An epidemiological model with voluntary quarantine strategies governed by evolutionary game dynamics

Abstract

During pandemic events, strategies such as quarantine and social distancing can be fundamental to curb viral spreading. Such actions can reduce the number of simultaneous infection cases and mitigate the disease spreading, which is relevant to the risk of a healthcare system collapse. Although these strategies can be suggested, or even imposed, their actual implementation may depend on the population perception of the risks associated with a potential infection. The current COVID-19 crisis, for instance, is showing that some individuals are much more prone than others to remain isolated, avoiding unnecessary contacts, and respecting other restrictions. With this motivation, we propose an epidemiological SIR model that uses evolutionary game theory to take into account dynamic individual quarantine strategies, intending to combine in a single process social strategies, individual risk perception, and viral spreading. The disease spreads in a population whose agents can choose between self-isolation and a lifestyle careless of any epidemic risk. The strategy adoption is individual and, most importantly, depends on the perceived disease risk compared to the quarantine cost. The game payoff governs the strategy adoption, while the epidemic process governs the agent's health state. At the same time, the infection rate depends on the agent's strategy while the perceived disease risk depends on the fraction of infected agents. Our results show recurrent infection waves phenomena, which are usually seen in previous historic epidemic scenarios with voluntary quarantine. In particular, such waves re-occur as the population reduces disease awareness. Notably, the risk perception parameter is found to be fundamental for controlling the magnitude of the infection peak, while the final infection size is mainly dictated by the infection rates. Low awareness leads to a single and strong infection peak, while a greater disease risk perception leads to shorter, although more frequent, peaks. The proposed model spontaneously captures relevant aspects of a pandemic event, highlighting the fundamental role of social strategies.

Dynamic Games of Social Distancing during an Epidemic: Analysis of Asymmetric Solutions

“…Recently, with the emergence of the COVID-19 pandemic, there is a renewed interest in modeling individual behaviors. Related tools include dynamic game analysis of social distancing [28,29,30,31,32,33], evolutionary game theory [34,35,36,37] and network game models [38,39]. This paper presents a game-theoretic model to describe the social distancing choices of individuals during an epidemic.…”

Nash Social Distancing Games with Equity Constraints: How Inequality Aversion Affects the Spread of Epidemics

“…Recently, with the outbreak of the COVID-19 pandemic, there is a renewed interest on the modeling of individual behaviors. For example, [25] provides a dynamic game analysis of social distancing, [26], [27], [28] use evolutionary game theory to study social distancing behaviors and [29] analyze the effects of the structure of the network of social interactions, the quality of information, and the capacity of the health-care system on the spread of epidemics.…”