Using Game Theory to Examine Incentives in Influenza Vaccination Behavior

Chapman, Gretchen B.; Li, Meng; Vietri, Jeffrey; Ibuka, Yoko; Thomas, D.W.P.; Yoon, Haewon; Galvani, Alison P.

doi:10.1177/0956797612437606

Cited by 88 publications

(66 citation statements)

References 10 publications

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“…For influenza, altruism has been suggested as a mechanism for boosting vaccine coverage [7,[24][25][26]. However, for paediatric infectious diseases, it is unclear whether altruism is an important motivating factor in vaccine decision-making [4,27,28].…”

Section: Introductionmentioning

confidence: 99%

The influence of social norms on the dynamics of vaccinating behaviour for paediatric infectious diseases

2014

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Mathematical models that couple disease dynamics and vaccinating behaviour often assume that the incentive to vaccinate disappears if disease prevalence is zero. Hence, they predict that vaccine refusal should be the rule, and elimination should be difficult or impossible. In reality, countries with non-mandatory vaccination policies have usually been able to maintain elimination or very low incidence of paediatric infectious diseases for long periods of time. Here, we show that including injunctive social norms can reconcile such behaviour-incidence models to observations. Adding social norms to a coupled behaviour-incidence model enables the model to better explain pertussis vaccine uptake and disease dynamics in the UK from 1967 to 2010, in both the vaccine-scare years and the years of high vaccine coverage. The model also illustrates how a vaccine scare can perpetuate suboptimal vaccine coverage long after perceived risk has returned to baseline, pre-vaccine-scare levels. However, at other model parameter values, social norms can perpetuate depressed vaccine coverage during a vaccine scare well beyond the time when the population's baseline vaccine risk perception returns to pre-scare levels. Social norms can strongly suppress vaccine uptake despite frequent outbreaks, as observed in some small communities. Significant portions of the parameter space also exhibit bistability, meaning long-term outcomes depend on the initial conditions. Depending on the context, social norms can either support or hinder immunization goals.

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Section: Introductionmentioning

confidence: 99%

The influence of social norms on the dynamics of vaccinating behaviour for paediatric infectious diseases

2014

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“…For example, altruism could enhance vaccination uptake [7] [24]. Studies have argued bandwagoning effects and the role of imitations in vaccination decisions [7] [25], and peer effects through social network are also known factors to determine health behavior [26].…”

Section: Discussionmentioning

confidence: 99%

Free-Riding Behavior in Vaccination Decisions: An Experimental Study

et al. 2014

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Individual decision-making regarding vaccination may be affected by the vaccination choices of others. As vaccination produces externalities reducing transmission of a disease, it can provide an incentive for individuals to be free-riders who benefit from the vaccination of others while avoiding the cost of vaccination. This study examined an individual's decision about vaccination in a group setting for a hypothetical disease that is called “influenza” using a computerized experimental game. In the game, interactions with others are allowed. We found that higher observed vaccination rate within the group during the previous round of the game decreased the likelihood of an individual's vaccination acceptance, indicating the existence of free-riding behavior. The free-riding behavior was observed regardless of parameter conditions on the characteristics of the influenza and vaccine. We also found that other predictors of vaccination uptake included an individual's own influenza exposure in previous rounds increasing the likelihood of vaccination acceptance, consistent with existing empirical studies. Influenza prevalence among other group members during the previous round did not have a statistically significant effect on vaccination acceptance in the current round once vaccination rate in the previous round was controlled for.

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“…Many experts are now referring to the decrease of vaccination rates as a confidence crisis linked to the spreading of unscientific myths on social media, but also to socio-economical, socio-cultural, psychological, and political factors [7,388,404,[741][742][743]. The features of online discussions about these and other topics can be mapped and as discussed in Section 9 used to model behavior-vaccination dynamics [738,739,[744][745][746][747].…”

Section: Social Media Based Methodsmentioning

confidence: 99%

Statistical physics of vaccination

et al. 2016

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Historically, infectious diseases caused considerable damage to human societies, and they continue to do so today. To help reduce their impact, mathematical models of disease transmission have been studied to help understand disease dynamics and inform prevention strategies. Vaccination-one of the most important preventive measures of modern times-is of great interest both theoretically and empirically. And in contrast to traditional approaches, recent research increasingly explores the pivotal implications of individual behavior and heterogeneous contact patterns in populations. Our report reviews the developmental arc of theoretical epidemiology with emphasis on vaccination, as it led from classical models assuming homogeneously mixing (mean-field) populations and ignoring human behavior, to recent models that account for behavioral feedback and/or population spatial/social structure. Many of the methods used originated in statistical physics, such as lattice and network models, and their associated analytical frameworks. Similarly, the feedback loop between vaccinating behavior and disease propagation forms a coupled nonlinear system with analogs in physics. We also review the new paradigm of digital epidemiology, wherein sources of digital data such as online social media are mined for high-resolution information on epidemiologically relevant individual behavior. Armed with the tools and concepts of statistical physics, and further assisted by new sources of digital data, models that capture nonlinear interactions between behavior and disease dynamics offer a novel way of modeling real-world phenomena, and can help improve health outcomes. We conclude the review by discussing open problems in the field and promising directions for future research.

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Using Game Theory to Examine Incentives in Influenza Vaccination Behavior

Cited by 88 publications

References 10 publications

The influence of social norms on the dynamics of vaccinating behaviour for paediatric infectious diseases

The influence of social norms on the dynamics of vaccinating behaviour for paediatric infectious diseases

Free-Riding Behavior in Vaccination Decisions: An Experimental Study

Statistical physics of vaccination

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