论文标题
合成控制，合成干预措施和COVID-19-19：探索锁定措施和牛群免疫力的影响
Synthetic Control, Synthetic Interventions, and COVID-19 spread: Exploring the impact of lockdown measures and herd immunity
论文作者
论文摘要
合成控制方法是使用观测数据的经验方法论推断。通过观察到世界各地的Covid-19的典范，我们使用预测，反事实分析和合成控制及其扩展的综合介入的能力分析了不同地区的死亡人数和病例的数量。 Weobserve认为，如果较早的锁定被锁定，并且重新开放是在后来进行的，尤其是在室内酒吧和餐馆中。我们还分析了牛群免疫对每个地区的扩散人口的影响，并表明锁定政策对差异的影响很大，无论先前感染的水平如何。 我们最新的代码，模型和数据可以是基础：https：//github.com/niloofarbayat/covid19-synthetic-control-analisy
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
