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针对变异株的干预措施以减缓替代速度并预防暴发。

Variant-specific interventions to slow down replacement and prevent outbreaks.

机构信息

Laboratory for Industrial and Applied Mathematics, Department of Mathematics and Statistics, York University, Canada.

Laboratory for Industrial and Applied Mathematics, Department of Mathematics and Statistics, York University, Canada.

出版信息

Math Biosci. 2022 Jan;343:108703. doi: 10.1016/j.mbs.2021.108703. Epub 2021 Sep 20.

Abstract

Emergency and establishment of variants of concern (VOC) impose significant challenges for the COVID-19 pandemic control specially when a large portion of the population has not been fully vaccinated. Here we develop a mathematical model and utilize this model to examine the impact of non pharmaceutical interventions, including the COVID-test (PCR, antigen and antibody test) and whole genome sequencing (WGS) test capacity and contact tracing and quarantine strength, on the VOC-induced epidemic wave. We point out the undesirable and unexpected effect of lukewarm tracing and quarantine that can potentially increase the VOC-cases at the outbreak peak time, and we demonstrate the significance of strain-specific interventions to either prevent a VOC-induced outbreak, or to mitigate the epidemic wave when this outbreak is unavoidable.

摘要

当很大一部分人口尚未完全接种疫苗时,紧急情况和关注变种(VOC)的建立给 COVID-19 大流行的控制带来了重大挑战。在这里,我们开发了一个数学模型,并利用该模型研究了非药物干预措施(包括 COVID 测试(PCR、抗原和抗体测试)和全基因组测序(WGS)测试能力以及接触者追踪和检疫强度)对 VOC 引发的疫情波的影响。我们指出了追踪和检疫不力的不良和意外影响,这可能会增加疫情高峰期的 VOC 病例数,并且我们证明了针对特定菌株的干预措施的重要性,无论是预防 VOC 引发的疫情,还是在不可避免时减轻疫情波。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc4e/8452136/2bb0c79f4a48/gr1_lrg.jpg

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