Experiments and models suggest that climate affects mosquito‐borne disease transmission. However, disease transmission involves complex nonlinear interactions between climate and population dynamics, which makes detecting climate drivers at the population level challenging. By analysing incidence data, estimated susceptible population size, and climate data with methods based on nonlinear time series analysis (collectively referred to as empirical dynamic modelling), we identified drivers and their interactive effects on dengue dynamics in San Juan, Puerto Rico. Climatic forcing arose only when susceptible availability was high: temperature and rainfall had net positive and negative effects respectively. By capturing mechanistic, nonlinear and context‐dependent effects of population susceptibility, temperature and rainfall on dengue transmission empirically, our model improves forecast skill over recent, state‐of‐the‐art models for dengue incidence. Together, these results provide empirical evidence that the interdependence of host population susceptibility and climate drives dengue dynamics in a nonlinear and complex, yet predictable way.

中文翻译：

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易感宿主可用性调节气候对登革热动态的影响

实验和模型表明，气候会影响蚊媒疾病的传播。然而，疾病传播涉及气候和人口动态之间复杂的非线性相互作用，这使得在人口层面检测气候驱动因素具有挑战性。通过使用基于非线性时间序列分析（统称为经验动态建模）的方法分析发病率数据、估计的易感人群规模和气候数据，我们确定了驱动因素及其对波多黎各圣胡安登革热动态的交互影响。气候强迫仅在易受影响的可用性高时出现：温度和降雨分别具有净正面和负面影响。通过捕捉人口易感性的机械、非线性和环境相关影响，从经验上看，温度和降雨对登革热传播的影响，我们的模型比最近的登革热发病率模型提高了预测技巧。总之，这些结果提供了经验证据，表明宿主种群易感性和气候的相互依赖以非线性和复杂但可预测的方式驱动登革热动态。