Proposal for a Methodology Based on Electricity Consumption to Analyze Social Isolation During a COVID-19 Pandemic: Case Study
Keywords:COVID-19, social insolation, energy demand, Artificial Neural Network
The first occurrences of Covid-19, the disease caused by the coronavirus SRA-CoV-2, emerged in the Wuhan region (China), the disease expanded rapidly around the world. Based on this, World Health Organization characterized the situation of COVID-19 as a pandemic. The solution adopted by the health authorities was to apply social isolation. Based on these measures, one of the challenges is the correct dimensioning and quantification of observance to these measures. This article presents a proposal for a new methodology for evaluating and monitoring the social isolation index of the population based on electricity consumption. This model that can be used to qualitatively determine social isolation, determined if the supervised city has a high, medium or low degree of social isolation. A trained Artificial Neural Network was used to determine the degree of isolation practiced by the citizens of a town. The results validate and demonstrate the efficiency of the proposed methodology.