After the lockdown: simulating mobility, public health and economic recovery scenarios

Abstract

The spread of SARS-COV-2 has affected many economic and social systems. This paper aims at estimating the impact on regional productive systems in Italy of the interplay between the epidemic and the mobility restriction measures put in place to contain the contagion. We focus then on the economic consequences of alternative lockdown lifting schemes. We leverage a massive dataset of human mobility which describes daily movements of over four million individuals in Italy and we model the epidemic spreading through a metapopulation SIR model, which provides the fraction of infected individuals in each Italian district. To quantify economic backslashes this information is combined with socio-economic data. We then carry out a scenario analysis to model the transition to a post-lockdown phase and analyze the economic outcomes derived from the interplay between (a) the timing and intensity of the release of mobility restrictions and (b) the corresponding scenarios on the severity of virus transmission rates. Using a simple model for the spreading disease and parsimonious assumptions on the relationship between the infection and the associated economic backlashes, we show how different policy schemes tend to induce heterogeneous distributions of losses at the regional level depending on mobility restrictions. Our work shed lights on how recovery policies need to balance the interplay between mobility flows of disposable workers and the diffusion of contagion.

Diffusion modeling of COVID-19 under lockdown

“…Analogous results were obtained by Spelta et al , using a simple model for the spreading disease represented by a Susceptible-Infected-Recovered (SIR) model. 22 The positive lockdown impact on virus diffusion was confirmed by Lillery et al in an Italian study, also. 23 …”

Machine Learning on the COVID-19 Pandemic, Human Mobility and Air Quality: A Review

“…Controlling the outbreak of COVID-19 has become a major concern of governments and public health professionals. Different measures such as stringent travel restrictions and self-quarantine measures (e.g., lockdown, emergency stay-athome orders, closing of public transportation systems, travel ban, restrictions on public gathering, closure of workplaces and educational institutions) and personal protective measures (e.g., face masks, gloves, hand sanitizer stations) have been implemented [2], [10]- [12], [18]- [20] throughout the world to control the COVID-19 outbreak. These various measures undertaken by governments have influenced both essential (e.g., work) and non-essential (e.g., recreation) trips.…”

Effects of Early Mask Mandates and Other Policy Interventions on COVID-19 Infections

“…[1][2][3][4][5][6][7][8][9] Yet, despite their demonstrated effectiveness, many NPIs hurt the economy and other aspects of social and personal wellbeing. 7 Still, little is known about how NPIs compare in their relative e cacies. 6,8,10 Suppose mandatory mask-wearing is more effective than other NPIs.…”