학술논문
Recommended reporting items for epidemic forecasting and prediction research: The EPIFORGE 2020 guidelines.
Document Type
Academic Journal
Author
Pollett S; Walter Reed Army Institute of Research, Silver Spring, Maryland, United States of America.; Johansson MA; Division of Vector-Borne Diseases, Centers for Disease Control & Prevention, San Juan, Puerto Rico, United States of America.; Reich NG; University of Massachusetts-Amherst, School of Public Health and Health Sciences, Amherst, Massachusetts, United States of America.; Brett-Major D; University of Nebraska Medical Center, Omaha, Nebraska, United States of America.; Del Valle SY; Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.; Venkatramanan S; Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, Virginia, United States of America.; Lowe R; Centre for Mathematical Modelling of Infectious Diseases and Centre on Climate Change and Planetary Health, London School of Hygiene & Tropical Medicine, London, United Kingdom.; Barcelona Institute for Global Health, Barcelona, Spain.; Porco T; University of California at San Francisco, San Francisco, California, United States of America.; Berry IM; Walter Reed Army Institute of Research, Silver Spring, Maryland, United States of America.; Deshpande A; Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.; Kraemer MUG; Department of Zoology, University of Oxford, Oxford, United Kingdom.; Blazes DL; Bill and Melinda Gates Foundation, Seattle, Washington, United States of America.; Pan-Ngum W; Mahidol-Oxford Tropical Medicine Research Unit and Department of Tropical Hygiene, Mahidol University, Thailand.; Vespigiani A; Network Science Institute, Northeastern University, Boston, Massachusetts, United States of America.; Mate SE; Walter Reed Army Institute of Research, Silver Spring, Maryland, United States of America.; Silal SP; Modelling and Simulation Hub, Africa, Department of Statistical Sciences, University of Cape Town, Cape Town, South Africa.; Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom.; Kandula S; Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York City, New York, United States of America.; Sippy R; Institute for Global Health and Translational Science, State University of New York Upstate Medical University, Syracuse, New York, United States of America.; Quandelacy TM; Division of Vector-Borne Diseases, Centers for Disease Control & Prevention, San Juan, Puerto Rico, United States of America.; Morgan JJ; Catholic University of America, Washington, DC, United States of America.; Ball J; U.S. Army Public Health Center, Edgewood, Maryland, United States of America.; Morton LC; Armed Forces Health Surveillance Division, Global Emerging Infections Surveillance, Silver Spring, Maryland, United States of America.; George Washington University, Milken Institute School of Public Health, Washington, DC, United States of America.; Althouse BM; University of Washington, Seattle, Washington, United States of America.; Institute for Disease Modeling, Bellevue, Washington, United States of America.; New Mexico State University, Las Cruces, New Mexico, United States of America.; Pavlin J; National Academies of Sciences, Engineering, and Medicine, Washington, DC, United States of America.; van Panhuis W; University of Pittsburgh Graduate School of Public Health, Pittsburgh, Pennsylvania, United States of America.; Riley S; MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College, London, United Kingdom.; Biggerstaff M; Influenza Division, Centers for Disease Control & Prevention, Atlanta, Georgia, United States of America.; Viboud C; Fogarty International Center, National Institutes for Health, Bethesda, Maryland, United States of America.; Brady O; Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom.; Rivers C; Johns Hopkins Center for Health Security, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America.
Source
Publisher: Public Library of Science Country of Publication: United States NLM ID: 101231360 Publication Model: eCollection Cited Medium: Internet ISSN: 1549-1676 (Electronic) Linking ISSN: 15491277 NLM ISO Abbreviation: PLoS Med Subsets: MEDLINE
Subject
Language
English
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.
Competing Interests: The authors have declared that no competing interests exist.
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.
Competing Interests: The authors have declared that no competing interests exist.