Bulletin of Mathematical Biology

, Volume 73, Issue 11, pp 2748–2772

Impact of Imitation Processes on the Effectiveness of Ring Vaccination

  • Chad R. Wells
  • Jean M. Tchuenche
  • Lauren Ancel Meyers
  • Alison P. Galvani
  • Chris T. Bauch
Original Article

Abstract

Ring vaccination can be a highly effective control strategy for an emerging disease or in the final phase of disease eradication, as witnessed in the eradication of smallpox. However, the impact of behavioural dynamics on the effectiveness of ring vaccination has not been explored in mathematical models. Here, we analyze a series of stochastic models of voluntary ring vaccination. Contacts of an index case base vaccinating decisions on their own individual payoffs to vaccinate or not vaccinate, and they can also imitate the behaviour of other contacts of the index case. We find that including imitation changes the probability of containment through ring vaccination considerably. Imitation can cause a strong majority of contacts to choose vaccination in some cases, or to choose non-vaccination in other cases—even when the equivalent solution under perfectly rational (non-imitative) behaviour yields mixed choices. Moreover, imitation processes can result in very different outcomes in different stochastic realizations sampled from the same parameter distributions, by magnifying moderate tendencies toward one behaviour or the other: in some realizations, imitation causes a strong majority of contacts not to vaccinate, while in others, imitation promotes vaccination and reduces the number of secondary infections. Hence, the effectiveness of ring vaccination can depend significantly and unpredictably on imitation processes. Therefore, our results suggest that risk communication efforts should be initiated early in an outbreak when ring vaccination is to be applied, especially among subpopulations that are heavily influenced by peer opinions.

Keywords

Ring vaccination Vaccinating behaviour Imitation Networks Modelling 

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Copyright information

© Society for Mathematical Biology 2011

Authors and Affiliations

  • Chad R. Wells
    • 1
  • Jean M. Tchuenche
    • 1
  • Lauren Ancel Meyers
    • 2
  • Alison P. Galvani
    • 3
  • Chris T. Bauch
    • 1
    • 4
  1. 1.Department of Mathematics and StatisticsUniversity of GuelphGuelphCanada
  2. 2.Section of Integrative BiologyUniversity of TexasAustinUSA
  3. 3.School of Public HealthYale UniversityNew HavenUSA
  4. 4.Department of Epidemiology, Biostatistics, and Occupational HealthMcGill UniversityMontrealCanada

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