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多种非药物干预措施对中国入境旅行的影响与国内 COVID-19 疫情爆发的关系。

The impact of multiple non-pharmaceutical interventions for China-bound travel on domestic COVID-19 outbreaks.

机构信息

Vanke School of Public Health, Tsinghua University, Beijing, China.

Shenzhen Health Development Research and Data Management Center, Shenzhen, Guangdong, China.

出版信息

Front Public Health. 2023 Jul 13;11:1202996. doi: 10.3389/fpubh.2023.1202996. eCollection 2023.

Abstract

OBJECTIVES

Non-pharmaceutical interventions (NPIs) implemented on China-bound travel have successfully mitigated cross-regional transmission of COVID-19 but made the country face ripple effects. Thus, adjusting these interventions to reduce interruptions to individuals' daily life while minimizing transmission risk was urgent.

METHODS

An improved Susceptible-Infected-Recovered (SIR) model was built to evaluate the Delta variant's epidemiological characteristics and the impact of NPIs. To explore the risk associated with inbound travelers and the occurrence of domestic traceable outbreaks, we developed an association parameter that combined inbound traveler counts with a time-varying initial value. In addition, multiple time-varying functions were used to model changes in the implementation of NPIs. Related parameters of functions were run by the MCSS method with 1,000 iterations to derive the probability distribution. Initial values, estimated parameters, and corresponding 95% CI were obtained. Reported existing symptomatic, suspected, and asymptomatic case counts were used as the training datasets. Reported cumulative recovered individual data were used to verify the reliability of relevant parameters. Lastly, we used the value of the ratio (Bias/Variance) to verify the stability of the mathematical model, and the effects of the NPIs on the infected cases to analyze the sensitivity of input parameters.

RESULTS

The quantitative findings indicated that this improved model was highly compatible with publicly reported data collected from July 21 to August 30, 2021. The number of inbound travelers was associated with the occurrence of domestic outbreaks. A proportional relationship between the Delta variant incubation period and PCR test validity period was found. The model also predicted that restoration of pre-pandemic travel schedules while adhering to NPIs requirements would cause shortages in health resources. The maximum demand for hospital beds would reach 25,000/day, the volume of PCR tests would be 8,000/day, and the number of isolation rooms would reach 800,000/day within 30 days.

CONCLUSION

With the pandemic approaching the end, reexamining it carefully helps better address future outbreaks. This predictive model has provided scientific evidence for NPIs' effectiveness and quantifiable evidence of health resource allocation. It could guide the design of future epidemic prevention and control policies, and provide strategic recommendations on scarce health resource allocation.

摘要

目的

在中国入境旅行中实施的非药物干预(NPIs)成功减轻了 COVID-19 的跨区域传播,但也给国家带来了连锁反应。因此,调整这些干预措施以减少对个人日常生活的干扰,同时最大限度地降低传播风险迫在眉睫。

方法

建立了改进的易感-感染-恢复(SIR)模型来评估德尔塔变异株的流行病学特征和 NPIs 的影响。为了探索入境旅行者带来的风险和国内可追踪疫情的发生,我们开发了一个关联参数,将入境旅行者人数与随时间变化的初始值相结合。此外,还使用多个随时间变化的函数来模拟 NPIs 的实施变化。通过 MCSS 方法对函数的相关参数进行 1000 次迭代,以得出概率分布。获取初始值、估计参数和相应的 95%置信区间。使用报告的现有症状、疑似和无症状病例数作为训练数据集。使用报告的累计康复个体数据来验证相关参数的可靠性。最后,我们使用比值(偏差/方差)来验证数学模型的稳定性,并分析输入参数对感染病例的影响。

结果

定量结果表明,该改进模型与 2021 年 7 月 21 日至 8 月 30 日期间公开报告的数据高度吻合。入境旅行者人数与国内疫情的发生有关。还发现德尔塔变异株潜伏期和 PCR 检测有效期之间存在比例关系。该模型还预测,在恢复大流行前的旅行计划的同时遵守 NPIs 要求,将导致卫生资源短缺。在 30 天内,医院床位的最大需求量将达到每天 25000 张,PCR 检测量将达到每天 8000 次,隔离室数量将达到每天 80 万间。

结论

随着大流行接近尾声,仔细重新审视它有助于更好地应对未来的疫情爆发。该预测模型为 NPIs 的有效性提供了科学依据,并提供了量化的卫生资源分配证据。它可以为未来的疫情防控政策设计提供指导,并为稀缺卫生资源的分配提供战略建议。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcec/10373927/1b75505c697a/fpubh-11-1202996-g001.jpg

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