Publication: Recommended reporting items for epidemic forecasting and prediction research: The EPIFORGE 2020 guidelines
Issued Date
2021-10-01
Resource Type
ISSN
15491676
15491277
15491277
Other identifier(s)
2-s2.0-85117437692
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Mahidol University
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SCOPUS
Bibliographic Citation
PLoS Medicine. Vol.18, No.10 (2021)
Suggested Citation
Simon Pollett, Michael A. Johansson, Nicholas G. Reich, David Brett-Major, Sara Y. Del Valle, Srinivasan Venkatramanan, Rachel Lowe, Travis Porco, Irina Maljkovic Berry, Alina Deshpande, Moritz U.G. Kraemer, David L. Blazes, Wirichada Pan-Ngum, Alessandro Vespigiani, Suzanne E. Mate, Sheetal P. Silal, Sasikiran Kandula, Rachel Sippy, Talia M. Quandelacy, Jeffrey J. Morgan, Jacob Ball, Lindsay C. Morton, Benjamin M. Althouse, Julie Pavlin, Wilbert van Panhuis, Steven Riley, Matthew Biggerstaff, Cecile Viboud, Oliver Brady, Caitlin Rivers Recommended reporting items for epidemic forecasting and prediction research: The EPIFORGE 2020 guidelines. PLoS Medicine. Vol.18, No.10 (2021). doi:10.1371/journal.pmed.1003793 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/77798
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Title
Recommended reporting items for epidemic forecasting and prediction research: The EPIFORGE 2020 guidelines
Author(s)
Simon Pollett
Michael A. Johansson
Nicholas G. Reich
David Brett-Major
Sara Y. Del Valle
Srinivasan Venkatramanan
Rachel Lowe
Travis Porco
Irina Maljkovic Berry
Alina Deshpande
Moritz U.G. Kraemer
David L. Blazes
Wirichada Pan-Ngum
Alessandro Vespigiani
Suzanne E. Mate
Sheetal P. Silal
Sasikiran Kandula
Rachel Sippy
Talia M. Quandelacy
Jeffrey J. Morgan
Jacob Ball
Lindsay C. Morton
Benjamin M. Althouse
Julie Pavlin
Wilbert van Panhuis
Steven Riley
Matthew Biggerstaff
Cecile Viboud
Oliver Brady
Caitlin Rivers
Michael A. Johansson
Nicholas G. Reich
David Brett-Major
Sara Y. Del Valle
Srinivasan Venkatramanan
Rachel Lowe
Travis Porco
Irina Maljkovic Berry
Alina Deshpande
Moritz U.G. Kraemer
David L. Blazes
Wirichada Pan-Ngum
Alessandro Vespigiani
Suzanne E. Mate
Sheetal P. Silal
Sasikiran Kandula
Rachel Sippy
Talia M. Quandelacy
Jeffrey J. Morgan
Jacob Ball
Lindsay C. Morton
Benjamin M. Althouse
Julie Pavlin
Wilbert van Panhuis
Steven Riley
Matthew Biggerstaff
Cecile Viboud
Oliver Brady
Caitlin Rivers
Other Contributor(s)
Institute for Disease Modeling
Instituto de Salud Global de Barcelona
National Center for Emerging and Zoonotic Infectious Diseases
Milken Institute School of Public Health
London School of Hygiene & Tropical Medicine
Northeastern University
Fogarty International Center (FIC)
University of Oxford
University of California, San Francisco
Bill and Melinda Gates Foundation
University of Virginia
Centers for Disease Control and Prevention
Catholic University of America
Imperial College Faculty of Medicine
SUNY Upstate Medical University
National Academies of Sciences, Engineering, and Medicine
University of Nebraska Medical Center
University of Washington
University of Massachusetts Amherst
Walter Reed Army Institute of Research
Mailman School of Public Health
Mahidol University
Nuffield Department of Medicine
Johns Hopkins Bloomberg School of Public Health
Los Alamos National Laboratory
University of Pittsburgh Graduate School of Public Health
New Mexico State University
University of Cape Town
U.S. Army Public Health Center
Armed Forces Health Surveillance Center
Instituto de Salud Global de Barcelona
National Center for Emerging and Zoonotic Infectious Diseases
Milken Institute School of Public Health
London School of Hygiene & Tropical Medicine
Northeastern University
Fogarty International Center (FIC)
University of Oxford
University of California, San Francisco
Bill and Melinda Gates Foundation
University of Virginia
Centers for Disease Control and Prevention
Catholic University of America
Imperial College Faculty of Medicine
SUNY Upstate Medical University
National Academies of Sciences, Engineering, and Medicine
University of Nebraska Medical Center
University of Washington
University of Massachusetts Amherst
Walter Reed Army Institute of Research
Mailman School of Public Health
Mahidol University
Nuffield Department of Medicine
Johns Hopkins Bloomberg School of Public Health
Los Alamos National Laboratory
University of Pittsburgh Graduate School of Public Health
New Mexico State University
University of Cape Town
U.S. Army Public Health Center
Armed Forces Health Surveillance Center
Abstract
Background 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.