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SUMMARY This paper examines the impact of seasonality and chaotic dynamics in simple models for the population dynamics of measles on the probability of fade-out of infection. It uses Monte Carlo simulations of the seasonally forced SEIR model, with parameters appropriate to a city of 1 million people. The incidence of fade-out in a spatially homogeneous model is compared with simple spatial models involving various degrees of coupling between subareas. The results indicate a significant degree of fade-out of infection, which is not consistent with previously derived criteria for the persistence of measles. Lowering the degree of spatial coupling does not substantially reduce the extent of fade-out. A simple non-linear analysis of the simulated series is presented, and the epidemiological implications of these results are discussed.
Bryan T. Grenfell (Wed,) studied this question.
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