综合控制、综合干预和COVID-19传播：探讨封锁措施和群体免疫的影响
Synthetic Control, Synthetic Interventions, and COVID-19 spread: Exploring the impact of lockdown measures and herd immunity
摘要：
综合控制法是一种利用观测数据进行因果推断的经验方法。通过观察COVID-19在全球范围内的传播，我们利用综合控制及其扩展的预测能力、反事实分析和综合干预，分析了不同地区的死亡人数和病例数数据。我们观察到，如果早一点实施封锁，晚一点重新开放，特别是在室内酒吧和餐馆，不同地区的死亡人数和病例数量会少得多。我们还分析了群体免疫对每个地区人口传播的推测影响，并表明封锁政策对传播具有非常强的影响，无论先前感染的水平如何。我们最新的代码、模型和数据可以在github上找到：https://github.com/niloofarbayat/COVID19-synthetic-control-analysis
英文摘要：
The synthetic control method is an empirical methodology forcausal inference using observational data. By observing thespread of COVID-19 throughout the world, we analyze the dataon the number of deaths and cases in different regions usingthe power of prediction, counterfactual analysis, and syntheticinterventions of the synthetic control and its extensions. Weobserve that the number of deaths and cases in different re-gions would have been much smaller had the lockdowns beenimposed earlier and had the re-openings been done later, es-pecially among indoor bars and restaurants. We also analyzethe speculated impact of herd immunity on the spread giventhe population of each region and show that lockdown policieshave a very strong impact on the spread regardless of the levelof prior infections. Our most up-to-date code, model, and data can be foundon github: https://github.com/niloofarbayat/COVID19-synthetic-control-analysis
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。
