Centro de Matemática e Aplicações Fundamentais , Universidade de Lisboa, Avenida Prof. Gama Pinto 2, 1649-003 Lisbon , Portugal.
Interface Focus. 2012 Apr 6;2(2):156-69. doi: 10.1098/rsfs.2011.0103. Epub 2012 Feb 1.
We revisit the parameter estimation framework for population biological dynamical systems, and apply it to calibrate various models in epidemiology with empirical time series, namely influenza and dengue fever. When it comes to more complex models such as multi-strain dynamics to describe the virus-host interaction in dengue fever, even the most recently developed parameter estimation techniques, such as maximum likelihood iterated filtering, reach their computational limits. However, the first results of parameter estimation with data on dengue fever from Thailand indicate a subtle interplay between stochasticity and the deterministic skeleton. The deterministic system on its own already displays complex dynamics up to deterministic chaos and coexistence of multiple attractors.
我们重新审视了群体生物动力学系统的参数估计框架，并将其应用于通过经验时间序列对流行病学中的各种模型进行校准，即流感和登革热。当涉及到更复杂的模型，如多株动力学来描述登革热中的病毒-宿主相互作用时，即使是最近开发的参数估计技术，如最大似然迭代滤波，也达到了其计算极限。然而，利用来自泰国的登革热数据进行参数估计的初步结果表明，随机性和确定性骨架之间存在微妙的相互作用。仅确定性系统本身就已经显示出复杂的动力学，包括确定性混沌和多个吸引子的共存。
