评估疫情应对免疫计划影响的框架。

Diseases Pub Date : 2024-04-04 DOI:10.3390/diseases12040073
D. Delport, Ben Sanderson, Rachel Sacks-Davis, Stefanie Vaccher, Milena Dalton, R. Martin-Hughes, T. Mengistu, Daniel Hogan, R. Abeysuriya, Nick Scott
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引用次数: 0

摘要

通过将观察到的结果与没有疫情反应免疫的模拟反事实情景进行比较,可以估算疫情反应免疫(ORI)的影响,但最合适的衡量标准取决于利益相关者的需求和数据可用性。本研究为使用数学模型评估 ORI 对疫苗可预防疾病的影响制定了一个框架。该框架的开发包括:(1) 根据利益相关者访谈和文献综述评估影响指标,确定数据可用性和作为模型结果的捕获能力;(2) 将对 ORI 要素的投资映射到模型参数,以确定情景;(3) 开发一个系统,让利益相关者参与其中,并制定模型问题、执行分析和解释结果;(4) 不同环境和病原体的示例应用。经确认,最有用的衡量标准是健康影响、经济影响和严重疫情爆发的风险。情景类别包括应对规模投资、应对速度和疫苗针对性。该框架定义了四个阶段:(1) 问题框架和数据来源(确定利益相关者的需求、指标和情景);(2) 模型选择;(3) 模型实施;(4) 解释和交流。该框架在巴布亚新几内亚的麻疹和刚果民主共和国的埃博拉疫情中的应用得到了验证。该框架是一种与利益相关者合作的系统方法,可确保分析符合目的、充分利用现有数据并使用合适的建模方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Framework for Assessing the Impact of Outbreak Response Immunization Programs.
The impact of outbreak response immunization (ORI) can be estimated by comparing observed outcomes to modelled counterfactual scenarios without ORI, but the most appropriate metrics depend on stakeholder needs and data availability. This study developed a framework for using mathematical models to assess the impact of ORI for vaccine-preventable diseases. Framework development involved (1) the assessment of impact metrics based on stakeholder interviews and literature reviews determining data availability and capacity to capture as model outcomes; (2) mapping investment in ORI elements to model parameters to define scenarios; (3) developing a system for engaging stakeholders and formulating model questions, performing analyses, and interpreting results; and (4) example applications for different settings and pathogens. The metrics identified as most useful were health impacts, economic impacts, and the risk of severe outbreaks. Scenario categories included investment in the response scale, response speed, and vaccine targeting. The framework defines four phases: (1) problem framing and data sourcing (identification of stakeholder needs, metrics, and scenarios); (2) model choice; (3) model implementation; and (4) interpretation and communication. The use of the framework is demonstrated by application to two outbreaks, measles in Papua New Guinea and Ebola in the Democratic Republic of the Congo. The framework is a systematic way to engage with stakeholders and ensure that an analysis is fit for purpose, makes the best use of available data, and uses suitable modelling methodology.
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