论文标题
部分可观测时空混沌系统的无模型预测
Analysis of the competition among viral strains using a temporal interaction-driven contagion model
论文作者
论文摘要
社会互动的时间动态显示会影响疾病的传播。在这里，我们对几种病毒菌株的进展和竞争的条件进行了建模，并探索了时间网络上各种跨度免疫力。我们使用与交互驱动的传染模型并使用几种病毒变体来表征。我们的结果是在时间随机网络和实际交互数据上获得的，表明时间动力学对于确定竞争结果至关重要。我们考虑两种和三种竞争的病原体，并显示了较慢的病原体保持活跃并创建第二波感染大部分人群的条件。然后，我们表明，当考虑相遇的持续时间时，扩展动力学会发生显着变化。我们的结果表明，在考虑空气传播疾病时，考虑时间会议的持续时间以建模病原体在人群中的传播可能至关重要。
The temporal dynamics of social interactions were shown to influence the spread of disease. Here, we model the conditions of progression and competition for several viral strains, exploring various levels of cross-immunity over temporal networks. We use our interaction-driven contagion model and characterize, using it, several viral variants. Our results, obtained on temporal random networks and on real-world interaction data, demonstrate that temporal dynamics are crucial to determining the competition results. We consider two and three competing pathogens and show the conditions under which a slower pathogen will remain active and create a second wave infecting most of the population. We then show that when the duration of the encounters is considered, the spreading dynamics change significantly. Our results indicate that when considering airborne diseases, it might be crucial to consider the duration of temporal meetings to model the spread of pathogens in a population.
