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在大流行期间重新校准政策制定中的建模概念。

Recalibrating the notion of modelling for policymaking during pandemics.

机构信息

Health Intervention and Technology Assessment Program (HITAP), Department of Health, Ministry of Public Health, 6th Floor, 6th Building, Tiwanon Road, Nonthaburi 11000, Thailand; Saw Swee Hock School of Public Health (SSHSPH), National University of Singapore (NUS), 12 Science Drive 2, #10-01, 117549, Singapore.

Health Intervention and Technology Assessment Program (HITAP), Department of Health, Ministry of Public Health, 6th Floor, 6th Building, Tiwanon Road, Nonthaburi 11000, Thailand.

出版信息

Epidemics. 2022 Mar;38:100552. doi: 10.1016/j.epidem.2022.100552. Epub 2022 Mar 2.

Abstract

COVID-19 disease models have aided policymakers in low-and middle-income countries (LMICs) with many critical decisions. Many challenges remain surrounding their use, from inappropriate model selection and adoption, inadequate and untimely reporting of evidence, to the lack of iterative stakeholder engagement in policy formulation and deliberation. These issues can contribute to the misuse of models and hinder effective policy implementation. Without guidance on how to address such challenges, the true potential of such models may not be realised. The COVID-19 Multi-Model Comparison Collaboration (CMCC) was formed to address this gap. CMCC is a global collaboration between decision-makers from LMICs, modellers and researchers, and development partners. To understand the limitations of existing COVID-19 disease models (primarily from high income countries) and how they could be adequately support decision-making in LMICs, a desk review of modelling experience during the COVID-19 and past disease outbreaks, two online surveys, and regular online consultations were held among the collaborators. Three key recommendations from CMCC include: A 'fitness-for-purpose' flowchart, a tool that concurrently walks policymakers (or their advisors) and modellers through a model selection and development process. The flowchart is organised around the following: policy aims, modelling feasibility, model implementation, model reporting commitment. Holmdahl and Buckee (2020) A 'reporting standards trajectory', which includes three gradually increasing standard of reports, 'minimum', 'acceptable', and 'ideal', and seeks collaboration from funders, modellers, and decision-makers to enhance the quality of reports over time and accountability of researchers. Malla et al. (2018) A framework for "collaborative modelling for effective policy implementation and evaluation" which extends the definition of stakeholders to funders, ground-level implementers, public, and other researchers, and outlines how each can contribute to modelling. We advocate for standardisation of modelling processes and adoption of country-owned model through iterative stakeholder participation and discuss how they can enhance trust, accountability, and public ownership to decisions.

摘要

COVID-19 疾病模型帮助中低收入国家(LMICs)的政策制定者做出了许多关键决策。在使用这些模型时,仍然存在许多挑战,包括模型选择和采用不当、证据报告不充分和不及时、以及在政策制定和审议过程中缺乏迭代式利益相关者参与。这些问题可能导致模型的滥用,并阻碍有效的政策实施。如果没有关于如何解决这些挑战的指导,这些模型的真正潜力可能无法实现。COVID-19 多模型比较合作组织(CMCC)就是为了解决这一差距而成立的。CMCC 是一个由来自 LMICs 的决策者、建模者和研究人员以及发展伙伴组成的全球合作组织。为了了解现有 COVID-19 疾病模型(主要来自高收入国家)的局限性,以及如何在 LMICs 中充分支持决策,合作者们对 COVID-19 和过去疾病爆发期间的建模经验进行了桌面审查、两次在线调查以及定期在线磋商。CMCC 的三项关键建议包括:

  1. 一个“适合目的”流程图,这是一个工具,可以同时指导政策制定者(或他们的顾问)和建模者完成模型选择和开发过程。该流程图围绕以下内容组织:政策目标、建模可行性、模型实施、模型报告承诺。Holmdahl 和 Buckee(2020)

  2. “报告标准轨迹”,包括三个逐渐增加的报告标准,“最低”、“可接受”和“理想”,并寻求资助者、建模者和决策者的合作,以随着时间的推移提高报告的质量和研究人员的问责制。Malla 等人(2018)

  3. “用于有效政策实施和评估的协作建模框架”,将利益相关者的定义扩展到资助者、基层实施者、公众和其他研究人员,并概述了每个利益相关者如何为建模做出贡献。我们主张通过迭代式利益相关者参与来标准化建模过程并采用国有模型,并讨论它们如何增强对决策的信任、问责制和公众所有权。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4725/8919056/5db0a81a4736/gr1.jpg

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