A platform to simulate COVID-19 that allows inclusion of mathematical modeling into decision-making management

The COVID-19 pandemic affected the entire world, forcing several institutions to designate a part of their resources to implement control strategies to reduce its incidence. Thus, mathematical modeling becomes an important tool to study the effects of control policies, as it communicates academic information to the public and decision-makers. Following these ideas, the group of mathematical epidemiology of EAFIT University in Colombia developed an online tool that shows the effect of modifying control strategies over different localities in Colombia. We developed this tool based on a novel discrete-time model with variations on parameters related to quarantine, identification, social distancing, migrations, vaccination, among others; besides visual tools that allow communication to the public. At the moment, we included in the platform over forty Colombian localities, in which we individualize the mathematical model estimating the corresponding parameters with real data provided from the Colombian national health institution. Every time we update the model with new data, the user can simulate and project different control scenarios over the affected population. In this work, we will present the structure of a platform that allows the non-expert users to simulate different control strategies; also, we could use it for monitoring other infectious diseases.