TY - JOUR T1 - Evolutionary Game Theory and Social Learning Can Determine How Vaccine Scares Unfold A1 - Bauch, Chris T. A1 - Bhattacharyya, Samit Y1 - 2012/04/05 N2 - Author Summary “Herd immunity” is a phenomenon whereby an entire population—including unvaccinated individuals—can be protected from infection by vaccinating only a certain percentage of the population. This suggests that immunization programs can be victims of their own success: past vaccinations can drive disease incidence to such low levels that as-yet unvaccinated individuals feel no incentive to get vaccinated, which creates conditions for future outbreaks. “Behavior-incidence” models capture this interplay between disease dynamics and vaccinating behavior. However, the predictive and explanatory value of these models is rarely tested against empirical data, and it is not clear whether the implied strategic interaction between individuals drives vaccinating behavior in real populations. Here we develop a behavior-incidence model based on evolutionary game theory and social learning. We show it often explains vaccine coverage data during a vaccine scare better than most competing models without strategic interactions and/or social learning. It can also predict future vaccine coverage and disease incidence peaks to a significant extent. Thus, strategic interactions between individuals via herd immunity appear to be a significant driver of behavior during a vaccine scare. It may be possible to harness behavior-incidence models to predict how future vaccine scares might unfold and possibly also to mitigate them. JF - PLOS Computational Biology JA - PLOS Computational Biology VL - 8 IS - 4 UR - https://doi.org/10.1371/journal.pcbi.1002452 SP - e1002452 EP - PB - Public Library of Science M3 - doi:10.1371/journal.pcbi.1002452 ER -