Modelling collective decision-making during epidemics
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The outcome of an epidemic outbreak can be critically shaped by the collective behavioural response of the population. Likewise, individual decision-making is highly influenced by the overwhelming pressure of epidemic spreading. However, existing models lack the ability to capture this complex interdependence over the entire course of the epidemic. We introduce a novel parsimonious network model, grounded in evolutionary game theory, in which decision-making and epidemics co-evolve, shaped by an interplay of factors mapped onto a minimal set of model parameters —including government-mandated interventions, socio-economic costs, perceived infection risks and social influences. This interplay gives rise to a range of characteristic phenomena that can be captured within this general framework, such as sustained periodic outbreaks, multiple epidemic waves, or prompt behavioural response ensuring a successful eradication of the disease. The model's potentialities are demonstrated by three case studies based on real-world gonorrhoea, 1918–19 Spanish flu and COVID-19.
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