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新冠疫情反弹期间大规模检测的影响：以法国为例的建模研究。

Impact of mass testing during an epidemic rebound of SARS-CoV-2: a modelling study using the example of France.

机构信息

Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, UMR2000, CNRS, Paris, France.

Collège Doctoral, Sorbonne Université, Paris, France.

出版信息

Euro Surveill. 2021 Jan;26(1). doi: 10.2807/1560-7917.ES.2020.26.1.2001978.

DOI:10.2807/1560-7917.ES.2020.26.1.2001978
PMID:33413741
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7791601/
Abstract

We used a mathematical model to evaluate the impact of mass testing in the control of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Under optimistic assumptions, one round of mass testing may reduce daily infections by up to 20-30%. Consequently, very frequent testing would be required to control a quickly growing epidemic if other control measures were to be relaxed. Mass testing is most relevant when epidemic growth remains limited through a combination of interventions.

摘要

我们使用数学模型评估了大规模检测对严重急性呼吸综合征冠状病毒 2（SARS-CoV-2）控制的影响。在乐观的假设下，一轮大规模检测最多可减少 20-30%的日感染人数。因此，如果放松其他控制措施，那么在疫情迅速蔓延的情况下，需要非常频繁地进行检测才能加以控制。当通过综合干预措施使疫情增长仍然受到限制时，大规模检测最相关。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ec31/7791601/440518778ce6/2001978-f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ec31/7791601/dd72629e4942/2001978-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ec31/7791601/ef69a309ae4c/2001978-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ec31/7791601/6f5d06b18f7e/2001978-f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ec31/7791601/440518778ce6/2001978-f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ec31/7791601/dd72629e4942/2001978-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ec31/7791601/ef69a309ae4c/2001978-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ec31/7791601/6f5d06b18f7e/2001978-f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ec31/7791601/440518778ce6/2001978-f4.jpg

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