中国的COVID零后的Omicron波:贝叶斯式分析
Jun Cai1, Yanpeng Wu2, Hengcong Liu1,3
1Department of Epidemiology, School of Public Health, Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, Shanghai 200032, China.
概括
中国中国中国中国.
科学领域:
- 流行病学 流行病学
- 数学建模的数学建模
- 公共卫生 公共卫生
背景情况:
- 中国在2022年底从其"动态零COVID"政策转变,导致严重急性呼吸系统综合征冠状病毒2 (SARS-CoV-2) 的Omicron波广泛蔓延.
- 了解这种波的传播动态对于为未来的公共卫生战略提供信息至关重要.
研究的目的:
- 在政策转变之后,描述SARS-CoV-2 Omicron波在中国的传播动态.
- 为了估计在波期间的累积感染攻击率和有效繁殖数.
- 调查行为因素和流动性对传播的影响.
主要方法:
- 使用贝叶斯框架来适应决定性的传输模型.
- 该模型使用报告的COVID-19每日病例数和每周病毒学/类似流感疾病 (ILI) 监测数据进行校准.
- 纳入了时间变化的行为反应系数,反映了累积感染和当前流行率.
主要成果:
- 到2023年2月中旬,估计累计感染攻击率达到87.8%,在政策放宽一个月内感染人口的比例为84.1%.
- 有效繁殖数在2022年12月8日达到5.69的峰值.
- 传播率与春节前的长期行为反应 (ρ = 0.92) 和短期反应 (ρ = 0.87) 的移动模式有显著的相关性.
结论:
- 中国的SARS-CoV-2 Omicron波是广泛的,累积感染攻击率很高.
- 人口免疫力在很大程度上阻止了随后的浪潮,尽管云期间传播增加了.
- 将时间变化的行为因素纳入流行病模型对于准确描述传播动态至关重要,特别是在突然的政策变化之后.
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