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Scenario Design for Infectious Disease Projections: Integrating Concepts from Decision Analysis and Experimental Design
Across many fields, scenario modeling has become an important tool for exploring long-term projections and how they might depend on potential interventions and critical uncertainties, with relevance to both decision makers and scientists. In the past decade, and especially during the COVID-19 pandem...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cold Spring Harbor Laboratory
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10592999/ https://www.ncbi.nlm.nih.gov/pubmed/37873156 http://dx.doi.org/10.1101/2023.10.11.23296887 |
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author | Runge, Michael C. Shea, Katriona Howerton, Emily Yan, Katie Hochheiser, Harry Rosenstrom, Erik Probert, William J.M. Borchering, Rebecca Marathe, Madhav V Lewis, Bryan Venkatramanan, Srinivasan Truelove, Shaun Lessler, Justin Viboud, Cécile |
author_facet | Runge, Michael C. Shea, Katriona Howerton, Emily Yan, Katie Hochheiser, Harry Rosenstrom, Erik Probert, William J.M. Borchering, Rebecca Marathe, Madhav V Lewis, Bryan Venkatramanan, Srinivasan Truelove, Shaun Lessler, Justin Viboud, Cécile |
author_sort | Runge, Michael C. |
collection | PubMed |
description | Across many fields, scenario modeling has become an important tool for exploring long-term projections and how they might depend on potential interventions and critical uncertainties, with relevance to both decision makers and scientists. In the past decade, and especially during the COVID-19 pandemic, the field of epidemiology has seen substantial growth in the use of scenario projections. Multiple scenarios are often projected at the same time, allowing important comparisons that can guide the choice of intervention, the prioritization of research topics, or public communication. The design of the scenarios is central to their ability to inform important questions. In this paper, we draw on the fields of decision analysis and statistical design of experiments to propose a framework for scenario design in epidemiology, with relevance also to other fields. We identify six different fundamental purposes for scenario designs (decision making, sensitivity analysis, value of information, situational awareness, horizon scanning, and forecasting) and discuss how those purposes guide the structure of scenarios. We discuss other aspects of the content and process of scenario design, broadly for all settings and specifically for multi-model ensemble projections. As an illustrative case study, we examine the first 17 rounds of scenarios from the U.S. COVID-19 Scenario Modeling Hub, then reflect on future advancements that could improve the design of scenarios in epidemiological settings. |
format | Online Article Text |
id | pubmed-10592999 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Cold Spring Harbor Laboratory |
record_format | MEDLINE/PubMed |
spelling | pubmed-105929992023-10-24 Scenario Design for Infectious Disease Projections: Integrating Concepts from Decision Analysis and Experimental Design Runge, Michael C. Shea, Katriona Howerton, Emily Yan, Katie Hochheiser, Harry Rosenstrom, Erik Probert, William J.M. Borchering, Rebecca Marathe, Madhav V Lewis, Bryan Venkatramanan, Srinivasan Truelove, Shaun Lessler, Justin Viboud, Cécile medRxiv Article Across many fields, scenario modeling has become an important tool for exploring long-term projections and how they might depend on potential interventions and critical uncertainties, with relevance to both decision makers and scientists. In the past decade, and especially during the COVID-19 pandemic, the field of epidemiology has seen substantial growth in the use of scenario projections. Multiple scenarios are often projected at the same time, allowing important comparisons that can guide the choice of intervention, the prioritization of research topics, or public communication. The design of the scenarios is central to their ability to inform important questions. In this paper, we draw on the fields of decision analysis and statistical design of experiments to propose a framework for scenario design in epidemiology, with relevance also to other fields. We identify six different fundamental purposes for scenario designs (decision making, sensitivity analysis, value of information, situational awareness, horizon scanning, and forecasting) and discuss how those purposes guide the structure of scenarios. We discuss other aspects of the content and process of scenario design, broadly for all settings and specifically for multi-model ensemble projections. As an illustrative case study, we examine the first 17 rounds of scenarios from the U.S. COVID-19 Scenario Modeling Hub, then reflect on future advancements that could improve the design of scenarios in epidemiological settings. Cold Spring Harbor Laboratory 2023-10-12 /pmc/articles/PMC10592999/ /pubmed/37873156 http://dx.doi.org/10.1101/2023.10.11.23296887 Text en https://creativecommons.org/publicdomain/zero/1.0/This article is a US Government work. It is not subject to copyright under 17 USC 105 and is also made available for use under a CC0 license (https://creativecommons.org/publicdomain/zero/1.0/) . |
spellingShingle | Article Runge, Michael C. Shea, Katriona Howerton, Emily Yan, Katie Hochheiser, Harry Rosenstrom, Erik Probert, William J.M. Borchering, Rebecca Marathe, Madhav V Lewis, Bryan Venkatramanan, Srinivasan Truelove, Shaun Lessler, Justin Viboud, Cécile Scenario Design for Infectious Disease Projections: Integrating Concepts from Decision Analysis and Experimental Design |
title | Scenario Design for Infectious Disease Projections: Integrating Concepts from Decision Analysis and Experimental Design |
title_full | Scenario Design for Infectious Disease Projections: Integrating Concepts from Decision Analysis and Experimental Design |
title_fullStr | Scenario Design for Infectious Disease Projections: Integrating Concepts from Decision Analysis and Experimental Design |
title_full_unstemmed | Scenario Design for Infectious Disease Projections: Integrating Concepts from Decision Analysis and Experimental Design |
title_short | Scenario Design for Infectious Disease Projections: Integrating Concepts from Decision Analysis and Experimental Design |
title_sort | scenario design for infectious disease projections: integrating concepts from decision analysis and experimental design |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10592999/ https://www.ncbi.nlm.nih.gov/pubmed/37873156 http://dx.doi.org/10.1101/2023.10.11.23296887 |
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