The virus and socioeconomic inequality: An agent-based model to simulate and assess the impact of interventions to reduce the spread of COVID-19 in Rio de Janeiro, Brazil

The emergence of COVID-19 in China, in December of 2019 led to a local epidemic that rapidly spread to multiple countries in the world, including Brazil. Nowadays, there is an accelerated search to understand the dynamics of the spread of the disease and evaluate the effectiveness of intervention measures. Given these special socioeconomic conditions surrounding Brazil, using the predictive models developed for other countries can make a very incomplete picture of the epidemic, since these differences could result in different patterns in low income settings. The aim of this work is to simulate interventions and understand the impact to reduce the spread of COVID-19 considering the socioeconomic conditions of Brazil. With this purpose we use an agent- based model (ABM), a subarea of the Artificial Intelligence, as it allows us to treat each individual in a personalized manner, as well as the environment of which they are part. The simulations have heterogeneous populations, considering different age groups, socioeconomic differences and number of members per family, contacts and movements intra and inter the sub-populations (favelas and non-favelas), numbers of Intensive Care Unit (ICU) and study different scenarios to show how the interventions can influence the spread of the virus in the population of simulated environments.