Suppr超能文献

建模中国动态清零向重新开放策略的转变,考虑到后遗症和再感染。

Modelling the reopen strategy from dynamic zero-COVID in China considering the sequela and reinfection.

机构信息

Department of Statistics and Data Science, Southern University of Science and Technology, Shenzhen, 518055, China.

Institute for Transport Studies, University of Leeds, Leeds, LS2 9JT, UK.

出版信息

Sci Rep. 2023 May 5;13(1):7343. doi: 10.1038/s41598-023-34207-7.

Abstract

Although the dynamic zero-COVID policy has effectively controlled virus spread in China, China has to face challenges in balancing social-economic burdens, vaccine protection, and the management of long COVID symptoms. This study proposed a fine-grained agent-based model to simulate various strategies for transitioning from a dynamic zero-COVID policy with a case study in Shenzhen. The results indicate that a gradual transition, maintaining some restrictions, can mitigate infection outbreaks. However, the severity and duration of epidemics vary based on the strictness of the measures. In contrast, a more direct transition to reopening may lead to rapid herd immunity but necessitate preparedness for potential sequelae and reinfections. Policymakers should assess healthcare capacity for severe cases and potential long-COVID symptoms and determine the most suitable approach tailored to local conditions.

摘要

尽管动态清零政策在中国有效地控制了病毒传播,但中国仍面临着平衡社会经济负担、疫苗保护和长期新冠症状管理的挑战。本研究提出了一个细粒度的基于代理的模型,通过在深圳进行案例研究来模拟各种从动态清零政策过渡的策略。结果表明,逐步过渡,保持一些限制,可以减轻感染爆发。然而,疫情的严重程度和持续时间取决于措施的严格程度。相比之下,更直接地过渡到重新开放可能会导致快速的群体免疫,但需要为潜在的后遗症和再感染做好准备。政策制定者应该评估严重病例和潜在长期新冠症状的医疗能力,并根据当地情况确定最合适的方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f3c5/10163221/15ffbf42bd39/41598_2023_34207_Fig1_HTML.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验