COVID-19 propagation in multilayer networks
SIR, Complex Networks, CDR, Genetic Algorithm, COVID-19
Epidemic modeling is a very useful tool to help institutions make decisions. Understanding the dynamics of the spread of the virus in the population makes it possible to develop effective public policies to combat the epidemic. This work aims to model multilayer networks, aiming to represent the economic, social and demographic aspects of a given population. The network layers will be modeled using census data and telephone call records (CDRs). Subsequently, it will be used to simulate the spread of COVID-19, applying the SIR epidemiological model. To use this model, the parameters $\beta$ and $\gamma$ will be estimated by a genetic algorithm, using real infection and recovery data in this adjustment process, generating simulations with patterns similar to reality.