Abstract

Voluntary vaccination reflects how individuals weigh the risk of infection and the cost of vaccination against the spread of vaccine-preventable diseases, such as smallpox and measles. In a homogeneously mixing population, the infection risk of an individual depends largely on the proportion of vaccinated individuals due to the effects of herd immunity. While in a structured population, the infection risk can also be affected by the structure of individuals’ social network. In this paper, we focus on studying individuals’ self-organizing behaviors under the circumstance of voluntary vaccination in different types of social networks. Specifically, we assume that each individual together with his/her neighbors forms a local well-mixed environment, where individuals meet equally often as long as they have a common neighbor. We carry out simulations on four types of locally-mixed social networks to investigate the network effects on voluntary vaccination. Furthermore, we also evaluate individuals’ vaccinating decisions through interacting with their “neighbors of neighbors”. The results and findings of this paper provide a new perspective for vaccination policy-making by taking into consideration human responses in complex social networks.

Highlights

  • Voluntary vaccination plays an essential role in achieving widespread immunity to many infectious diseases, such as smallpox and measles[1,2,3]

  • It is almost impossible for any individual to have complete knowledge about network structure of the whole population, which make it difficult to predict the dynamics of disease epidemics[30,31,32,33], as well as human behavioral responses[34,35,36]

  • Since the effect of infection force β on disease epidemics and human vaccinating behaviors varies on different networks, it would be necessary to identify the pure effects of network structure

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Summary

Introduction

Voluntary vaccination plays an essential role in achieving widespread immunity to many infectious diseases, such as smallpox and measles[1,2,3]. Perisic and Bauch have shown that social contact structure can enable eradication of an infectious disease under voluntary vaccination[37, 38] In their simulation, individuals decide to vaccinate when the perceived payoff of vaccinating is larger than that of not vaccinating during the epidemic process. Many studies have focused on modeling the epidemic dynamics and immunization on metapopulation networks[46, 47] and multiplex networks[48,49,50,51] Motivated by this consideration, in this paper, we formulate a social contact network as a “network of networks”[52,53,54] by assuming that each individual together with his/her neighbors forms a locally-mixed group. Our model offers a new perspective for analyzing individuals voluntary vaccinating behaviors, which does not rely on social learning among neighboring individuals, nor individuals’ past experiences about vaccination and infection from an infectious disease

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