COVID-19政策影响评估：常见设计问题指南
COVID-19 Policy Impact Evaluation: A guide to common design issues
摘要：
应对COVID-19的政策，特别是与非药物干预相关的政策，在规模和范围上都是前所未有的。流行病学家比以往任何时候都更多地参与决策和证据生成。然而，政策影响评估总是需要复杂的环境，研究设计，数据，统计和分析的组合。除了任何政策都面临的问题外，对COVID-19政策的评估因与传染病动态和滞后有关的额外挑战而变得复杂，缺乏对关键结果的直接观察，以及在加速的时间尺度上发生的多种干预措施。政策层面影响评估所需的方法在流行病学中并不经常使用或教授，并且在重要方面可能并不明显。政策评估的数量和速度以及方法上的复杂性可能使决策者和研究人员难以综合和评估COVID-19卫生政策文件中的证据强度。在本文中，我们（1）介绍了针对观测数据的政策影响评估设计的基本套件，包括横截面分析、前/后、中断时间序列和差异中差异分析，（2）展示了在COVID-19背景下，这些设计背后的要求和假设经常被违反的关键方式，以及（3）为决策者和审查者提供识别这些关键违规行为的概念和图形指南。本文的总体目标是帮助流行病学家、政策制定者、期刊编辑、记者、研究人员和其他研究消费者理解和权衡对决策至关重要的证据的优势和局限性。
英文摘要：
Policy responses to COVID-19, particularly those related to non-pharmaceutical interventions, are unprecedented in scale and scope. Epidemiologists are more involved in policy decisions and evidence generation than ever before. However, policy impact evaluations always require a complex combination of circumstance, study design, data, statistics, and analysis. Beyond the issues that are faced for any policy, evaluation of COVID-19 policies is complicated by additional challenges related to infectious disease dynamics and lags, lack of direct observation of key outcomes, and a multiplicity of interventions occurring on an accelerated time scale. The methods needed for policy-level impact evaluation are not often used or taught in epidemiology, and differ in important ways that may not be obvious. The volume and speed, and methodological complications of policy evaluations can make it difficult for decision-makers and researchers to synthesize and evaluate strength of evidence in COVID-19 health policy papers. In this paper, we (1) introduce the basic suite of policy impact evaluation designs for observational data, including cross-sectional analyses, pre/post, interrupted time-series, and difference-in-differences analysis, (2) demonstrate key ways in which the requirements and assumptions underlying these designs are often violated in the context of COVID-19, and (3) provide decision-makers and reviewers a conceptual and graphical guide to identifying these key violations. The overall goal of this paper is to help epidemiologists, policy-makers, journal editors, journalists, researchers, and other research consumers understand and weigh the strengths and limitations of evidence that is essential to decision-making.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
