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Where Do We Go From Here? A Framework for Using Susceptible-Infectious-Recovered Models for Policy Making in Emerging Infectious Diseases
OBJECTIVES: Throughout the coronavirus disease 2019 pandemic, susceptible-infectious-recovered (SIR) modeling has been the preeminent modeling method to inform policy making worldwide. Nevertheless, the usefulness of such models has been subject to controversy. An evolution in the epidemiological mo...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
ISPOR-The Professional Society for Health Economics and Outcomes Research. Published by Elsevier Inc.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8110035/ https://www.ncbi.nlm.nih.gov/pubmed/34243834 http://dx.doi.org/10.1016/j.jval.2021.03.005 |
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author | Zawadzki, Roy S. Gong, Cynthia L. Cho, Sang K. Schnitzer, Jan E. Zawadzki, Nadine K. Hay, Joel W. Drabo, Emmanuel F. |
author_facet | Zawadzki, Roy S. Gong, Cynthia L. Cho, Sang K. Schnitzer, Jan E. Zawadzki, Nadine K. Hay, Joel W. Drabo, Emmanuel F. |
author_sort | Zawadzki, Roy S. |
collection | PubMed |
description | OBJECTIVES: Throughout the coronavirus disease 2019 pandemic, susceptible-infectious-recovered (SIR) modeling has been the preeminent modeling method to inform policy making worldwide. Nevertheless, the usefulness of such models has been subject to controversy. An evolution in the epidemiological modeling field is urgently needed, beginning with an agreed-upon set of modeling standards for policy recommendations. The objective of this article is to propose a set of modeling standards to support policy decision making. METHODS: We identify and describe 5 broad standards: transparency, heterogeneity, calibration and validation, cost-benefit analysis, and model obsolescence and recalibration. We give methodological recommendations and provide examples in the literature that employ these standards well. We also develop and demonstrate a modeling practices checklist using existing coronavirus disease 2019 literature that can be employed by readers, authors, and reviewers to evaluate and compare policy modeling literature along our formulated standards. RESULTS: We graded 16 articles using our checklist. On average, the articles met 6.81 of our 19 categories (36.7%). No articles contained any cost-benefit analyses and few were adequately transparent. CONCLUSIONS: There is significant room for improvement in modeling pandemic policy. Issues often arise from a lack of transparency, poor modeling assumptions, lack of a system-wide perspective in modeling, and lack of flexibility in the academic system to rapidly iterate modeling as new information becomes available. In anticipation of future challenges, we encourage the modeling community at large to contribute toward the refinement and consensus of a shared set of standards for infectious disease policy modeling. |
format | Online Article Text |
id | pubmed-8110035 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | ISPOR-The Professional Society for Health Economics and Outcomes Research. Published by Elsevier Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-81100352021-05-11 Where Do We Go From Here? A Framework for Using Susceptible-Infectious-Recovered Models for Policy Making in Emerging Infectious Diseases Zawadzki, Roy S. Gong, Cynthia L. Cho, Sang K. Schnitzer, Jan E. Zawadzki, Nadine K. Hay, Joel W. Drabo, Emmanuel F. Value Health Themed Section: COVID-19 OBJECTIVES: Throughout the coronavirus disease 2019 pandemic, susceptible-infectious-recovered (SIR) modeling has been the preeminent modeling method to inform policy making worldwide. Nevertheless, the usefulness of such models has been subject to controversy. An evolution in the epidemiological modeling field is urgently needed, beginning with an agreed-upon set of modeling standards for policy recommendations. The objective of this article is to propose a set of modeling standards to support policy decision making. METHODS: We identify and describe 5 broad standards: transparency, heterogeneity, calibration and validation, cost-benefit analysis, and model obsolescence and recalibration. We give methodological recommendations and provide examples in the literature that employ these standards well. We also develop and demonstrate a modeling practices checklist using existing coronavirus disease 2019 literature that can be employed by readers, authors, and reviewers to evaluate and compare policy modeling literature along our formulated standards. RESULTS: We graded 16 articles using our checklist. On average, the articles met 6.81 of our 19 categories (36.7%). No articles contained any cost-benefit analyses and few were adequately transparent. CONCLUSIONS: There is significant room for improvement in modeling pandemic policy. Issues often arise from a lack of transparency, poor modeling assumptions, lack of a system-wide perspective in modeling, and lack of flexibility in the academic system to rapidly iterate modeling as new information becomes available. In anticipation of future challenges, we encourage the modeling community at large to contribute toward the refinement and consensus of a shared set of standards for infectious disease policy modeling. ISPOR-The Professional Society for Health Economics and Outcomes Research. Published by Elsevier Inc. 2021-07 2021-05-10 /pmc/articles/PMC8110035/ /pubmed/34243834 http://dx.doi.org/10.1016/j.jval.2021.03.005 Text en © 2021 ISPOR-The Professional Society for Health Economics and Outcomes Research. Published by Elsevier Inc. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Themed Section: COVID-19 Zawadzki, Roy S. Gong, Cynthia L. Cho, Sang K. Schnitzer, Jan E. Zawadzki, Nadine K. Hay, Joel W. Drabo, Emmanuel F. Where Do We Go From Here? A Framework for Using Susceptible-Infectious-Recovered Models for Policy Making in Emerging Infectious Diseases |
title | Where Do We Go From Here? A Framework for Using Susceptible-Infectious-Recovered Models for Policy Making in Emerging Infectious Diseases |
title_full | Where Do We Go From Here? A Framework for Using Susceptible-Infectious-Recovered Models for Policy Making in Emerging Infectious Diseases |
title_fullStr | Where Do We Go From Here? A Framework for Using Susceptible-Infectious-Recovered Models for Policy Making in Emerging Infectious Diseases |
title_full_unstemmed | Where Do We Go From Here? A Framework for Using Susceptible-Infectious-Recovered Models for Policy Making in Emerging Infectious Diseases |
title_short | Where Do We Go From Here? A Framework for Using Susceptible-Infectious-Recovered Models for Policy Making in Emerging Infectious Diseases |
title_sort | where do we go from here? a framework for using susceptible-infectious-recovered models for policy making in emerging infectious diseases |
topic | Themed Section: COVID-19 |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8110035/ https://www.ncbi.nlm.nih.gov/pubmed/34243834 http://dx.doi.org/10.1016/j.jval.2021.03.005 |
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