Please use this identifier to cite or link to this item: https://doi.org/10.1111/j.1467-9876.2005.05383.x
Title: Semiparametric estimation of the duration of immunity from infectious disease time series: Influenza as a case-study
Authors: Xia, Y. 
Gog, J.R.
Grenfell, B.T.
Keywords: Dynamical models in epidemics
Generalized partially linear single-index model
Immunity
Influenza
Kernel smoother
Susceptible-infected-recovered-susceptible model
Issue Date: 2005
Citation: 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. ScholarBank@NUS Repository. https://doi.org/10.1111/j.1467-9876.2005.05383.x
Abstract: 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.
Source Title: Journal of the Royal Statistical Society. Series C: Applied Statistics
URI: http://scholarbank.nus.edu.sg/handle/10635/105353
ISSN: 00359254
DOI: 10.1111/j.1467-9876.2005.05383.x
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