Dynamics of epidemic spreading with vaccination: Impact of social pressure and engagement

Abstract

In this work we consider a model of epidemic spreading coupled with an opinion dynamics in a fully-connected population. Regarding the opinion dynamics, the individuals may be in two distinct states, namely in favor or against a vaccination campaign. Individuals against the vaccination follow a standard SIS model, whereas the pro-vaccine individuals can also be in a third compartment, namely Vaccinated.In addition, the opinions change according to the majority-rule dynamics in groups with three individuals. We also consider that the vaccine can give permanent or temporary immunization to the individuals. By means of analytical calculations and computer simulations, we show that the opinion dynamics can drastically affect the disease propagation, and that the engagement of the pro-vaccine individuals can be crucial for stopping the epidemic spreading. The full numerical code for simulate the model is available from the authors' webpage.

Sudden transitions in coupled opinion and epidemic dynamics with vaccination

“…Considering the Vaccinated agents, we considered that the vaccine is not permanent, so a vaccinated agent becomes susceptible again with rate φ, the resusceptibility probability [19,20]. Summarizing, the individuals can undergo the following transitions among the epidemic compartments: As previous behavioral change models [13,18,[21][22][23][24], we have not employed a game theory approach, but rather we have considered a mixed belief-based model that also includes risk perception of becoming infected (prevalence-based information). This is a plausible hypothesis as was shown in [23]: "assumptions of economic rationality and payoff maximization are not mandatory for predicting commonly observed dynamics of vaccination coverage".…”

Coupling Epidemiological Models with Social Dynamics

“…Several authors divided the susceptible population in three (or more) different groups, the vaccinated, the non-vaccinated individuals, and the ones that decided to remain non-vaccinated, see for instance (Bauch 2005;Bauch and Earn 2004;Pires and Crokidakis 2017). Also, related models considered two groups of susceptible agents, the ones who are aware and those who are not aware of the threat of an infection (Clancy 2018;Misra et al 2011;Yang et al 2017).…”

“…In particular, when vaccines are available, opinion-based models were used to analyze the transition from susceptible to vaccinated states, as a result of social interactions, see (Dorso et al. 2017 ; Pires and Crokidakis 2017 ). However, the decision of being vaccinated depends on other factors like their cost, risks, and perceived advantages, see for instance the Bauch’s work (Bauch 2005 ), where a replicator-type equation was added to a classical SIR model, and the payoff of being vaccinated changes depending on the risk of contagion.…”

SIR Dynamics with Vaccination in a Large Configuration Model

“…Let us observe that the authors in [ 21 ] propose an evolutionary game-theoretic problem, where individuals use evidence to estimate costs of vaccination, the model being based on the agent point of view. Vaccination strategies can also be influenced by a neighborhood behavior and may depend on the individual’s beliefs about their neighborhood vaccination strategies [ 36 , 45 ]. Another approach can be found in [ 22 ], where they study how the psychology of individuals intervenes in their perception of their risk, susceptibility or mortality rates.…”