HOW INITIAL PUBLIC OPINION ON VACCINATION AFFECTS VACCINATION ADHERENCE DURING INFECTIOUS DISEASE OUTBREAK: AN AGENT-BASED SIMULATION STUDY IN A RANDOMLY GENERATED SOCIAL NETWORK

Purpose:  One of the most striking public health achievements has been the near eradication of vaccine-preventable diseases. However, studies suggest that the number of people deciding to vaccinate has been decreasing. Because of the novelty and involved uncertainty of the threat of a pandemic like H1N1, consumers' opinions are likely to be shaped by social influence processes. Therefore, understanding the impact of low-level vaccination support within a complex social network is critical to efficient deployment of vaccination in the public both from a theoretical and policy-making perspective. 

Method: We conducted an agent-based simulation study, in which we attempted to explore factors that may affect the vaccination adherence rate in a randomly generated social network modeling connections among both friends and family members. Drawing upon behavioral models in individual decision making, our simulation aimed to explore the impact of social influence. In the simulation, agents contacted each other according to a specified contact rule and updated their individual opinions according to a specified decision rule that integrated the opinions of their fellow neighbors who were contacted. Each agent was associated with a four-member family and randomly connected to at most seven friends. We systematically varied (a) initial percentage of agents favoring vaccination, b) how agents regarded expertise (decision rule), and (c) whether agents contacted their friends and to what extent (contact rule).

Result: It is more likely to

·         form negative opinion towards vaccination within the entire population of consumers when all of them ignore expertise entirely (Figures 1 vs. 2; more than 30% of initial population favoring vaccination is needed (Figure 1));

·         form positive opinion within the entire population if communications exist among both friends and family members (Figure 2 vs. 4; 70% of initial population is sufficient (Figure 2)); and

·         form positive opinion within the entire population if all consumers entirely rely on expert's opinion among their contacts (comparing Figures 1 – 3; 60% of initial population is sufficient (Figure 1)).

Conclusions:   Our agent-based simulation model has the potential to play the proof-of-the-concept role to assist policy-makers' investigation of the effect of individual support on the possibility of vaccination adherence in a complex social network. Therefore, it may assist scenario analysis on resource allocation and personnel planning for mass vaccination campaign.