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

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 researcher...

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Autores principales: Pollett, Simon, Johansson, Michael, Biggerstaff, Matthew, Morton, Lindsay C., Bazaco, Sara L., Major, David M. Brett, Stewart-Ibarra, Anna M., Pavlin, Julie A., Mate, Suzanne, Sippy, Rachel, Hartman, Laurie J., Reich, Nicholas G., Berry, Irina Maljkovic, Chretien, Jean-Paul, Althouse, Benjamin M., Myer, Diane, Viboud, Cecile, Rivers, Caitlin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8667087/
https://www.ncbi.nlm.nih.gov/pubmed/33130412
http://dx.doi.org/10.1016/j.epidem.2020.100400
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author Pollett, Simon
Johansson, Michael
Biggerstaff, Matthew
Morton, Lindsay C.
Bazaco, Sara L.
Major, David M. Brett
Stewart-Ibarra, Anna M.
Pavlin, Julie A.
Mate, Suzanne
Sippy, Rachel
Hartman, Laurie J.
Reich, Nicholas G.
Berry, Irina Maljkovic
Chretien, Jean-Paul
Althouse, Benjamin M.
Myer, Diane
Viboud, Cecile
Rivers, Caitlin
author_facet Pollett, Simon
Johansson, Michael
Biggerstaff, Matthew
Morton, Lindsay C.
Bazaco, Sara L.
Major, David M. Brett
Stewart-Ibarra, Anna M.
Pavlin, Julie A.
Mate, Suzanne
Sippy, Rachel
Hartman, Laurie J.
Reich, Nicholas G.
Berry, Irina Maljkovic
Chretien, Jean-Paul
Althouse, Benjamin M.
Myer, Diane
Viboud, Cecile
Rivers, Caitlin
author_sort Pollett, Simon
collection PubMed
description 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.
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spelling pubmed-86670872021-12-13 Identification and evaluation of epidemic prediction and forecasting reporting guidelines: A systematic review and a call for action Pollett, Simon Johansson, Michael Biggerstaff, Matthew Morton, Lindsay C. Bazaco, Sara L. Major, David M. Brett Stewart-Ibarra, Anna M. Pavlin, Julie A. Mate, Suzanne Sippy, Rachel Hartman, Laurie J. Reich, Nicholas G. Berry, Irina Maljkovic Chretien, Jean-Paul Althouse, Benjamin M. Myer, Diane Viboud, Cecile Rivers, Caitlin Epidemics Article 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. 2020-07-09 2020-12 /pmc/articles/PMC8667087/ /pubmed/33130412 http://dx.doi.org/10.1016/j.epidem.2020.100400 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) ).
spellingShingle Article
Pollett, Simon
Johansson, Michael
Biggerstaff, Matthew
Morton, Lindsay C.
Bazaco, Sara L.
Major, David M. Brett
Stewart-Ibarra, Anna M.
Pavlin, Julie A.
Mate, Suzanne
Sippy, Rachel
Hartman, Laurie J.
Reich, Nicholas G.
Berry, Irina Maljkovic
Chretien, Jean-Paul
Althouse, Benjamin M.
Myer, Diane
Viboud, Cecile
Rivers, Caitlin
Identification and evaluation of epidemic prediction and forecasting reporting guidelines: A systematic review and a call for action
title Identification and evaluation of epidemic prediction and forecasting reporting guidelines: A systematic review and a call for action
title_full Identification and evaluation of epidemic prediction and forecasting reporting guidelines: A systematic review and a call for action
title_fullStr Identification and evaluation of epidemic prediction and forecasting reporting guidelines: A systematic review and a call for action
title_full_unstemmed Identification and evaluation of epidemic prediction and forecasting reporting guidelines: A systematic review and a call for action
title_short Identification and evaluation of epidemic prediction and forecasting reporting guidelines: A systematic review and a call for action
title_sort identification and evaluation of epidemic prediction and forecasting reporting guidelines: a systematic review and a call for action
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8667087/
https://www.ncbi.nlm.nih.gov/pubmed/33130412
http://dx.doi.org/10.1016/j.epidem.2020.100400
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