Infections produced by non-symptomatic (pre-symptomatic and asymptomatic) individuals have been identified as major drivers of COVID-19 transmission. Non-symptomatic individuals, unaware of the infection risk they pose to others, may perceive themselves—and be perceived by others—as not presenting a risk of infection. Yet, many epidemiological models currently in use do not include a behavioral component, and do not address the potential consequences of risk misperception. To study the impact of behavioral adaptations to the perceived infection risk, we use a mathematical model that incorporates the behavioral decisions of individuals, based on a projection of the system’s future state over a finite planning horizon. We found that individuals’ risk misperception in the presence of non-symptomatic individuals may increase or reduce the final epidemic size. Moreover, under behavioral response the impact of non-symptomatic infections is modulated by symptomatic individuals’ behavior. Finally, we found that there is an optimal planning horizon that minimizes the final epidemic size.
【저자키워드】 Infectious diseases, Human behaviour, Applied mathematics, 【초록키워드】 Infection, risk, Epidemic, Asymptomatic, pre-symptomatic, symptomatic, epidemiological, infection risk, risk of infection, COVID-19 transmission, individual, Final, consequence, produced, include, reduce, individuals, presenting, mathematical, modulated, driver, 【제목키워드】 adaptive, Epidemic, human behavior, individual, Final,