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COVID-19 中期情景作为免疫不确定性和慢性病的函数。

Medium-term scenarios of COVID-19 as a function of immune uncertainties and chronic disease.

机构信息

Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA.

Miller Institute for Basic Research in Science, University of California, Berkeley, CA, USA.

出版信息

J R Soc Interface. 2023 Aug;20(205):20230247. doi: 10.1098/rsif.2023.0247. Epub 2023 Aug 30.

Abstract

As the SARS-CoV-2 trajectory continues, the longer-term immuno-epidemiology of COVID-19, the dynamics of Long COVID, and the impact of escape variants are important outstanding questions. We examine these remaining uncertainties with a simple modelling framework that accounts for multiple (antigenic) exposures via infection or vaccination. If immunity (to infection or Long COVID) accumulates rapidly with the valency of exposure, we find that infection levels and the burden of Long COVID are markedly reduced in the medium term. More pessimistic assumptions on host adaptive immune responses illustrate that the longer-term burden of COVID-19 may be elevated for years to come. However, we also find that these outcomes could be mitigated by the eventual introduction of a vaccine eliciting robust (i.e. durable, transmission-blocking and/or 'evolution-proof') immunity. Overall, our work stresses the wide range of future scenarios that still remain, the importance of collecting real-world epidemiological data to identify likely outcomes, and the crucial need for the development of a highly effective transmission-blocking, durable and broadly protective vaccine.

摘要

随着 SARS-CoV-2 疫情的持续发展,COVID-19 的长期免疫流行病学、长新冠的动态变化以及逃逸变异的影响,都是重要的悬而未决的问题。我们使用一个简单的建模框架来研究这些剩余的不确定性,该框架通过感染或接种疫苗来考虑多种(抗原)暴露。如果免疫(针对感染或长新冠)随着暴露的效价迅速积累,我们发现感染水平和长新冠的负担在中期会显著降低。对宿主适应性免疫反应更悲观的假设表明,未来几年 COVID-19 的长期负担可能会升高。然而,我们还发现,最终引入一种能引起强大(即持久、具有传播阻断性和/或“抗进化”)免疫的疫苗,可以减轻这些后果。总的来说,我们的工作强调了仍然存在的广泛的未来情景,强调了收集真实世界流行病学数据以识别可能结果的重要性,以及迫切需要开发一种高效的具有传播阻断性、持久性和广泛保护力的疫苗。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/322b/10465195/b542161dfeb7/rsif20230247f01.jpg

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