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Chimeric forecasting: combining probabilistic predictions from computational models and human judgment

Forecasts of the trajectory of an infectious agent can help guide public health decision making. A traditional approach to forecasting fits a computational model to structured data and generates a predictive distribution. However, human judgment has access to the same data as computational models pl...

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Autores principales: McAndrew, Thomas, Codi, Allison, Cambeiro, Juan, Besiroglu, Tamay, Braun, David, Chen, Eva, De Cèsaris, Luis Enrique Urtubey, Luk, Damon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9648897/
https://www.ncbi.nlm.nih.gov/pubmed/36357829
http://dx.doi.org/10.1186/s12879-022-07794-5
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author McAndrew, Thomas
Codi, Allison
Cambeiro, Juan
Besiroglu, Tamay
Braun, David
Chen, Eva
De Cèsaris, Luis Enrique Urtubey
Luk, Damon
author_facet McAndrew, Thomas
Codi, Allison
Cambeiro, Juan
Besiroglu, Tamay
Braun, David
Chen, Eva
De Cèsaris, Luis Enrique Urtubey
Luk, Damon
author_sort McAndrew, Thomas
collection PubMed
description Forecasts of the trajectory of an infectious agent can help guide public health decision making. A traditional approach to forecasting fits a computational model to structured data and generates a predictive distribution. However, human judgment has access to the same data as computational models plus experience, intuition, and subjective data. We propose a chimeric ensemble—a combination of computational and human judgment forecasts—as a novel approach to predicting the trajectory of an infectious agent. Each month from January, 2021 to June, 2021 we asked two generalist crowds, using the same criteria as the COVID-19 Forecast Hub, to submit a predictive distribution over incident cases and deaths at the US national level either two or three weeks into the future and combined these human judgment forecasts with forecasts from computational models submitted to the COVID-19 Forecasthub into a chimeric ensemble. We find a chimeric ensemble compared to an ensemble including only computational models improves predictions of incident cases and shows similar performance for predictions of incident deaths. A chimeric ensemble is a flexible, supportive public health tool and shows promising results for predictions of the spread of an infectious agent. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12879-022-07794-5.
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spelling pubmed-96488972022-11-14 Chimeric forecasting: combining probabilistic predictions from computational models and human judgment McAndrew, Thomas Codi, Allison Cambeiro, Juan Besiroglu, Tamay Braun, David Chen, Eva De Cèsaris, Luis Enrique Urtubey Luk, Damon BMC Infect Dis Research Forecasts of the trajectory of an infectious agent can help guide public health decision making. A traditional approach to forecasting fits a computational model to structured data and generates a predictive distribution. However, human judgment has access to the same data as computational models plus experience, intuition, and subjective data. We propose a chimeric ensemble—a combination of computational and human judgment forecasts—as a novel approach to predicting the trajectory of an infectious agent. Each month from January, 2021 to June, 2021 we asked two generalist crowds, using the same criteria as the COVID-19 Forecast Hub, to submit a predictive distribution over incident cases and deaths at the US national level either two or three weeks into the future and combined these human judgment forecasts with forecasts from computational models submitted to the COVID-19 Forecasthub into a chimeric ensemble. We find a chimeric ensemble compared to an ensemble including only computational models improves predictions of incident cases and shows similar performance for predictions of incident deaths. A chimeric ensemble is a flexible, supportive public health tool and shows promising results for predictions of the spread of an infectious agent. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12879-022-07794-5. BioMed Central 2022-11-10 /pmc/articles/PMC9648897/ /pubmed/36357829 http://dx.doi.org/10.1186/s12879-022-07794-5 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
McAndrew, Thomas
Codi, Allison
Cambeiro, Juan
Besiroglu, Tamay
Braun, David
Chen, Eva
De Cèsaris, Luis Enrique Urtubey
Luk, Damon
Chimeric forecasting: combining probabilistic predictions from computational models and human judgment
title Chimeric forecasting: combining probabilistic predictions from computational models and human judgment
title_full Chimeric forecasting: combining probabilistic predictions from computational models and human judgment
title_fullStr Chimeric forecasting: combining probabilistic predictions from computational models and human judgment
title_full_unstemmed Chimeric forecasting: combining probabilistic predictions from computational models and human judgment
title_short Chimeric forecasting: combining probabilistic predictions from computational models and human judgment
title_sort chimeric forecasting: combining probabilistic predictions from computational models and human judgment
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9648897/
https://www.ncbi.nlm.nih.gov/pubmed/36357829
http://dx.doi.org/10.1186/s12879-022-07794-5
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