Open AccessA topological approach to the study of COVID-19 pandemic: qualitative models for understanding and helping taking decisions
Author(s) -
Jesús Rodríguez-Millán
Publication year - 2021
Publication title -
revista ingenio
Language(s) - English
Resource type - Journals
eISSN - 2389-864X
pISSN - 2011-642X
DOI - 10.22463/2011642x.2388
Subject(s) - metaphor , computer science , sequence (biology) , covid-19 , pandemic , order (exchange) , motion (physics) , dynamical systems theory , control (management) , topology (electrical circuits) , artificial intelligence , theoretical computer science , human–computer interaction , mathematics , physics , economics , biology , medicine , disease , genetics , finance , pathology , quantum mechanics , combinatorics , infectious disease (medical specialty) , philosophy , linguistics
Mathematical models are either strategic, simplified, to study global qualitative properties, or tactic, detailed, appropriate for fine quantitative adjustment to reality. When complex systems interact with their medium or undergo parameter perturbations, they can suffer changes of order making qualitative and quantitative studies difficult. Epidemiological processes allow distinguishing between topological and dynamical alterations, and establishing precedence among them. In this essay we approach COVID-19 this way, to separate topological transformations inducing changes of order in the system, from dynamic transformations themselves. We then develop a visual metaphor, a sequence of images to support a stop-motion, allowing distinguishing the stages, identifying and classifying sceneries, and suggest actions to improve the understanding and control, of the pandemic.