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利用半参数增长模型评估南蒂罗尔 COVID-19 大规模检测的影响。

Assessing the impact of COVID-19 mass testing in South Tyrol using a semi-parametric growth model.

机构信息

Faculty of Economics and Management, Free University of Bozen-Bolzano, Piazza Università 1, 39100, Bolzano, Italy.

Research Institute for the Evaluation of Public Policies, Bruno Kessler Foundation, Trento, Italy.

出版信息

Sci Rep. 2022 Oct 26;12(1):17952. doi: 10.1038/s41598-022-21292-3.

Abstract

Mass antigen testing has been proposed as a possible cost-effective tool to contain the COVID-19 pandemic. We test the impact of a voluntary mass testing campaign implemented in the Italian region of South Tyrol on the spread of the virus in the following months. We do so by using an innovative empirical approach which embeds a semi-parametric growth model-where COVID-19 transmission dynamics are allowed to vary across regions and to be impacted by the implementation of the mass testing campaign-into a synthetic control framework which creates an appropriate control group of other Italian regions. Our results suggest that mass testing campaigns are useful instruments for mitigating the pandemic.

摘要

大规模抗原检测已被提议作为一种控制 COVID-19 大流行的具有成本效益的工具。我们测试了在意大利南蒂罗尔地区实施的自愿大规模检测运动对随后几个月病毒传播的影响。我们通过使用一种创新的实证方法来实现这一点,该方法将允许 COVID-19 传播动态在不同地区变化并受大规模检测运动实施影响的半参数增长模型嵌入到合成控制框架中,该框架为其他意大利地区创建了一个合适的对照组。我们的结果表明,大规模检测运动是缓解大流行的有用工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b477/9605953/93b7eb2cb6dc/41598_2022_21292_Fig1_HTML.jpg

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