Systems theory and analysis of the implementation of non pharmaceutical policies for the mitigation of the covid-19 pandemic

Leventides, J.; Poulios, C.; Tsiatsios, G. A.; Livada, M.; Tsipras, S.; Lefcaditis, K.; Sargenti, P.; Sargenti, A.

We utilize systems theory in the study of the implementation of non pharmaceutical strategies for the mitigation of the COVID-19 pandemic. We present two models. The first one is a model of predictive control with receding horizon and discontinuous actions of unknown costs for the implementation of adaptive triggering policies during the disease. This model is based on a periodic assessment of the peak of the pandemic (and, thus, of the health care demand) utilizing the latest data about the transmission and recovery rate of the disease. Consequently, the model seems to be suitable for discontinuous, non-mechanical (i.e. human) actions with unknown effectiveness, like those applied in the case of COVID-19. Secondly, we consider a feedback control problem in order to contain the pandemic at the capacity of the NHS (National Health System). As input parameter we consider the value p that reflects the intensity-effectiveness of the measures applied and as output the predicted maximum of infected people to be treated by NHS. The feedback control regulates p so that the number of infected people is manageable. Based on this approach, we address the following questions: (a) the limits of improvement of this approach;(b) the effectiveness of this approach;(c) the time horizon and timing of the application. © American Institute of Mathematical Sciences