Prof. Silvio Ferreira
Name: Silvio da Costa Ferreira Junior
Affiliation: Departamento de Física, Universidade Federal de Viçosa, Viçosa-MG, 36570-000, Brazil
Phone: +55 31 38992820 FAX: +55 31 38992483
Email: silviojr@ufv.br
Preprints
R20K50.mp4R60K70.mp4covid-19 spreading in brazil
G. S. Costa , W. Cota , S. C. Ferreira, Metapopulation modeling of COVID-19 advancing into the countryside: an analysis of mitigation strategies for Brazil
Supplementary material Video 1 Video 2 Video 3
Since the first case of COVID-19 was confirmed in Brazil at 19 February 2020, this epidemics has spread out throughout all states and at least 2142 of 5570 municipalities up to 30 April 2020. We investigate a stochastic epidemic model using a metapopulation approach.Properties of the epidemics curves such as time and value of epidemic peak and outbreak duration have very broad distributions across different geographical locations. The epidemic waves start from several foci concentrated in highly populated regions and propagate towards countryside. Responses of different regions to a same mitigation protocol can vary enormously such that the policies of combat to COVID-19, such as quarantine or lockdown, must be engineered according to the region specificity but integrated with the overall situation.
Recent papers
G. S. Costa, S. C. Ferreira, Nonmassive immunization to contain spreading on complex networks, Phys. Rev. E 101, 022311, (2020).
In this work we study the effects of immunization for the spread of epidemics in complex networks. The aim was to show that it is possible to prevent the spread of an epidemic of the SIS model type with immunization fractions far below the percolation threshold of these same networks. Among other results, we show that the epidemic threshold of the SIS model, which is null in scale-free networks, becomes finite using simple immunization strategies. Figure shows the comparison immunization and percolation threshold for several real networks.
W. Cota, S. C. Ferreira, R. Pastor-Satorras, and M. Starnini, Quantifying echo chamber effects in information spreading over political communication networks, EPJ Data Science 8, 35 (2019).
We quantify the effects of echo chambers on the diffusion of information over online communication networks, characterizing the debate about the impeachment process of former Brazilian President Dilma Rousseff. We estimate the capability of users to spread the content they produce, showing that individuals broadcasting pro-impeachment sentiments can break their echo chamber, by reaching a larger and more diverse audience than other users. Figure shows the aggregated network of users expressing majorly pro-impeachment (blue), neutral (white), and anti-impeachment (red) sentiments in the content produced by them.