Epidemic prevalence information on social networks mediates emergent collective outcomes in voluntary vaccine schemes

TL;DR

This paper models how social network information influences voluntary vaccination decisions, showing that local prevalence data can significantly reduce epidemic size and impact public health strategies.

Contribution

It introduces an integrated model where rational agents adapt vaccination behavior based on local and global epidemic information, revealing the importance of information type on vaccination outcomes.

Findings

Local prevalence information can lead to higher vaccine coverage.

For less contagious diseases, collective behavior significantly reduces epidemic size.

Near the epidemic threshold, vaccination responses can be dichotomous.

Abstract

The success of a vaccination program is crucially dependent on its adoption by a critical fraction of the population, as the resulting herd immunity prevents future outbreaks of an epidemic. However, the effectiveness of a campaign can engender its own undoing if individuals choose to not get vaccinated in the belief that they are protected by herd immunity. Although this may appear to be an optimal decision, based on a rational appraisal of cost and benefits to the individual, it exposes the population to subsequent outbreaks. We investigate if voluntary vaccination can emerge in a an integrated model of an epidemic spreading on a social network of rational agents that make informed decisions whether to be vaccinated. The information available to each agent includes the prevalence of the disease in their local network neighborhood and/or globally in the population, as well as the fraction of their neighbors that are protected against the disease. Crucially, the payoffs governing the decision of agents evolve with disease prevalence, resulting in the co-evolution of vaccine uptake behavior with the spread of the contagion. The collective behavior of the agents responding to local prevalence can lead to a significant reduction in the final epidemic size, particularly for less contagious diseases having low basic reproduction number $R_0$. Near the epidemic threshold ($R_0\approx1$) the use of local prevalence information can result in a dichotomous response in final vaccine coverage. The implications of our results suggest the nature of information used by individuals is a critical factor determining the success of public health intervention schemes that involve mass vaccination.