Disentangling extrinsic from intrinsic factors in disease dynamics: A nonlinear time series approach with an application to cholera
Disentangling extrinsic from intrinsic factors in disease dynamics: A nonlinear time series approach with an application to cholera
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DOI：
10.1086/420798
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发表时间：
2004-06-01
影响因子：
2.9
通讯作者：
Pascual, M
中科院分区：
文献类型：
--
作者：
Koelle, K;Pascual, M
对疾病和其他种群周期的其他解释通常包括外部环境驱动因素，如气候变化，以及系统内反馈产生的内在非线性动力学，如物种相互作用和密度依赖。由于这些不同的因素可以在非线性系统中相互作用，并且可以引起其频率不同于外部驱动器的振荡，因此很难从时间种群模式中确定它们各自的贡献。在疾病的情况下，免疫力是一个重要的内在因素。然而，对于许多疾病，如霍乱，免疫力是暂时的，免疫力的持续时间和衰减模式并不为人所知。我们提出了一个非线性的时间序列模型，有两个相关的目标：重建的免疫模式的数据的情况下，人口规模和识别的外在和内在因素的动态中的各自作用。这里的外在因素包括强迫的季节性和长期变化或年际变化。模拟结果表明，这种半参数方法成功地恢复了免疫力的衰减，并确定了年际变化的来源。历史霍乱数据的应用表明，临时免疫力可以持久，并在大约9年内衰减。传递率的外部强迫被确定为具有很强的季节分量，沿着长期下降。此外，噪声似乎在长期动态中维持多个频率。类似的半参数模型应适用于疾病以外的人口数据。
Alternative explanations for disease and other population cycles typically include extrinsic environmental drivers, such as climate variability, and intrinsic nonlinear dynamics resulting from feedbacks within the system, such as species interactions and density dependence. Because these different factors can interact in nonlinear systems and can give rise to oscillations whose frequencies differ from those of extrinsic drivers, it is difficult to identify their respective contributions from temporal population patterns. In the case of disease, immunity is an important intrinsic factor. However, for many diseases, such as cholera, for which immunity is temporary, the duration and decay pattern of immunity is not well known. We present a nonlinear time series model with two related objectives: the reconstruction of immunity patterns from data on cases and population sizes and the identification of the respective roles of extrinsic and intrinsic factors in the dynamics. Extrinsic factors here include both seasonality and long-term changes or interannual variability in forcing. Results with simulated data show that this semiparametric method successfully recovers the decay of immunity and identifies the origin of interannual variability. An application to historical cholera data indicates that temporary immunity can be long-lasting and decays in approximately 9 yr. Extrinsic forcing of transmissibility is identified to have a strong seasonal component along with a long-term decrease. Furthermore, noise appears to sustain the multiple frequencies in the long-term dynamics. Similar semiparametric models should apply to population data other than for disease.