A behavioural modelling approach to assess the impact of COVID-19 vaccine hesitancy

TL;DR

This paper presents a compartmental epidemic model incorporating vaccine hesitancy and information dynamics to analyze COVID-19 transmission, showing that voluntary vaccination reduces but does not eliminate the disease, with information coverage and memory affecting outcomes.

Contribution

It introduces a novel behavioral model with information-based decision-making to assess vaccination impact on COVID-19 spread.

Findings

Voluntary vaccination reduces disease impact but cannot eliminate it.

Higher information coverage and shorter memory decrease hesitancy.

Seasonality influences disease dynamics and vaccination effectiveness.

Abstract

In this paper we introduce a compartmental epidemic model describing the transmission of the COVID-19 disease in presence of non-mandatory vaccination. The model takes into account the hesitancy and refusal of vaccination. To this aim, we employ the information index, which mimics the idea that individuals take their decision on vaccination based not only on the present but also on the past information about the spread of the disease. Theoretical analysis and simulations show clearly as a voluntary vaccination can certainly reduce the impact of the disease but it is unable to eliminate it. We also show how the information-related parameters affect the dynamics of the disease. In particular, the hesitancy and refusal of vaccination is better contained in case of large information coverage and small memory characteristic time. Finally, the possible influence of seasonality is also investigated.