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

doi:10.1016/j.epidem.2020.100400

. 2020 Dec:33:100400.

doi: 10.1016/j.epidem.2020.100400. Epub 2020 Jul 9.

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

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.

PMID: 33130412
PMCID: PMC8667087
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

Simon Pollett et al. Epidemics. 2020 Dec.

. 2020 Dec:33:100400.

doi: 10.1016/j.epidem.2020.100400. Epub 2020 Jul 9.

Authors

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.

PMID: 33130412
PMCID: PMC8667087
DOI: 10.1016/j.epidem.2020.100400

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.

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Conflict of interest statement

Declaration of Competing Interest

The authors declare no conflicts of interest.

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References

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[1] www.equator-network.org accessed Oct 04 2019.

[2] www.equator-network.org accessed Oct 04 2019.

[3] https://www.equator-network.org/toolkits/developing-a-reporting-guideline/, accessed Oct 04 2019.

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[8] www.consort-statement.org accessed Oct 04 2019.

[9] https://strobe-statement.org accessed Oct 04 2019.

[10] https://strobe-statement.org accessed Oct 04 2019.

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

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

Authors

Affiliations

Abstract

Conflict of interest statement

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