Identification and evaluation of epidemic prediction and forecasting reporting guidelines: A systematic review and a call for action
Simon Pollett,
Michael Johansson,
Matthew Biggerstaff,
Lindsay C. Morton,
Sara L. Bazaco,
David M. Brett Major,
Anna M. Stewart-Ibarra,
Julie A. Pavlin,
Suzanne Mate,
Rachel Sippy,
Laurie J. Hartman,
Nicholas G. Reich,
Irina Maljkovic Berry,
Jean-Paul Chretien,
Benjamin M. Althouse,
Diane Myer,
Cecile Viboud,
Caitlin Rivers
Affiliations
Simon Pollett
Viral Diseases Branch, Walter Reed Army Institute of Research, MD, USA; Corresponding author at: Johns Hopkins Center for Health Security, MD, USA.
Michael Johansson
Division of Vector-Borne Diseases, Centers for Disease Control & Prevention, San Juan, Puerto Rico, USA
Matthew Biggerstaff
Influenza Division, Centers for Disease Control & Prevention, GA, USA
Lindsay C. Morton
Global Emerging Infections Surveillance, Armed Forces Health Surveillance Division, Silver Spring, MD, USA; Cherokee Nation Strategic Programs, Tulsa, OK, USA; Milken Institute School of Public Health, The George Washington University, Washington, DC, USA
Sara L. Bazaco
Global Emerging Infections Surveillance, Armed Forces Health Surveillance Division, Silver Spring, MD, USA; General Dynamics Information Technology, Falls Church, VA, USA
David M. Brett Major
College of Public Health, University of Nebraska Medical Center, Omaha, NE
Anna M. Stewart-Ibarra
Institute for Global Health and Translational Science, State University of New York Upstate Medical University, Syracuse, NY, USA; InterAmerican Institute for Global Change Research (IAI), Montevideo, Department of Montevideo, Uruguay
Julie A. Pavlin
National Academies of Sciences, Engineering, and Medicine, DC, USA
Suzanne Mate
Emerging Infectious Diseases Branch, Walter Reed Army Institute of Research, MD, USA
Rachel Sippy
Institute for Global Health and Translational Science, State University of New York Upstate Medical University, Syracuse, NY, USA
Laurie J. Hartman
Global Emerging Infections Surveillance, Armed Forces Health Surveillance Division, Silver Spring, MD, USA; Cherokee Nation Strategic Programs, Tulsa, OK, USA
Nicholas G. Reich
University of Massachusetts at Amherst, MA, USA
Irina Maljkovic Berry
Viral Diseases Branch, Walter Reed Army Institute of Research, MD, USA
Jean-Paul Chretien
Department of Defense, MD, USA
Benjamin M. Althouse
University of Washington, WA, USA; Institute for Disease Modeling, Bellevue, WA, USA; New Mexico State University, Las Cruces, NM, USA
Diane Myer
Johns Hopkins Center for Health Security, MD, USA
Cecile Viboud
Fogarty International Center, National Institutes of Health, MD, USA
Introduction: High quality epidemic forecasting and prediction are critical to support response to local, regional and global infectious disease threats. Other fields of biomedical research use consensus reporting guidelines to ensure standardization and quality of research practice among researchers, and to provide a framework for end-users to interpret the validity of study results. The purpose of this study was to determine whether guidelines exist specifically for epidemic forecast and prediction publications. Methods: We undertook a formal systematic review to identify and evaluate any published infectious disease epidemic forecasting and prediction reporting guidelines. This review leveraged a team of 18 investigators from US Government and academic sectors. Results: A literature database search through May 26, 2019, identified 1467 publications (MEDLINE n = 584, EMBASE n = 883), and a grey-literature review identified a further 407 publications, yielding a total 1777 unique publications. A paired-reviewer system screened in 25 potentially eligible publications, of which two were ultimately deemed eligible. A qualitative review of these two published reporting guidelines indicated that neither were specific for epidemic forecasting and prediction, although they described reporting items which may be relevant to epidemic forecasting and prediction studies. Conclusions: This systematic review confirms that no specific guidelines have been published to standardize the reporting of epidemic forecasting and prediction studies. These findings underscore the need to develop such reporting guidelines in order to improve the transparency, quality and implementation of epidemic forecasting and prediction research in operational public health.
