During the course of an epidemic , individuals constantly make decisions on how to fight against epidemic spreading. Collectively, these individual decisions are critical to the global outcome of the epidemic , especially when no pharmaceutical interventions are available . However, existing epidemic models lack the ability to capture this complex decision-making process, which is shaped by an interplay of factors including government-mandated policy interventions, expected socio-economic costs, perceived infection risks and social influences. Here, we introduce a novel parsimonious  model, grounded in evolutionary game theory, able to capture decision-making dynamics over heterogeneous time scales. Using real data, we analyse three case studies in the spreading of gonorrhoea, the 1918--19 Spanish flu and COVID-19. Behavioural factors shaping the course of the epidemic are intelligibly mapped onto a minimal set of model parameters , and their interplay gives rise to characteristic phenomena , such as sustained periodic outbreaks, multiple epidemic waves, or  a successful eradication of the disease. Our modelenables a direct assessment of the epidemiological and socio-economic impact of different policy interventions implemented to combat epidemic outbreaks. Besides the common-sense finding that stringent non-pharmaceutical interventions are essential to taming the initial phases of the outbreak, the duration of such interventions and the way they are phased out are key for an eradication in the medium-to-long term. Surprisingly, our findings reveal that social influence is a double-edged sword in the control of epidemics, helping strengthen collective adoption of self-protective behaviours during the early stages of the epidemic, but then accelerating their rejection upon lifting of non-pharmaceutical containment interventions .
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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, individuals constantly make decisions on how to fight against epidemic spreading. Collectively, these individual decisions are critical to the global outcome of the epidemic , especially when no pharmaceutical interventions are available
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decision-making process, which is shaped by an interplay of factors including government-mandated policy interventions, expected socio-economic costs, perceived infection risks and social influences. Here, we
interdependence over the entire course of the epidemic. We
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dynamics over heterogeneous time scales. Using real data, we analyse three case studies in the spreading of gonorrhoea, the 1918--19 Spanish flu and COVID-19. Behavioural factors shaping the course of the epidemic are intelligibly
and epidemics co-evolve, shaped by an interplay of factors
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---including government-mandated interventions, socio-economic costs, perceived infection risks and social influences. This
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characteristic phenomena
a range of characteristic phenomena that can be captured within this general framework
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Our modelenables a direct assessment of the epidemiological and socio-economic impact of different policy interventions implemented to combat epidemic outbreaks. Besides the common-sense finding that stringent non-pharmaceutical interventions are essential to taming the initial phases of the outbreak, the duration of such interventions and the way they are phased out are key for an eradication in the medium-to-long term. Surprisingly, our findings reveal that social influence is a double-edged sword in the control of epidemics, helping strengthen collective adoption of self-protective behaviours during the early stages of the epidemic, but then accelerating their rejection upon lifting of non-pharmaceutical containment interventions
The model's potentialities are demonstrated by three case studies based on real-world gonorrhoea, 1918--19 Spanish flu and COVID-19