A minimalist model of ecohydrologic dynamics is coupled to the well-known susceptible–infected–recovered epidemiological model to explore hydro-climatic controls on infection dynamics and extreme outbreaks. The resulting HYSIR model reveals the existence of a noise-induced bifurcation producing oscillations in infection dynamics. Linearization of the governing equations allows for an analytic expression for the periodicity of infections in terms of both epidemiological (e.g. transmission and recovery rate) and hydrologic (i.e. soil moisture decay rate or memory) parameters. Numerical simulations of the full stochastic, nonlinear system show extreme outbreaks in response to particular combinations of hydro-climatic conditions, neither of which is extreme per se, rather than a single major climatic event. These combinations depend on the assumed functional relationship between the hydrologic variables and the transmission rate. Our results emphasize the importance of hydro-climatic history and system memory in evaluating the risk of severe outbreaks.

中文翻译：

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由水文气候变异和记忆引起的周期性流行病和极端暴发

生态水文动力学的极简模型与众所周知的易感-感染-恢复流行病学模型相结合，以探索对感染动力学和极端爆发的水文气候控制。由此产生的 HYSIR 模型揭示了在感染动力学中产生振荡的噪声诱导分叉的存在。控制方程的线性化允许在流行病学（例如传播和恢复率）和水文（即土壤水分衰减率或记忆）参数方面对感染的周期性进行分析表达。完全随机、非线性系统的数值模拟显示响应于水文气候条件的特定组合的极端爆发，这两种情况本身都不是极端的，而是单一的主要气候事件。这些组合取决于假设的水文变量和传输速率之间的函数关系。我们的结果强调了水文气候历史和系统记忆在评估严重爆发风险方面的重要性。