An important epidemiological problem is to estimate the decay through time of immunity following infection. For this purpose, we propose a semiparametric time series epidemic model that is based on the mechanism of the susceptible-infected-recovered-susceptible system to analyse complex time series data. We develop an estimation method for the model. Simulations show that the approach proposed can capture the non-linearity of epidemics as well as estimate the decay of immunity. We apply our approach to influenza in France and the Netherlands and show a rapid decline in immunity following infection, which agrees with recent spatiotemporal analyses. © 2005 Royal Statistical Society.
CITATION STYLE
Xia, Y., Gog, J. R., & Grenfell, B. T. (2005). Semiparametric estimation of the duration of immunity from infectious disease time series: Influenza as a case-study. Journal of the Royal Statistical Society. Series C: Applied Statistics, 54(3), 659–672. https://doi.org/10.1111/j.1467-9876.2005.05383.x
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