A computational approach to studying possible scenarios of complex social contagion on vaccination behaviour
This project is aimed to the use of simulation techniques for the study of the spread of complex dynamics of health behaviors and, in our case, specifically related to the decision to vaccinate.
Specific research objective:
- To explore the drivers of the social contagion of vaccination attitudes and vaccine hesitancy.
- To analyze which are factors (i.e., influencers, network topologies, message contents, etc) that may amplify or reduce the propagation of vaccine hesitancy.
As a complementary technique to social networks analysis (SNA), experimental data, qualitative and quantitative evidence from previous case studies, Agent-Based Modelling (ABM) will be used to explore how collective dynamics of opinion contagion can evolve under different simulated scenarios. ABM aims to simulate the behaviour of autonomous artificial agents and also their interactions in the system as a whole. The main advantage of this methodology is not only the possibility of re-creating and predicting social behaviour, but in particular of studying the emergence and evolution of complex (social) phenomena which, as the spread of anti-vaccination attitudes, are difficult to capture and understand using conventional methods.
The evidence to be discussed from the Case Studies (supported by external funders) are related to (a) understanding how attitudes of young people towards vaccination are built from different information sources, both on- and off-line using a mixed methods approach interviewing and surveying students at Bordeaux; (b) understanding how participants in a virtual online network spread vaccination-related attitudes (social contagion) using funding established at the University of Cyprus and (c) exploring innovative methods to assess social contagion of vaccination attitudes using Computer Agent-Based Modelling with simulations at the University of Cadiz.
Led by: Javier Alvarez-Galvez, University of Cadiz