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发表之前没有公开提供，至少不是很容易。技术进步以及开源和可再生科学的发展意味着这不再站得住脚。虽然目前提供给英国政策的模型是公开的，但它们仍然缺乏将数据和假设与模型输出连接起来的透明和易于追踪的证据链，从而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，苏格兰新冠肺炎应对联盟(SCRC)利用RAMP倡议内的志愿者资源开发的新冠肺炎流行病模型，以创建新的补充模型。数据管道在评估模型的适用性方面发挥了关键作用，通过管理和记录将原始数据、分析以及新冠肺炎上已发布和未发布的文献与模型输出连接起来的信任链，并记录所得出结论的出处，从而在提供政策建议方面发挥关键作用。我们开发的软件界面将是强大的、通用的工具，将对任何面向政策的建模社区有用。

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policy advice, by managing and documenting a chain of trust that connects the primary data, analyses, and published and unpublished literature on COVID-19 to model outputs, documenting provenance of the conclusions being reached.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.