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[智利传染病动态的非线性分析]

[Non linear analysis of infection diseases dynamics in Chile].

作者信息

Canals M, Labra F

机构信息

Departamento de Ciencias Ecológicas, Facultad de Ciencias, Universidad de Chile.

出版信息

Rev Med Chil. 1999 Sep;127(9):1086-92.

PMID:10752272
Abstract

BACKGROUND

The incidence of infectious diseases generally has large fluctuations, probably due to interactions between seasonal fluctuations and those secondary to case-susceptible host interactions.

AIM

To analyze the complexity and attractant topological resemblance of seven infectious diseases in Chile.

MATERIAL AND METHODS

The annual incidence of measles, whooping cough, scarlet fever, meningococcal meningitis, diphtheria, typhoid fever and poliomyelitis was obtained from the annual reports of diseases. Correlation dimensions and the largest Lyapunov series exponents were estimated. The resemblance among their attractants was assessed by Hausdorff distance. The measures were performed both before and after seasonal filtering.

RESULTS

All series showed a dynamics near low dimensional chaos. The correlation dimensions ranged between 2.12 and 2.76. The correlation dimensions did not change after seasonal differentiation. Apart from one, all disease dynamics had large Lyapunov exponents, near 0.6 Bits/year. These decreased if series were differentiated. Before differentiation, the topological resemblance was mainly caused by the seasonal component of the dynamics but thereafter, the resemblance increased. In spite of different transmission mechanisms and etiologies, all analyzed infectious diseases conformed a truly single group, during cluster analyses.

CONCLUSIONS

These results suggest that beneath the dynamics of infectious diseases, obscured by seasonal environmental factors, lays a very consistent nonlinear agent-susceptible host dynamics.

摘要

背景

传染病的发病率通常有很大波动,这可能是由于季节性波动与病例易感宿主相互作用所导致的继发性波动之间的相互作用。

目的

分析智利七种传染病的复杂性和吸引子拓扑相似性。

材料与方法

从疾病年度报告中获取麻疹、百日咳、猩红热、脑膜炎球菌性脑膜炎、白喉、伤寒和脊髓灰质炎的年发病率。估计关联维数和最大李雅普诺夫序列指数。通过豪斯多夫距离评估它们吸引子之间的相似性。在季节性滤波前后都进行了测量。

结果

所有序列都显示出接近低维混沌的动态。关联维数在2.12至2.76之间。季节性分化后关联维数没有变化。除一种疾病外,所有疾病动态都有较大的李雅普诺夫指数,接近0.6比特/年。如果对序列进行分化,这些指数会降低。在分化之前,拓扑相似性主要由动态的季节性成分引起,但此后相似性增加。尽管传播机制和病因不同,但在聚类分析中,所有分析的传染病都形成了一个真正单一的组。

结论

这些结果表明,在季节性环境因素掩盖下的传染病动态之下,存在着非常一致的非线性病原体 - 易感宿主动态。

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