感染症のダイナミクス

概要

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Recurrent outbreaks of infectious diseases such as measles, mumps and rubella indicate the fairly strong periodicities accompanied with irregularities. Recently, the prevalence of infectious diseases has been explained in terms of chaotic dynamics. With respect to chaotic time series, it is said that we can make a short-term prediction.In this paper, we present a short review for applications of a newly devised procedure of time series analysis to the incidence data of infectious diseases and the time series numerically generated from a mathematical model, called susceptible / exposed / infectious / recovered (SEIR) model for recurrent infectious disease. Several characteristics to be a measure of chaotic systems were indicated. The present method was successfully used to predict the incidence of measles quantitatively. The mechanism of epidemics of fifteen infectious diseases were classified into the three typical patterns, according to the resemblance of temporal variational structures of the incidence data. Results of the quantitative estimation of the effect of mass vaccinations on measles were also indicated.
札幌医科大学の論文
2003-12-01