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

, and . In the figures σE γI , dI /dt γI γI 2 2 − 2 1 2 = 2 1 − 2 2 I = I 1 + I 2 / γ R = β we used a worst-case assumption of no herd immunity, namely . Herd immunity S ≈ 1 further reduces case numbers. Case numbers are in arbitrary units, and can describe large or small outbreaks. The deterministic simulation describes a fully-mixed population. Population structure typically reduces overall outbreak peak size ( 23 ) compared to a fully mixed situation with the same mean transmission rate, but includes the possibility of high attack rates in certain sub-populations. For example, a stochastic simulation on a network shows a larger range of conditions for a cyclic strategy to work than in a deterministic model (compare Fig 4 and Fig S5) , Staggered cyclic strategy, SEIR-Erlang model: We model two groups, A and B, with a susceptible, exposed and infectious compartment for each group. The SEIR-Erlang model for group A is: