Predicting the effects of seasonality and climate change on the emergence and spread of infectious disease remains difficult, in part because of poorly understood connections between warming and the mechanisms driving disease. Trait-based mechanistic models combined with thermal performance curves arising from the metabolic theory of ecology (MTE) have been highlighted as a promising approach going forward; however, this framework has not been tested under controlled experimental conditions that isolate the role of gradual temporal warming on disease dynamics and emergence. Here, we provide experimental evidence that a slowly warming host–parasite system can be pushed through a critical transition into an epidemic state. We then show that a trait-based mechanistic model with MTE functional forms can predict the critical temperature for disease emergence, subsequent disease dynamics through time and final infection prevalence in an experimentally warmed system of Daphnia and a microsporidian parasite. Our results serve as a proof of principle that trait-based mechanistic models using MTE subfunctions can predict warming-induced disease emergence in data-rich systems—a critical step towards generalizing the approach to other systems.

中文翻译：

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气候变暖引起的疾病发生的实验证据及其基于特征的机制模型的预测

预测季节性和气候变化对传染病出现和传播的影响仍然很困难，部分原因是人们对变暖与疾病驱动机制之间的联系知之甚少。基于特性的机械模型与生态代谢理论 (MTE) 产生的热性能曲线相结合，已被强调为一种有前途的方法；然而，该框架尚未在受控实验条件下进行测试，这些条件隔离了逐渐时间变暖对疾病动态和出现的作用。在这里，我们提供了实验证据，证明缓慢变暖的宿主 - 寄生虫系统可以通过关键的过渡进入流行状态。然后，我们展示了具有 MTE 功能形式的基于特征的机械模型可以预测疾病出现的临界温度、随时间变化的后续疾病动态以及在水蚤和微孢子虫寄生虫的实验加热系统中的最终感染流行率。我们的结果证明了原理，即使用 MTE 子功能的基于特征的机械模型可以预测数据丰富的系统中由变暖引起的疾病的出现——这是将该方法推广到其他系统的关键一步。