标题： 复杂多年周期的肺炎支原体：持久性和随机性的作用 显示英文标题

标题： Complex multiannual cycles of Mycoplasma pneumoniae: persistence and the role of stochasticity

摘要： 肺炎支原体的流行病学动态特征表现为复杂的、尚不完全理解的多年周期，这给预测带来了挑战。通过使用贝叶斯方法拟合一个具有季节性强迫的传播模型到丹麦（1958-1995年，2010-2025年）的长期监控数据，我们研究了导致肺炎支原体复发性爆发的机制。多年周期的周期（主要约为5年）被解释为系统内两个时间尺度相互作用的结果，一个是内在的，另一个是外在的（季节性的）。虽然该模型对较短的时间序列（几十年）提供了极佳的拟合效果，但我们发现确定性模型最终会进入每年一次的循环模式，无法再现观察到的4-5年的长期周期性。进一步分析显示，该系统表现出瞬态混沌特性并对随机性高度敏感。我们证明了环境（但非纯粹人口统计学）随机性可以通过随机共振维持多年的循环周期。COVID-19非药物干预措施对肺炎支原体传播的影响构成了一种关于大规模扰动效应的自然实验。因此，模型中包含了这些干预措施的效果，并探索了中期预测。我们的研究结果强调了肺炎支原体动力学对扰动和干预措施的固有敏感性，突显了确定性流行病学模型在长期预测方面的局限性。更广泛地说，我们的结果强调了随机性作为潜在驱动因素，在地方性和复发性病原体复杂循环中的作用。 显示英文摘要

摘要： The epidemiological dynamics of Mycoplasma pneumoniae are characterized by complex and poorly understood multiannual cycles, posing challenges for forecasting. Using Bayesian methods to fit a seasonally forced transmission model to long-term surveillance data from Denmark (1958-1995, 2010-2025), we investigate the mechanisms driving recurrent outbreaks of M. pneumoniae. The period of the multiannual cycles (predominantly approx. 5 years in Denmark) are explained as a consequence of the interaction of two time-scales in the system, one intrinsic and one extrinsic (seasonal). While it provides an excellent fit to shorter time series (a few decades), we find that the deterministic model eventually settles into an annual cycle, failing to reproduce the observed 4-5-year periodicity long-term. Upon further analysis, the system is found to exhibit transient chaos and thus high sensitivity to stochasticity. We show that environmental (but not purely demographic) stochasticity can sustain the multi-year cycles via stochastic resonance. The disruptive effects of COVID-19 non-pharmaceutical interventions (NPIs) on M. pneumoniae circulation constitute a natural experiment on the effects of large perturbations. Consequently, the effects of NPIs are included in the model and medium-term predictions are explored. Our findings highlight the intrinsic sensitivity of M. pneumoniae dynamics to perturbations and interventions, underscoring the limitations of deterministic epidemic models for long-term prediction. More generally, our results emphasize the potential role of stochasticity as a driver of complex cycles across endemic and recurring pathogens.