Optimal COVID-19 epidemic control until vaccine deployment

Ramses Djidjou-Demasse; Yannis Michalakis; Marc Choisy; Micea T. Sofonea; Samuel Alizon

Here, we adopt a more modelling approach based on optimal control theory [15, 22] to determine the best strategy to implement until vaccine deployment. We therefore focus on a finite time interval [0, T ], where T is the number of days required for vaccine discovery, manufacturing and deployment. Our key metric is the fraction c of decrease in R 0 (or, equivalently, in the contact rate) obtained through non-pharmaceutical interventions, which we refer to as control intensity. Importantly, the model considers that implementing the control policy comes with a cost, which corresponds to diverting funding from important sources or to social deleterious effects, and can cause indirect mortality. Optimal control theory allows us to find the optimal control strategy over time, denoted by c(t), that minimises the cumulative sum of these costs over the [0, T ] period of time. We compare this strategy to scenarios without any control or with more homogeneous control (i.e. with c alternating between constant values at a given frequency) that involve the same average effort over time as the optimal strategy. We find that the optimal control strategy outperforms the others in terms of direct and indirect mortality.