Understanding R-based planning decisions and control for COVID-19 recovery

Abstract

A strategy is a high level plan to achieve one or more goals under conditions of uncertainty, it is about reaching desirable ends with available means. In this paper practical management tools to tackle the deconfinement strategy design problem are presented. But strategy is not only about design, it has much to do with implementation too. A proper control system to follow the course of action, especially in a scenario with unprecedent uncertainty, is developed. This is considered a must to launch strategy implementation. In the paper, it is remarked the importance of R, first as a variable to monitor and control the pandemic, to ensure its decline; second as a target to score risks associated to start certain activities over, after confinement. Reducing the potential increase in the value of R, when any type of activity is re-opening, guides the strategy. In terms of control, the paper benefits of up-to-date developments within the field of predictive maintenance (PdM). The emergence of predictive analytics and the introduction of prognosis interpretation rules can be very valuable now, when you need to take decisions based on data and predictions. A novel and innovative way to structure the data model required for such a control system is presented in the paper. Whatever actions are taken as appropriate will impact the economy in the shortmidterm, and understanding the extent of that impact by economic sector and time scale is rather interesting. This paper also provides an answer to this concern. With this paper, SIM research group ends a trilogy related to Covid 19 pandemic management analysis. Our aim has been always to put our best skills and our experience to serve our communities when facing this unprecedent situation.