Evidence map›Paper›PMID 33130412›Full record

SynthesisEpidemics2020

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 and 8 more

Abstract readSystematic Review
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in Epidemics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. How to avoid a local epidemic becoming a global pandemic.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  4. Predicting Infectious Diseases: A Bibliometric Review on Africa.International journal of environmental research and public health · 2022
    Review
  5. Article
  6. Article
  7. Article
  8. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

18 authors.

Simon PollettViral Diseases Branch, Walter Reed Army Institute of Research, MD, USA. Electronic address: simon.d.pollett.ctr@mail.mil.
Michael JohanssonDivision of Vector-Borne Diseases, Centers for Disease Control & Prevention, San Juan, Puerto Rico, USA.
Matthew BiggerstaffInfluenza Division, Centers for Disease Control & Prevention, GA, USA.
Lindsay C MortonGlobal 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 BazacoGlobal Emerging Infections Surveillance, Armed Forces Health Surveillance Division, Silver Spring, MD, USA; General Dynamics Information Technology, Falls Church, VA, USA.
David M Brett MajorCollege of Public Health, University of Nebraska Medical Center, Omaha, NE.
Anna M Stewart-IbarraInstitute 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 PavlinNational Academies of Sciences, Engineering, and Medicine, DC, USA.
Suzanne MateEmerging Infectious Diseases Branch, Walter Reed Army Institute of Research, MD, USA.
Rachel SippyInstitute for Global Health and Translational Science, State University of New York Upstate Medical University, Syracuse, NY, USA.
Laurie J HartmanGlobal Emerging Infections Surveillance, Armed Forces Health Surveillance Division, Silver Spring, MD, USA; Cherokee Nation Strategic Programs, Tulsa, OK, USA.
Nicholas G ReichUniversity of Massachusetts at Amherst, MA, USA.
Irina Maljkovic BerryViral Diseases Branch, Walter Reed Army Institute of Research, MD, USA.
Jean-Paul ChretienDepartment of Defense, MD, USA.
Benjamin M AlthouseUniversity of Washington, WA, USA; Institute for Disease Modeling, Bellevue, WA, USA; New Mexico State University, Las Cruces, NM, USA.
Diane MyerJohns Hopkins Center for Health Security, MD, USA.
Cecile ViboudFogarty International Center, National Institutes of Health, MD, USA.
Caitlin RiversJohns Hopkins Center for Health Security, MD, USA. Electronic address: crivers6@jhu.edu.

Funding

Statistical methods for real-time forecasts of infectious disease: expanding dynamic time-series and machine learning approaches for pandemic scenariosR35GM119582 · NIGMS · UNIVERSITY OF MASSACHUSETTS AMHERST · PI Nicholas G Reich · 2016 to 2026
$4.8M
NIGMS NIH HHS R35 GM119582
6 · The paper itself

Abstract

introductionHigh 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.

methodsWe 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.

resultsA 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.

conclusionsThis 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.

Indexed as

EpidemicsCommunicable DiseasesDisease NotificationForecastingGuidelines as TopicHumansPublic HealthEpidemicForecastingModelingOutbreakPredictionReporting guidelines

Identifiers

PMID33130412
PMCPMC8667087

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.