Covid-19 curve

contribution of the mathematical models as scientific divulgation language

Abstract

In this work, the COVID-19 curve disclosed by the media is explored through the tools of scientific dissemination. The motivation for this exploration is the recognition of the public's difficulty in interpreting the graph of the new coronavirus pandemic. The target audience for the presentation of the curve is made up of those who know only one potentiation operation, a geometric progression and an exponential function, but who have no notions of differential equations. Before exploring the COVID-19 curve, the text begins by introducing the concept of a mathematical model. The differential equations involved in mathematical models will not be made explicit, but will be written in terms of hypotheses. The calculation of the solutions of non-comprehensive equations, but as consequences of the hypotheses, will be exposed through arguments. Then, the article shows a mathematical model to describe the development of COVID-19, the SIR, acronym for susceptible-infected-recovered. The SIR model requires a dynamic where the susceptible (S) can become infected (I) and the latter, recovered (R). The work shows how the SIR model is a base of the COVID-19 curve, where the number of infected people grow and develop. Although the SIR model does not directly predict deaths, the estimate of the latter amount is made based on the number of infected people per day. The article discusses how the SIR model is close to the observed data, despite all its limitations. The conclusion of the article is that the assumptions and general changes of the SIR model can be explained to an audience that does not master advanced mathematics, but the estimated death values and the duration of the pandemic scheduled for planning measures against the pandemic no qualitative explanations can be found.