标题： 流行病早期阶段的侵袭预测 显示英文标题

标题： Prediction of invasion from the early stage of an epidemic

摘要： 不可预测事件的可预测性是地震学、经济学和流行病学等多个科学领域中备受关注的问题。 在这里，我们专注于由在康复或死亡后会导致感染宿主永久免疫的疾病引起的广泛类别的流行病的可预测性。 我们从复杂性科学的角度出发，提出了几种用于估计流行病重要特征（如入侵概率）的策略，并进行了测试。 我们的结果表明，简洁的近似方法可能会导致最可靠和稳健的预测。 所提出的方法首先应用于对实验观察到的流行病的分析：真菌植物病原体\emph{纹枯病菌}在重复宿主微宇宙中的入侵。 然后，我们考虑了SIR（易感-感染-移除）模型的数值实验，以更详细地研究所提出方法的性能。 该建议的框架可以作为在流行病刚开始发展时快速评估流行病威胁的有用工具。 此外，我们的工作强调了小规模和有限时间的微宇宙流行病实现的重要性，揭示了它们的预测能力。 显示英文摘要

摘要： Predictability of undesired events is a question of great interest in many scientific disciplines including seismology, economy, and epidemiology. Here, we focus on the predictability of invasion of a broad class of epidemics caused by diseases that lead to permanent immunity of infected hosts after recovery or death. We approach the problem from the perspective of the science of complexity by proposing and testing several strategies for the estimation of important characteristics of epidemics, such as the probability of invasion. Our results suggest that parsimonious approximate methodologies may lead to the most reliable and robust predictions. The proposed methodologies are first applied to analysis of experimentally observed epidemics: invasion of the fungal plant pathogen \emph{Rhizoctonia solani} in replicated host microcosms. We then consider numerical experiments of the SIR (susceptible-infected-removed) model to investigate the performance of the proposed methods in further detail. The suggested framework can be used as a valuable tool for quick assessment of epidemic threat at the stage when epidemics only start developing. Moreover, our work amplifies the significance of the small-scale and finite-time microcosm realizations of epidemics revealing their predictive power.