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Reconstructing the transmission dynamics of rubella in Japan, 2012-2013

Author

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  • Masaya M Saito
  • Hiroshi Nishiura
  • Tomoyuki Higuchi

Abstract

Background: Japan experienced a nationwide rubella epidemic from 2012 to 2013, mostly in urban prefectures with large population sizes. The present study aimed to capture the spatiotemporal patterns of rubella using a parsimonious metapopulation epidemic model and examine the potential usefulness of spatial vaccination. Methodology/Principal findings: A metapopulation epidemic model in discrete time and space was devised and applied to rubella notification data from 2012 to 2013. Employing a piecewise constant model for the linear growth rate in six different time periods, and using the particle Markov chain Monte Carlo method, the effective reproduction numbers were estimated at 1.37 (95% CrI: 1.12, 1.77) and 1.37 (95% CrI: 1.24, 1.48) in Tokyo and Osaka groups, respectively, during the growing phase of the epidemic in 2013. The rubella epidemic in 2012 involved substantial uncertainties in its parameter estimates and forecasts. We examined multiple scenarios of spatial vaccination with coverages of 1%, 3% and 5% for all of Japan to be distributed in different combinations of prefectures. Scenarios indicated that vaccinating the top six populous urban prefectures (i.e., Tokyo, Kanagawa, Osaka, Aichi, Saitama and Chiba) could potentially be more effective than random allocation. However, greater uncertainty was introduced by stochasticity and initial conditions such as the number of infectious individuals and the fraction of susceptibles. Conclusions: While the forecast in 2012 was accompanied by broad uncertainties, a narrower uncertainty bound of parameters and reliable forecast were achieved during the greater rubella epidemic in 2013. By better capturing the underlying epidemic dynamics, spatial vaccination could substantially outperform the random vaccination.

Suggested Citation

  • Masaya M Saito & Hiroshi Nishiura & Tomoyuki Higuchi, 2018. "Reconstructing the transmission dynamics of rubella in Japan, 2012-2013," PLOS ONE, Public Library of Science, vol. 13(10), pages 1-15, October.
    • Handle: RePEc:plo:pone00:0205889
    DOI: 10.1371/journal.pone.0205889
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    References listed on IDEAS

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    1. Christophe Andrieu & Arnaud Doucet & Roman Holenstein, 2010. "Particle Markov chain Monte Carlo methods," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 72(3), pages 269-342, June.
    2. Alan E. Gelfand & Sujit K. Ghosh & Cindy Christiansen & Stephen B. Soumerai & Thomas J. McLaughlin, 2000. "Proportional hazards models: a latent competing risk approach," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 49(3), pages 385-397.
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