Modelling information–dependent social behaviors in response to lockdowns: the case of COVID–19 epidemic in Italy

Abstract The COVID–19 pandemic started in January 2020 has not only threatened world public health, but severely impacted almost every facet of lives including behavioral and psychological aspects. In this paper we focus on the ‘human element’ and propose a mathematical model to investigate the effects on the COVID–19 epidemic of social behavioral changes in response to lockdowns. We consider a SEIR-like epidemic model where that contact and quarantine rates are assumed to depend on the available information and rumors about the disease status in the community. The model is applied to the case of COVID–19 epidemic in Italy. We consider the period that stretches between Bebruary 24, 2020 when the first bulletin by the Italian Civil Brotection was reported and May 18, 2020 when the lockdown restrictions have been mostly removed. The role played by the information–related parameters is determined by evaluating how they affect suitable outbreak–severity indicators. We estimated that citizens compliance with mitigation measures played a decisive role in curbing the epidemic curve by preventing a duplication of deaths and about 46% more contagions. Subject class: 92D30, 34C60