Sudden transitions in coupled opinion and epidemic dynamics with vaccination

Abstract

This work consists of an epidemic model with vaccination coupled with an opinion dynamics. Our objective was to study how disease risk perception can influence opinions about vaccination and therefore the spreading of the disease. Differently from previous works we have considered continuous opinions. The epidemic spreading is governed by an SIS-like model with an extra vaccinated state. In our model individuals vaccinate with a probability proportional to their opinions. The opinions change due to peer influence in pairwise interactions. The epidemic feedback to the opinion dynamics acts as an external field increasing the vaccination probability. We performed Monte Carlo simulations in fully-connected populations. Interestingly we observed the emergence of a first-order phase transition, besides the usual activeabsorbing phase transition presented in the SIS model. Our simulations also show that with a certain combination of parameters, an increment in the initial fraction of the population that is pro-vaccine has a twofold effect: it can lead to smaller epidemic outbreaks in the short term, but it also contributes to the survival of the chain of infections in the long term. Our results also suggest that it is possible that more effective vaccines can decrease the long-term vaccine coverage. This is a counterintuitive outcome, but it is in line with empirical observations that vaccines can become a victim of their own success.

Three-state opinion dynamics in modular networks

“…In a recent work [59] it was discussed how abrupt changes in the global opinion of a population can affect the spreading of diseases when a vaccination campaign is taken into account. In the mentioned model, the opinions against and in favor of the vaccination influences directly the vaccination probability of the agents.…”

Epidemic spreading with awareness and different timescales in multiplex networks

“…In particular, individual prevention methods can considerably reduce the overall incidence of a disease, but the acknowledgment of the methods and the decision to adopt them depend on behavioral factors. The latter have been modeled using opinion dynamics [12][13][14][15], game-theoretical approaches [16][17][18][19], spreading processes [20][21][22][23][24][25], risk perception [26][27][28][29][30], and other approaches [10]. * francisco@icmc.usp.br…”

A model of opinion dynamics with echo chambers explains the spatial distribution of vaccine hesitancy

“…A more recent strand of literature on vaccine hesitancy bypasses utilitarian considerations and focuses directly on opinion dynamics [60,3,56]. Rather than modeling individual decisions as a result of utility maximization, the individual is seen as being influenced by the social environment; e.g.…”