Oscillatory dynamics in the dilemma of social distancing
Alina Glaubitz, Feng Fu

TL;DR
This paper models the oscillatory social distancing behavior during epidemics using evolutionary game theory, revealing how individual decision-making impacts infection waves and disease mitigation.
Contribution
It introduces a novel model combining epidemiology and adaptive social learning to explain oscillations in social distancing and infection dynamics.
Findings
Oscillatory social distancing dynamics lead to infection waves.
Social distancing effectiveness depends on individual responsiveness and rationality.
Oscillations diminish as herd immunity is reached.
Abstract
Social distancing as one of the main non-pharmaceutical interventions can help slow down the spread of diseases, like in the COVID-19 pandemic. Effective social distancing, unless enforced as drastic lockdowns and mandatory cordon sanitaire, requires consistent strict collective adherence. However, it remains unknown what the determinants for the resultant compliance of social distancing and their impact on disease mitigation are. Here, we incorporate into the epidemiological process with an evolutionary game theory model that governs the evolution of social distancing behavior. In our model, we assume an individual acts in their best interest and their decisions are driven by adaptive social learning of the real-time risk of infection in comparison with the cost of social distancing. We find interesting oscillatory dynamics of social distancing accompanied with waves of infection.…
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