在接触适应性网络中,流行病随着无症状传染期的传播
Wei Koong Chai1, Merkourios Karaliopoulos2
1School of Computing & Engineering, Bournemouth University, Poole, UK. wchai@bournemouth.ac.uk.
Scientific reports
|January 23, 2026
概括
无症状感染通过限制适应性行为 (如避免接触) 来增加流行病的传播. 无症状病例数量较多降低了流行病值,使得疫情更有可能爆发.
科学领域:
- 流行病学 流行病学
- 数学建模的数学建模
- 网络科学 网络科学
背景情况:
- 流行病模型往往简化了感染期,忽视了无症状传播.
- 个人通过改变社会联系来适应流行病,这种行为很少被模拟.
- 了解无症状传播对于准确的流行病预测和控制至关重要.
研究的目的:
- 开发和分析一种包含无症状感染和适应性接触行为的流行病模型.
- 调查无症状个体和适应性网络变化如何影响流行病动态.
- 确定无症状感染对流行病值和流行率的影响.
主要方法:
- 开发了一个易感-无症状感染-症状感染-易感 (SAIS) 模型.
- 采用基于个体的平均场方法,使用连续时间的马尔科夫链.
- 导出基本的复制号码,并分析了适应性接触场景 (链路断裂/重新连接).
主要成果:
- 无症状感染降低了适应能力,增加了网络密度和流行病发病率.
- 在无症状传播的情况下,避免接触的减缓效应会减弱.
- 流行病值与无症状人口的比例相反;较高的无症状患病率降低了值.
结论:
- 无症状传播显著改变了流行病的动态,往往加剧了传播.
- 适应性行为在缓解具有大量无症状成分的流行病方面效果较差.
- 无症状感染的流行率是决定流行病出现和严重程度的关键因素.
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