ABSTRACT
COVID data are usually presented in a non-structured format and mainly focused on healthy issues (incidence, mortality, etc). At the same time, Governments have designed a set of measures to deal with the Pandemic. In addition, several institutions have studied the economical effects of the situation in each country. In this work, we combine these three data sources and illustrate how Formal Concept Analysis can become a useful tool to discover relationships among these three views of the situation: health, politics and economy. Our aim is to provide an implication-driven approach to discover knowledge behind the data. © 2021 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0)
ABSTRACT
Despite the high incidence of COVID-19 cases worldwide, the volume of subjects affected by the pandemic is not lim-ited to subjects with the infection. Notably, their repercus-sions extend to the general population, in both physical and mental aspects. Social distancing measures, although effective, implicate drastic changes in people’s daily rou-tines upon confinement, a high-stress situation. Additively and in synergy, these factors bear consequences on health by altering circadian rhythms, a phenomenon known as “chronodisruption”. It is associated with a greater risk of various cardiometabolic disorders. Insulin resistance (IR) is a key pathophysiologic component in this scenario. Chro-nodisruption appears to favor the development of changes in its signaling in peripheral tissues. Furthermore, it may be linked with direct pancreatic toxicity. This may be mediated by disorders in the circadian gene expression, and alteration in the functionality of the suprachiasmatic nucleus of the hypothalamus and melatonin. The objective of this review is to describe the possible pathophysiological mechanisms involved in the chronodisruption seen in individuals in confinement and the development of IR.