Pandemic waves as the outcome of coupled social and disease dynamics: a mathematical modelling study.

The COVID-19 pandemic was strongly shaped by population behavioural responses. As cases surged, populations adopted contact precautions that reduced infection levels. This, in turn encouraged relaxation of control measures and prepared the ground for the next pandemic wave. Standard mathematical models do not account for this interaction between infection dynamics and behaviour. Here, we compare a standard transmission model to a coupled behaviour-disease model. We parameterise the models for 13 European countries, using data on SARS-CoV-2 infection incidence and stringency of control measures. We show how coupling behavioural and disease dynamics improves the ability of mathematical models to explain and predict crucial features of pandemic waves. Our findings demonstrate how behavioural feedback influences not only current transmission patterns but also the timing and magnitude of future pandemic waves. Such models could help decision-makers anticipate population responses to public health interventions, thereby contributing to scenario planning and intervention design.