Elementary formulae for social distancing scenarios: Application to COVID-19 mitigation via feedback control
Abstract
Social distancing has been enacted in order to mitigate the spread of COVID-19. Like many authors, we adopt the classic epidemic SIR model, where the infection rate is the control variable. Its differential flatness property yields elementary closed-form formulae for open-loop social distancing scenarios, where, for instance, the increase of the number of uninfected people may be taken into account. Those formulae might therefore be useful to decision makers. A feedback loop stemming from model-free control leads to a remarkable robustness with respect to severe uncertainties of various kinds. Although an identification procedure is presented, a good knowledge of the recovery rate is not necessary for our control strategy. Several convincing computer experiments are displayed.
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