论文标题
建模预防措施及其对新兴流行病的产生时间的影响
Modelling preventive measures and their effect on generation times in emerging epidemics
论文作者
论文摘要
我们提出了一个随机流行模型，以研究各种预防措施的影响，例如统一的接触和传播，疫苗接种，隔离，筛查和接触跟踪，对同质混合社区中疾病爆发的爆发。该模型基于感染过程，我们通过随机接触和传染性过程来定义该过程，因此每个人都具有独立的感染性概况。特别是，我们监视繁殖数和发电时间分布的变化。我们表明，某些干预措施（即均匀的还原和疫苗接种）会影响前者，而离开后者则没有变化，而其他干预措施，即隔离，筛选和接触跟踪会影响这两个量。我们提供了这些数量变化的理论分析，我们表明，在实践中，生成时间分布的变化可能很重要，并且在估计复制数字时可能会引起偏见。该框架由于其一般性而捕获了许多传染病的特性，但特别强调了Covid-19，为此提供了数值结果。
We present a stochastic epidemic model to study the effect of various preventive measures, such as uniform reduction of contacts and transmission, vaccination, isolation, screening and contact tracing, on a disease outbreak in a homogeneously mixing community. The model is based on an infectivity process, which we define through stochastic contact and infectiousness processes, so that each individual has an independent infectivity profile. In particular, we monitor variations of the reproduction number and of the distribution of generation times. We show that some interventions, i.e. uniform reduction and vaccination, affect the former while leaving the latter unchanged, whereas other interventions, i.e. isolation, screening and contact tracing, affect both quantities. We provide a theoretical analysis of the variation of these quantities, and we show that, in practice, the variation of the generation time distribution can be significant and that it can cause biases in the estimation of reproduction numbers. The framework, because of its general nature, captures the properties of many infectious diseases, but particular emphasis is on COVID-19, for which numerical results are provided.
