Contribution of mathematical models and big data for company decision-making; the case of epidemiological events such as SARS-CoV-2 in the health area in Chile

Abstract : The pandemic caused by the COVID-19 virus has given rise to numerous analyses and studies due to the implications and serious consequences it has had on all areas of human development worldwide. The data unquestionably reflect the degree of impact it has had, not only on the mortality rate, but also on the economic indices of nations. In analysing all these indicators, the question arises as to whether some key elements, such as the number of incidences, the variables of the effective reproductive factor of the disease could better reflect the predictability of the cases and, in turn, evaluate the mitigating measures to pla­cate the incidence of new cases. This analysis is especially significant considering that the pandemic is not over, and that more and better resolutions are still needed to address this ongoing crisis. In this context, the present study aims to analyse, from the theoretical math­ematical models, what has been the contribution of this area of science to find and predict possible solutions to quell the effects of this global pandemic. For this purpose, statistical analyses based on three models will be used : non-linear phenomenological models, data modeling and the generalised logistic model, which are expected to contribute to a better evaluation and understanding of the measures taken to face this health crisis and, in the future, the importance of understanding the use of data and the technological tools avail­able to mankind today in the face of any new virus.

Keywords : SARS-CoV-2, mathematical models, applied statistics.

JEL classification : C02, I12.

DOI: https://doi.org/10.18559/RIELF.2023.1.1