publications

2022

1. Effects of infection fatality ratio and social contact matrices on vaccine prioritization strategies

   Arthur Schulenburg, Wesley Cota, Guilherme S. Costa, and Silvio C. Ferreira

   Chaos: An Interdisciplinary Journal of Nonlinear Science, Sep 2022

   Abs

   Effective strategies of vaccine prioritization are essential to mitigate the impacts of severe infectious diseases. We investigate the role of infection fatality ratio (IFR) and social contact matrices on vaccination prioritization using a compartmental epidemic model fueled by real-world data of different diseases and countries. Our study confirms that massive and early vaccination is extremely effective to reduce the disease fatality if the contagion is mitigated, but the effectiveness is increasingly reduced as vaccination beginning delays in an uncontrolled epidemiological scenario. The optimal and least effective prioritization strategies depend non-linearly on epidemiological variables. Regions of the epidemiological parameter space, in which prioritizing the most vulnerable population is more effective than the most contagious individuals, depend strongly on the IFR age profile being, for example, substantially broader for COVID-19 in comparison with seasonal influenza. Demographics and social contact matrices deform the phase diagrams but do not alter their qualitative shapes.

2. Heterogeneous mean-field theory for two-species symbiotic processes on networks

   Guilherme S. Costa, Marcelo M. Oliveira, and Silvio C. Ferreira

   Phys. Rev. E, Aug 2022
3. Data-driven approach in a compartmental epidemic model to assess undocumented infections

   Guilherme S. Costa, Wesley Cota, and Silvio C. Ferreira

   Chaos, Solitons & Fractals, Aug 2022

   Abs

   Nowcasting and forecasting of epidemic spreading rely on incidence series of reported cases to derive the fundamental epidemiological parameters for a given pathogen. Two relevant drawbacks for predictions are the unknown fractions of undocumented cases and levels of nonpharmacological interventions, which span highly heterogeneously across different places and times. We describe a simple data-driven approach using a compartmental model including asymptomatic and pre-symptomatic contagions that allows to estimate both the level of undocumented infections and the value of effective reproductive number Rt from time series of reported cases, deaths, and epidemiological parameters. The method was applied to epidemic series for COVID-19 across different municipalities in Brazil allowing to estimate the heterogeneity level of under-reporting across different places. The reproductive number derived within the current framework is little sensitive to both diagnosis and infection rates during the asymptomatic states. The methods described here can be extended to more general cases if data is available and adapted to other epidemiological approaches and surveillance data.

2021

1. Simple quasistationary method for simulations of epidemic processes with localized states

   Guilherme S. Costa, and Silvio C. Ferreira

   Computer Physics Communications, Aug 2021

   Abs

   Epidemic processes on random graphs or networks are marked by localization of activity that can trap the dynamics into a metastable state, confined to a subextensive part of the network, before visiting an absorbing configuration. Quasistationary (QS) method is a technique to deal with absorbing states for finite sizes and has played a central role in the investigation of epidemic processes on heterogeneous networks where localization is a hallmark. The standard QS method possesses high computer and algorithmic complexity for large systems besides parameters whose choice are not systematic. However, simpler approaches, such as a reflecting boundary condition (RBC), are not able to capture the localization effects as the standard QS method does. In the present work, we propose a QS method that consists of reactivating nodes proportionally to the time they were active along the preceding simulation. The method is compared with the standard QS and RBC methods for the susceptible-infected-susceptible model on complex networks, which is a prototype of a dynamic process with strong localization effects. We verify that the method performs as well the as standard QS in all investigated simulations, providing the same scaling exponents, epidemic thresholds, and localized phases, thus overcoming the limitations of other simpler approaches. We also report that the present method has significant lower computer and algorithmic complexity than the standard QS method. So, this method arises as a simpler and efficient tool to analyze localization on heterogeneous structures through QS simulations.

2020

1. Outbreak diversity in epidemic waves propagating through distinct geographical scales

   Guilherme S. Costa, Wesley Cota, and Silvio C. Ferreira

   Phys. Rev. Res., Dec 2020
2. Nonmassive immunization to contain spreading on complex networks

   Guilherme S. Costa, and Silvio C. Ferreira

   Phys. Rev. E, Feb 2020

2016

1. Sampling methods for the quasistationary regime of epidemic processes on regular and complex networks

   Renan S. Sander, Guilherme S. Costa, and Silvio C. Ferreira

   Phys. Rev. E, Feb 2016