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Individuals socio-demographic and economic characteristics crucially shapethe spread of an epidemic by largely determining the exposure level to thevirus and the severity of the disease for those who got infected. While thecomplex interplay between individual characteristics and epidemic dynamics iswidely recognized, traditional mathematical models often overlook thesefactors. In this study, we examine two important aspects of human behaviorrelevant to epidemics: contact patterns and vaccination uptake. Using datacollected during the Covid-19 pandemic in Hungary, we first identify thedimensions along which individuals exhibit the greatest variation in theircontact patterns and vaccination attitudes. We find that generally privilegedgroups of the population have higher number of contact and a higher vaccinationuptake with respect to disadvantaged groups. Subsequently, we propose adata-driven epidemiological model that incorporates these behavioraldifferences. Finally, we apply our model to analyze the fourth wave of Covid-19in Hungary, providing valuable insights into real-world scenarios. By bridgingthe gap between individual characteristics and epidemic spread, our researchcontributes to a more comprehensive understanding of disease dynamics andinforms effective public health strategies.

Social inequalities that matter for contact patterns, vaccination, and the spread of epidemics