By Alberto Aleta, David Martín-Corral, Ana Pastore y Piontti, Marco Ajelli, Maria Litvinova, Matteo Chinazzi, Natalie E. Dean, M. Elizabeth Halloran, Ira M. Longini, Jr., Stefano Merler, Alex Pentland, Alessandro Vespignani, Esteban Moro & Yamir Moreno
Summary of the results
As the number of confirmed COVID-19 cases increased and the expansion of the disease entered into a global exponential growth phase, a large number of affected countries were forced to adopt non-pharmaceutical interventions at an unprecedented scale. The aggressive social distancing interventions implemented by many countries in response to the COVID-19 pandemic appear to have achieved the interruption of transmission and the abatement of the epidemic, although at the price of huge societal disruption and economic costs.
In such a context, the identification of “exit strategies” that allow restarting economic and social activities while still protecting the healthcare systems and minimizing the burden of the epidemic is of primary importance.
In our paper we adopt a multi-disciplinary approach to study to model the impact of testing, contact tracing, and quarantine into the transmission of COVID-19 in the Boston metropolitan area. By using highly detailed (anonymized, privacy-enhanced) mobility data from mobile devices to describe the transmission of SARS-CoV-2 we study the effect of social distancing and non-pharmaceutical interventions to provide exit scenarios.
Gradually removing the restrictions imposed by social distancing could lead to a second wave with the potential to overwhelm the healthcare system if not combined with strategies aimed at the prompt testing of symptomatic infections and the tracing and quarantine of as many of their contacts as possible.
Specifically, if the “stay at home” order is lifted after 8 weeks by reopening all work and community places, except for mass-gathering locations such as restaurants, theaters, and similar locations, resurgence of the epidemic and a second COVID-19 wave are inevitable. We also estimate that a second wave of the epidemic still has the potential to infect a large fraction of the population and to overwhelm the health care systems.
However, if the “stay at home” order is lifted as in the previous scenario, but we identify 50% of the symptomatic infections, and trace of 40% of their contacts and households (which corresponds to about a 9% of the populations quarantined), the ensuing reduction in transmission allows the reopening of economic activities while attaining a manageable impact on the health care system.
While this is certainly a relevant fraction of the population, it is a much better option if compared with massive social distancing policies affecting the entire population that last for months.
Given that it uses real mobility data, our modeling framework enables the realistic simulation of scenarios with social distancing interventions and mobility reduction. Because of that, future policies, interventions or mobility restrictions can be easily included by using up-to-date data or new behavioral features. Our modeling framework can be extended to other cities and metropolitan areas wherever similar data is available.
Download the paper here.