Publication:
Recommended reporting items for epidemic forecasting and prediction research: The EPIFORGE 2020 guidelines

dc.contributor.authorSimon Polletten_US
dc.contributor.authorMichael A. Johanssonen_US
dc.contributor.authorNicholas G. Reichen_US
dc.contributor.authorDavid Brett-Majoren_US
dc.contributor.authorSara Y. Del Valleen_US
dc.contributor.authorSrinivasan Venkatramananen_US
dc.contributor.authorRachel Loween_US
dc.contributor.authorTravis Porcoen_US
dc.contributor.authorIrina Maljkovic Berryen_US
dc.contributor.authorAlina Deshpandeen_US
dc.contributor.authorMoritz U.G. Kraemeren_US
dc.contributor.authorDavid L. Blazesen_US
dc.contributor.authorWirichada Pan-Ngumen_US
dc.contributor.authorAlessandro Vespigianien_US
dc.contributor.authorSuzanne E. Mateen_US
dc.contributor.authorSheetal P. Silalen_US
dc.contributor.authorSasikiran Kandulaen_US
dc.contributor.authorRachel Sippyen_US
dc.contributor.authorTalia M. Quandelacyen_US
dc.contributor.authorJeffrey J. Morganen_US
dc.contributor.authorJacob Ballen_US
dc.contributor.authorLindsay C. Mortonen_US
dc.contributor.authorBenjamin M. Althouseen_US
dc.contributor.authorJulie Pavlinen_US
dc.contributor.authorWilbert van Panhuisen_US
dc.contributor.authorSteven Rileyen_US
dc.contributor.authorMatthew Biggerstaffen_US
dc.contributor.authorCecile Vibouden_US
dc.contributor.authorOliver Bradyen_US
dc.contributor.authorCaitlin Riversen_US
dc.contributor.otherInstitute for Disease Modelingen_US
dc.contributor.otherInstituto de Salud Global de Barcelonaen_US
dc.contributor.otherNational Center for Emerging and Zoonotic Infectious Diseasesen_US
dc.contributor.otherMilken Institute School of Public Healthen_US
dc.contributor.otherLondon School of Hygiene & Tropical Medicineen_US
dc.contributor.otherNortheastern Universityen_US
dc.contributor.otherFogarty International Center (FIC)en_US
dc.contributor.otherUniversity of Oxforden_US
dc.contributor.otherUniversity of California, San Franciscoen_US
dc.contributor.otherBill and Melinda Gates Foundationen_US
dc.contributor.otherUniversity of Virginiaen_US
dc.contributor.otherCenters for Disease Control and Preventionen_US
dc.contributor.otherCatholic University of Americaen_US
dc.contributor.otherImperial College Faculty of Medicineen_US
dc.contributor.otherSUNY Upstate Medical Universityen_US
dc.contributor.otherNational Academies of Sciences, Engineering, and Medicineen_US
dc.contributor.otherUniversity of Nebraska Medical Centeren_US
dc.contributor.otherUniversity of Washingtonen_US
dc.contributor.otherUniversity of Massachusetts Amhersten_US
dc.contributor.otherWalter Reed Army Institute of Researchen_US
dc.contributor.otherMailman School of Public Healthen_US
dc.contributor.otherMahidol Universityen_US
dc.contributor.otherNuffield Department of Medicineen_US
dc.contributor.otherJohns Hopkins Bloomberg School of Public Healthen_US
dc.contributor.otherLos Alamos National Laboratoryen_US
dc.contributor.otherUniversity of Pittsburgh Graduate School of Public Healthen_US
dc.contributor.otherNew Mexico State Universityen_US
dc.contributor.otherUniversity of Cape Townen_US
dc.contributor.otherU.S. Army Public Health Centeren_US
dc.contributor.otherArmed Forces Health Surveillance Centeren_US
dc.date.accessioned2022-08-04T09:10:43Z
dc.date.available2022-08-04T09:10:43Z
dc.date.issued2021-10-01en_US
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.en_US
dc.identifier.citationPLoS Medicine. Vol.18, No.10 (2021)en_US
dc.identifier.doi10.1371/journal.pmed.1003793en_US
dc.identifier.issn15491676en_US
dc.identifier.issn15491277en_US
dc.identifier.other2-s2.0-85117437692en_US
dc.identifier.urihttps://repository.li.mahidol.ac.th/handle/20.500.14594/77798
dc.rightsMahidol Universityen_US
dc.rights.holderSCOPUSen_US
dc.source.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85117437692&origin=inwarden_US
dc.subjectMedicineen_US
dc.titleRecommended reporting items for epidemic forecasting and prediction research: The EPIFORGE 2020 guidelinesen_US
dc.typeArticleen_US
dspace.entity.typePublication
mu.datasource.scopushttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85117437692&origin=inwarden_US

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