Agent-Based Modelling of Vaccine Hesitancy and Public Trust: Special Reference to West Bengal, India

Abstract

Vaccine hesitancy has emerged as one of the most pressing public health challenges in the twenty-first century, particularly in the aftermath of the COVID-19 pandemic. While immunisation programmes have substantially reduced morbidity and mortality worldwide, varying levels of public trust, misinformation, social influence, and institutional credibility continue to shape vaccination behaviour. In West Bengal, diverse socio-economic conditions, cultural heterogeneity, rural-urban disparities, and differential access to healthcare create complex patterns of vaccine acceptance and refusal. Traditional epidemiological models often fail to capture these behavioural and social dynamics because they treat populations as homogeneous groups. Agent-Based Modelling (ABM) offers an alternative computational framework by representing individuals as autonomous agents whose decisions evolve through interactions within social networks.
This study proposes a sociologically informed ABM to analyse vaccine hesitancy and public trust in West Bengal. The model integrates sociological theories of social capital, risk perception, institutional trust, and social influence with computational simulation techniques. Five principal determinants are incorporated into the model: institutional trust, misinformation exposure, peer influence, perceived vaccine safety, and healthcare accessibility. Each agent updates its vaccination decision dynamically based on interactions with neighbouring agents and changing information environments. The study also introduces a Public Trust–Vaccine Hesitancy Index (PTVHI) to quantify the combined effects of trust and misinformation on vaccine uptake. The empirical framework is designed around a synthetic dataset of 2,000 respondents representing different districts of West Bengal, enabling advanced statistical analyses including Structural Equation Modelling (SEM), logistic regression, and network analysis alongside simulation experiments.
The findings are expected to demonstrate that institutional trust functions as a protective factor against misinformation, while strong social networks can either reinforce vaccine acceptance or amplify hesitancy depending on prevailing community norms. The proposed model contributes to mathematical sociology by integrating behavioural decision-making, computational simulation, and public health governance into a unified analytical framework. It further provides evidence-based policy recommendations for improving vaccination campaigns, strengthening public trust, and promoting equitable healthcare delivery in India and other developing regions.