COVID-19: Fast multi-shot epidemic interventions for post lockdown Covid-19 mitigation: Open-loop mitigation strategies

Lead Research Organisation: Imperial College London
Department Name: Design Engineering

Abstract

The objective of this 4-month SPRINT is to design and validate new exit-strategies from the current lockdown policy that actively suppress COVID-19, while allowing significant economic activity. Currently proposed exit-strategies suggest that intermittent lockdowns, in addition to contact tracing, masking, and other measures, may be necessary until an effective vaccine is found. Most of the these propose using data-driven feedback signals, such as hospital admissions, to initiate lockdowns, with a key design consideration being the capacity of the healthcare system. The difficulty with this approach is timing. Intervene too early, and one simply shifts the peak of ill people to a later date, whereas too late an intervention will not limit the peak of infections. The issue of timing is exacerbated by the virus having up to a 14-day incubation period and an initial exponential growth rate. Thus, the problem of observing the true state of the epidemic, in the face of exponential growth, makes the effectiveness of any data-driven feedback policy extremely sensitive to the timing of intervention. From a classical perspective, controlling locally unstable systems, as this is, with time-varying time-delays, is known to be a frontier problem in control engineering. Our suggestion is to circumvent this difficulty by developing periodic open-loop lockdown strategies over short timescales. Such policies, will help suppressing the virus and allow predictable periodic periods of lockdown, thereby facilitating economic activity. The policies will be validated on advanced, realistic epidemiological mathematical models and data, and will be developed for national and international compartmental scenarios.

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