论文标题
具有潜在基因型网络的多种流行病的本地化,流行过渡和不可预测性
Localization, epidemic transitions, and unpredictability of multistrain epidemics with an underlying genotype network
论文作者
论文摘要
数学疾病模型长期以来一直在假设中,任何一种传染病都是由一种可传播的病原体在人群中传播引起的。该范式在简化流行病的生物学现实方面非常有用,并允许建模社区专注于其他因素(例如人口结构和干预措施)的复杂性。但是,越来越多的证据表明,病原体的应变多样性及其与宿主免疫系统的相互作用可以在塑造流行病动力学中发挥重要作用。在这里,我们引入了一个具有潜在基因型网络的疾病模型,以说明两种重要机制。第一,由于疾病在宿主人群中扩散时,该疾病会沿网络途径突变。第二,基因型网络使我们能够定义跨菌株的遗传距离,从而建模在现实世界病原体中经常观察到的免疫力的超越性。我们通过其流行期过渡研究了流行病的出现,并强调了基因型网络在驱动疾病循环,大规模波动,顺序流行过渡以及周围定位的特定病原体菌株中的作用。更普遍的是,我们的模型说明了行为的丰富性,即使在混合良好的宿主种群中,我们考虑了应变多样性,并且超越了“一种疾病等于一种病原体”范式。
Mathematical disease modelling has long operated under the assumption that any one infectious disease is caused by one transmissible pathogen spreading among a population. This paradigm has been useful in simplifying the biological reality of epidemics and has allowed the modelling community to focus on the complexity of other factors such as population structure and interventions. However, there is an increasing amount of evidence that the strain diversity of pathogens, and their interplay with the host immune system, can play a large role in shaping the dynamics of epidemics. Here, we introduce a disease model with an underlying genotype network to account for two important mechanisms. One, the disease can mutate along network pathways as it spreads in a host population. Two, the genotype network allows us to define a genetic distance across strains and therefore to model the transcendence of immunity often observed in real world pathogens. We study the emergence of epidemics in this model, through its epidemic phase transitions, and highlight the role of the genotype network in driving cyclicity of diseases, large scale fluctuations, sequential epidemic transitions, as well as localization around specific strains of the associated pathogen. More generally, our model illustrates the richness of behaviours that are possible even in well-mixed host populations once we consider strain diversity and go beyond the "one disease equals one pathogen" paradigm.