Aguiar Maíra, Ballesteros Sebastién, Boto João Pedro, Kooi Bob W, Mateus Luís, Stollenwerk Nico
Centro de Matemática e Aplicações Fundamentais CMAF, Universidade de Lisboa, Avenida Prof. Gama Pinto 2, 1649-003 Lisboa, Portugal.
Faculty of Earth and Life Sciences, Department of Theoretical Biology, Vrije Universiteit Amsterdam, De Boelelaan 1087, NL 1081 HV Amsterdam, The Netherlands.
AIP Conf Proc. 2011 Sep 14;1389(1):1248-1251. doi: 10.1063/1.3637843.
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 like multi-strain dynamics to describe the virus-host interaction in dengue fever, even most recently developed parameter estimation techniques, like maximum likelihood iterated filtering, come to their computational limits. However, the first results of parameter estimation with data on dengue fever from Thailand indicate a subtle interplay between stochasticity and deterministic skeleton. The deterministic system on its own already displays complex dynamics up to deterministic chaos and coexistence of multiple attractors.
我们重新审视了种群生物动力学系统的参数估计框架，并将其应用于利用经验时间序列校准流行病学中的各种模型，即流感和登革热模型。对于更复杂的模型，如用于描述登革热病毒-宿主相互作用的多毒株动力学模型，即使是最近开发的参数估计技术，如最大似然迭代滤波，也会达到其计算极限。然而，利用泰国登革热数据进行参数估计的初步结果表明，随机性与确定性框架之间存在微妙的相互作用。确定性系统本身就已经表现出复杂的动力学，直至确定性混沌以及多个吸引子的共存。
