Open Epidemiology for pandemic modelling: a transparent, traceable, reusable, open source pipeline for reproducible science

从历史上看，用于支持向政府提供建议的模型在出版之前并没有公开，至少不是现成的。技术进步、开源和可再生科学的发展意味着这种情况不再站得住脚。尽管英国政策的现行模型是公开的，但它们仍然缺乏透明和易于追溯的证据链，将数据和假设与模型输出联系起来，使它们能够容易地进行独立评估。我们的数据管道支持实施我们苏格兰COVID-19应对联盟（SCRC）利用RAMP计划中的志愿者资源开发的COVID-19流行病学模型，以创建新的互补模型。数据管道在我们评估模型是否适合提供政策建议方面发挥着关键作用，它管理和记录了一条信任链，将有关COVID-19的原始数据、分析、已发表和未发表的文献与模型产出联系起来，并记录了得出结论的来源。我们开发的软件接口将是强大的通用工具，对任何面向策略的建模社区都很有用。

Historically, models used to support advice to government have not been publicly available, at least not readily, prior to publication. Technological advances and the growth of open source and reproducible science mean this is no longer tenable. Although current models feeding into UK policy are publicly available, they still lack the transparent and readily traceable chain of evidence connecting data and assumptions with model outputs that allows them to be readily independently assessed.Our Data Pipeline supports the implementation of COVID-19 epidemiological models that we, the Scottish COVID-19 Response Consortium (SCRC), have developed using volunteer resources within the RAMP initiative, to create new, complementary models. The Data Pipeline fulfils a critical role in our assessment of fitness for purpose for the models in providing policy advice, by managing and documenting a chain of trust that connects the primary data, analyses, and published and unpublished literature on COVID-19 to model outputs, documenting provenance of the conclusions being reached. The software interfaces we develop will be powerful, generic tools that will be useful to any policy-oriented modelling community.