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

doi:10.1016/j.epidem.2020.100400

Identification and evaluation of epidemic prediction and forecasting reporting guidelines: A systematic review and a call for action

Epidemics. 2020 Dec:33:100400. doi: 10.1016/j.epidem.2020.100400. Epub 2020 Jul 9.

Authors

Simon Pollett¹, Michael Johansson², Matthew Biggerstaff³, Lindsay C Morton⁴, Sara L Bazaco⁵, David M Brett Major⁶, Anna M Stewart-Ibarra⁷, Julie A Pavlin⁸, Suzanne Mate⁹, Rachel Sippy¹⁰, Laurie J Hartman¹¹, Nicholas G Reich¹², Irina Maljkovic Berry¹³, Jean-Paul Chretien¹⁴, Benjamin M Althouse¹⁵, Diane Myer¹⁶, Cecile Viboud¹⁷, Caitlin Rivers¹⁸

Affiliations

¹ Viral Diseases Branch, Walter Reed Army Institute of Research, MD, USA. Electronic address: simon.d.pollett.ctr@mail.mil.
² Division of Vector-Borne Diseases, Centers for Disease Control & Prevention, San Juan, Puerto Rico, USA.
³ Influenza Division, Centers for Disease Control & Prevention, GA, USA.
⁴ 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.
⁵ Global Emerging Infections Surveillance, Armed Forces Health Surveillance Division, Silver Spring, MD, USA; General Dynamics Information Technology, Falls Church, VA, USA.
⁶ College of Public Health, University of Nebraska Medical Center, Omaha, NE.
⁷ 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.
⁸ National Academies of Sciences, Engineering, and Medicine, DC, USA.
⁹ Emerging Infectious Diseases Branch, Walter Reed Army Institute of Research, MD, USA.
¹⁰ Institute for Global Health and Translational Science, State University of New York Upstate Medical University, Syracuse, NY, USA.
¹¹ Global Emerging Infections Surveillance, Armed Forces Health Surveillance Division, Silver Spring, MD, USA; Cherokee Nation Strategic Programs, Tulsa, OK, USA.
¹² University of Massachusetts at Amherst, MA, USA.
¹³ Viral Diseases Branch, Walter Reed Army Institute of Research, MD, USA.
¹⁴ Department of Defense, MD, USA.
¹⁵ University of Washington, WA, USA; Institute for Disease Modeling, Bellevue, WA, USA; New Mexico State University, Las Cruces, NM, USA.
¹⁶ Johns Hopkins Center for Health Security, MD, USA.
¹⁷ Fogarty International Center, National Institutes of Health, MD, USA.
¹⁸ Johns Hopkins Center for Health Security, MD, USA. Electronic address: crivers6@jhu.edu.

Abstract

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.

Keywords: Epidemic; Forecasting; Modeling; Outbreak; Prediction; Reporting guidelines.

Publication types

Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.
Systematic Review

MeSH terms

Communicable Diseases
Disease Notification / methods*
Disease Notification / statistics & numerical data
Epidemics*
Forecasting
Guidelines as Topic
Humans
Public Health

Grants and funding

R35 GM119582/GM/NIGMS NIH HHS/United States