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