Category: Research Papers

Abstract/Vision:

To curb the spread of COVID-19, many governments around the world have implemented tiered lockdowns with varying degrees of stringency. Lockdown levels are typically increased when the disease spreads and reduced when the disease abates. A predictive control approach is used to develop optimized lockdown strategies for curbing the spread of COVID-19. These strategies are then applied to South African data. The South African case is of immediate interest as the number of confirmed infectious cases does not appear to have peaked yet (at the time of writing), while at the same time the South African government is busy reducing the degree of lockdown. An epidemiological model for the spread of COVID-19 in South Africa was previously developed, and is used in conjunction with a hybrid model predictive controller to optimize lockdown management under different policy scenarios. Scenarios considered include how flatten the curve to a level that the healthcare system can cope with, how to balance lives and livelihoods, and what impact the compliance of the population to the lockdown measures has on the spread of COVID-19.

Contact: Ian Craig

Other participants:

External website: https://arxiv.org/abs/2006.16379

Tags: control

Keywords: COVID-19; Epidemiology; Genetic algorithm; Hybrid systems; Model predictive control; SARS-CoV-2; SEIQRDP model.

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