Understanding COVID-19 spreading through simulation modeling and scenarios comparison: preliminary results.

Since late 2019 the world is facing the rapid spreading of a novel viral disease (SARS-CoV-2) provoked by the coronavirus 2 infection (COVID-19), declared pandemic last 12 March 2020. As of 27 March 2020, there were more than 500,000 confirmed cases and 23,335 deaths worldwide. In those places with a rapid growth in numbers of sick people in need of hospitalization and intensive care, this demand has over-saturate the medical facilities and, in turn, rise the mortality rate. In the absence of a vaccine, classical epidemiological measures such as testing, quarantine and physical distancing are ways to reduce the growing speed of new infections. Thus, these measures should be a priority for all governments in order to minimize the morbidity and mortality associated to this disease. System dynamics is widely used in many fields of the biological sciences to study and explain changing systems. The system dynamics approach can help us understand the rapid spread of an infectious disease such as COVID-19 and also generate scenarios to test the effect of different control measures. The aim of this study is to provide an open model (using STELLA(R) from Iseesystems) that can be customized to any area/region and by any user, allowing them to evaluate the different behavior of the COVID-19 dynamics under different scenarios. Thus, our intention is not to generate a model to accurately predict the evolution of the disease nor to supplant others more robust -official and non-official-from governments and renowned institutions. We believe that scenarios comparison can be an effective tool to convince the society of the need of a colossal and unprecedented effort to reduce new infections and ultimately, fatalities.