Research Institute of Intelligent Complex Systems, Fudan University, Shanghai, 200433, China.
Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, 200433, China.
Bull Math Biol. 2022 Jan 10;84(2):30. doi: 10.1007/s11538-021-00958-5.
The COVID-19 pandemic has adversely affected the entire world. The effective implementation of vaccination strategy is critical to prevent the resurgence of the pandemic, especially during large-scale population migration. We establish a multiple patch coupled model based on the transportation network among the 31 provinces in China, under the combined strategies of vaccination and quarantine during large-scale population migration. Based on the model, we derive a critical quarantine rate to control the pandemic transmission and a vaccination rate to achieve herd immunity. Furthermore, we evaluate the influence of passenger flow on the effective reproduction number during the Chinese-Spring-Festival travel rush. Meanwhile, the spread of the COVID-19 pandemic is investigated for different control strategies, viz. global control and local control. The impact of vaccine-related parameters, such as the number, the effectiveness and the immunity period of vaccine, are explored. It is believed that the articulated models as well as the presented simulation results could be beneficial to design of feasible strategies for preventing COVID-19 transmission during the Chinese-Spring-Festival travel rush or the other future events involving large-scale population migration.
新冠疫情大流行对全球造成了负面影响。在大规模人口迁移期间,有效实施疫苗接种策略对于防止疫情再次爆发至关重要。我们建立了一个基于中国 31 个省份之间交通网络的多补丁耦合模型,该模型结合了大规模人口迁移期间的疫苗接种和隔离策略。基于该模型,我们推导出了控制疫情传播的临界隔离率和实现群体免疫的疫苗接种率。此外,我们评估了春运期间客流量对有效繁殖数的影响。同时,我们还研究了不同控制策略(全球控制和局部控制)下 COVID-19 疫情的传播情况。我们还探讨了疫苗相关参数(如疫苗数量、有效性和免疫期)的影响。我们相信,所提出的模型和仿真结果有助于设计在春运或其他涉及大规模人口迁移的未来事件中预防 COVID-19 传播的可行策略。