Adaptive cyclic exit strategies from lockdown to suppress COVID-19 and allow economic activity

Omer Karin; Yinon M. Bar-On; Tomer Milo; Itay Katzir; Avi Mayo; Yael Korem; Boaz Dudovich; Amos J. Zehavi; Nadav Davidovich; Ron Milo; Uri Alon

Simulations using a variety of epidemiological models, including SEIR models and stochastic network-based simulations, show that a cyclic strategy can suppress the epidemic provided that the lockdown is effective enough (Fig. 4 , Table 1 ). A 4-10 cycle seems to work well for a range of parameters and is robust to uncertainties in the model (Fig. S2, S3 ). The transmission parameters during work days and lockdown days can be described by the effective replication numbers that describe extended periods of work and lockdown conditions, and , respectively. If lockdown is as strong as strong as in R W R L Wuhan, with estimated ( 10 ) , a 4-10 cycle suppresses the epidemic even if .3 R L ≈ 0 workday is as large as in the early days of the epidemic in Europe, with R W ( 11 ) . A weaker lockdown, with , can support a cyclic R W ≈ 3 − 4 .6 .8 R L ≈ 0 − 0 strategy with 2-4 work days when strict measures are enforced during workdays providing (Table 1) . Simulating on a social network provides an even .5 R W ≈ 1 − 2 larger range of conditions of a cyclic strategy to control the epidemic ( Fig S5) . Ideally, measures will eventually bring down R during workdays below 1, as in South Korea's control of the epidemic in early 2020, making lockdown unnecessary.