Cyclic exit strategies to suppress COVID-19 and allow economic activity

Abstract

Many countries have applied lockdown that helped suppress COVID-19, but with devastating economic consequences. Here we propose exit strategies from lockdown that provide sustainable, albeit reduced, economic activity. We use mathematical models to show that a cyclic schedule of 4-day work and 10-day lockdown, or similar variants, can, in certain conditions, suppress the epidemic while providing part-time employment. The cycle reduces the reproduction number R by a combination of reduced exposure time and an anti-phasing effect in which those infected during work days reach peak infectiousness during lockdown days. The number of work days can be adapted in response to observations. Throughout, full epidemiological measures need to continue including hygiene, physical distancing, compartmentalization and extensive testing and contact tracing. We do not call for immediate adoption of this policy, but rather to consider it as a conceptual framework, which, when combined with other interventions to control the epidemic, can offer the beginnings of predictability to many economic sectors.Current non-pharmaceutical interventions (NPI) to suppress COVID-19 use testing, contact tracing, physical distancing, mask use, identification of regional outbreaks, compartmentalization down to the neighborhood and company level, and population-level quarantine at home known as lockdown ( 1 -4 ) . The aim is to flatten the infection curve and prevent overload of the medical system until a vaccine becomes available.Lockdown is currently in place in many countries. It has a large economic and social cost, including unemployment on a massive scale. Once a lockdown has reduced the number of critical cases to a desired goal, a decision must be reached on how to exit it responsibly. The main concern is the risk of resurgence of the epidemic. One strategy proposes reinstating lockdown when a threshold number of critical cases is exceeded in a resurgence, and stopping lockdown again once cases drop below a low threshold ( 2 , 5 ) ( Fig 1A,S1). While such an "adaptive triggering" strategy can prevent healthcare services from becoming overloaded, it leads to economic uncertainty and continues to accumulate cases with each resurgence.

Estimating and Simulating a SIRD Model of COVID-19 for Many Countries, States, and Cities

“…Bodenstein, Corsetti and Guerrieri (2020) combine a compartmental model with a multisector dynamic general equilibrium model to capture key characteristics of the U.S. Input-Output Tables. Garriga, Manuelli and Sanghi (2020), Hornstein (2020), and Karin, Bar-On, Milo, Katzir, Mayo, Korem, Dudovich, Yashiv, Zehavi, Davidovich et al (2020) study a variety of containment policies. Toda (2020), besides also estimating a SIRD model as we do, explores the optimal mitigation policy that controls the timing and intensity of social distancing.…”

Universal Features of Epidemic Models Under Social Distancing Guidelines

“…We find that the "V" shaped pattern is consistent among all of these models, and we believe it is a universal feature in epidemic models. Lastly, we investigate the relation between "mild" social distancing and periodic relaxations that has been recently proposed by [69,64]; our goal is to understand their limitations. We also show that a well-timed one-shot social distancing pulse can significantly reduce the infected peak, when applied in conjunction with periodic relaxation or mild social distancing strategies.…”

Assessing the immediate effect of COVID-19 lockdown on air quality: A case study of Delhi, India

“…However, the extent of lockdown varies across different countries and cities around the globe depending on the level of cases. Undoubtedly, the lockdown has put a temporary rest to a signi cant number of social and economic activities in the country and its people (Alvarez et al 2020;Inoue and Todo 2020;Karin et al 2020). Overall, the signi cance and impacts of lockdown are yet not well understood and likely to have a signi cant role in the restoration of air quality (Mahato et al 2020).…”