Semiparametric estimation of the duration of immunity from infectious disease time series: Influenza as a case-study

Yingcun Xia, Julia R. Gog, Bryan T. Grenfell

Research output: Contribution to journalArticlepeer-review

36 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)659-672
Number of pages14
JournalJournal of the Royal Statistical Society. Series C: Applied Statistics
Volume54
Issue number3
DOIs
StatePublished - 2005
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

Keywords

  • Dynamical models in epidemics
  • Generalized partially linear single-index model
  • Immunity
  • Influenza
  • Kernel smoother
  • Susceptible-infected-recovered-susceptible model

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