Litcius/Paper detail

Contact rate epidemic control of COVID-19: an equilibrium view

Romuald Elie, Emma Hubert, Gabriel Turinici

2020Mathematical Modelling of Natural Phenomena59 citationsDOIOpen Access PDF

Abstract

We consider the control of the COVID-19 pandemic through a standard SIR compartmental model. This control is induced by the aggregation of individuals’ decisions to limit their social interactions: when the epidemic is ongoing, an individual can diminish his/her contact rate in order to avoid getting infected, but this effort comes at a social cost. If each individual lowers his/her contact rate, the epidemic vanishes faster, but the effort cost may be high. A Mean Field Nash equilibrium at the population level is formed, resulting in a lower effective transmission rate of the virus. We prove theoretically that equilibrium exists and compute it numerically. However, this equilibrium selects a sub-optimal solution in comparison to the societal optimum (a centralized decision respected fully by all individuals), meaning that the cost of anarchy is strictly positive. We provide numerical examples and a sensitivity analysis, as well as an extension to a SEIR compartmental model to account for the relatively long latent phase of the COVID-19 disease. In all the scenario considered, the divergence between the individual and societal strategies happens both before the peak of the epidemic, due to individuals’ fears, and after, when a significant propagation is still underway.

Topics & Concepts

Nash equilibriumMathematical economicsDivergence (linguistics)PopulationLimit (mathematics)Epidemic modelExtension (predicate logic)Meaning (existential)MathematicsControl (management)Sensitivity (control systems)Transmission (telecommunications)EconomicsSocial contactMathematical optimizationOptimal controlOrder (exchange)Social costConstant (computer programming)Field (mathematics)Transmission rateApplied mathematicsStatistical physicsEconometricsCoronavirus disease 2019 (COVID-19)Term (time)Mean field theoryPhase (matter)Range (aeronautics)Computer scienceVariable (mathematics)Best responseCOVID-19 epidemiological studiesMathematical and Theoretical Epidemiology and Ecology ModelsComplex Network Analysis Techniques
Contact rate epidemic control of COVID-19: an equilibrium view | Litcius