Del Valle , S Y , Venkatramanan , S , Lowe , R , Porco , T , Berry , I M , Deshpande , A , Kraemer , M U G , Blazes , D L , Pan-Ngum , W , Vespigiani , A , Mate , S E , Silal , S P , Kandula , S , Sippy , R , Quandelacy , T M , Morgan , J J , Ball , J , Morton , L C , Althouse , B M , Pavlin , J , van Panhuis , W , Riley , S , Biggerstaff , M , Viboud , C , Brady , O & Rivers , C 2021 , ' Recommended reporting items for epidemic forecasting and prediction research : the EPIFORGE 2020 guidelines ' , PLoS Medicine , vol. 18 , no. 10 , e1003793 . https://doi.org/10.1371/journal.pmed.1003793en
dc.identifier.issn1549-1277
dc.identifier.otherPURE: 277522143
dc.identifier.otherPURE UUID: 480b6145-189d-437f-ae08-332eaaf28d0c
dc.identifier.otherPubMed: 34665805
dc.identifier.otherPubMedCentral: PMC8525759
dc.identifier.otherScopus: 85117437692
dc.identifier.otherORCID: /0000-0003-3617-2093/work/106838514
dc.identifier.urihttps://hdl.handle.net/10023/24719
dc.descriptionFunding: MIDAS Coordination Center and the National Institutes of General Medical Sciences (NIGMS 1U24GM132013) for supporting travel to the face-to-face consensus meeting by members of the Working Group. NGR was supported by the National Institutes of General Medical Sciences (R35GM119582). Travel for SV was supported by the National Institutes of General Medical Sciences (1U24GM132013-01). BMA was supported by Bill & Melinda Gates through the Global Good Fund. RL was funded by a Royal Society Dorothy Hodgkin Fellowship.en
dc.description.abstractBackground  The importance of infectious disease epidemic forecasting and prediction research is underscored by decades of communicable disease outbreaks, including COVID-19. Unlike other fields of medical research, such as clinical trials and systematic reviews, no reporting guidelines exist for reporting epidemic forecasting and prediction research despite their utility. We therefore developed the EPIFORGE checklist, a guideline for standardized reporting of epidemic forecasting research. Methods and findings  We developed this checklist using a best-practice process for development of reporting guidelines, involving a Delphi process and broad consultation with an international panel of infectious disease modelers and model end users. The objectives of these guidelines are to improve the consistency, reproducibility, comparability, and quality of epidemic forecasting reporting. The guidelines are not designed to advise scientists on how to perform epidemic forecasting and prediction research, but rather to serve as a standard for reporting critical methodological details of such studies. Conclusions  These guidelines have been submitted to the EQUATOR network, in addition to hosting by other dedicated webpages to facilitate feedback and journal endorsement.
dc.format.extent12
dc.language.isoeng
dc.relation.ispartofPLoS Medicineen
dc.rightsThis is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.en
dc.subjectBiomedical research/methodsen
dc.subjectCOVID-19/epidemiologyen
dc.subjectChecklist/methodsen
dc.subjectCommunicable diseases/epidemiologyen
dc.subjectEpidemics/statistics & numerical dataen
dc.subjectForecasting/methodsen
dc.subjectGuidelines as topic/standardsen
dc.subjectHumansen
dc.subjectReproducibility of resultsen
dc.subjectResearch designen
dc.subjectRA0421 Public health. Hygiene. Preventive Medicineen
dc.subjectNDASen
dc.subjectSDG 3 - Good Health and Well-beingen
dc.subject.lccRA0421en
dc.titleRecommended reporting items for epidemic forecasting and prediction research : the EPIFORGE 2020 guidelinesen
dc.typeJournal articleen
dc.description.versionPublisher PDFen
dc.contributor.institutionUniversity of St Andrews. Statisticsen
dc.identifier.doihttps://doi.org/10.1371/journal.pmed.1003793
dc.description.statusNon peer revieweden


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