Scaling effect in COVID-19 spreading: The role of heterogeneity in a hybrid ODE-network model with restrictions on the inter-cities flow.

Autor: Miranda JGV; Instituto de Física, Universidade Federal da Bahia (UFBA), Rua Barão de Jeremoabo, 147, Campus Universitário de Ondina, CEP: 40170-115, Salvador, Bahia, Brazil., Silva MS; Instituto de Física, Universidade Federal da Bahia (UFBA), Rua Barão de Jeremoabo, 147, Campus Universitário de Ondina, CEP: 40170-115, Salvador, Bahia, Brazil., Bertolino JG; Instituto de Física, Universidade Federal da Bahia (UFBA), Rua Barão de Jeremoabo, 147, Campus Universitário de Ondina, CEP: 40170-115, Salvador, Bahia, Brazil., Vasconcelos RN; Universidade Estadual de Feira de Santana (UEFS), Avenida Transnordestina, s/n, CEP: 44036-900, Novo Horizonte, Feira de Santana, Bahia, Brazil., Cambui ECB; Instituto de Física, Universidade Federal da Bahia (UFBA), Rua Barão de Jeremoabo, 147, Campus Universitário de Ondina, CEP: 40170-115, Salvador, Bahia, Brazil., Araújo MLV; Instituto Federal de Ciência e Tecnologia da Bahia (IFBA), Tv. Santo Amaro, 44, Santo Amaro - BA, 44200-000, Brazil., Saba H; Universidade do Estado da Bahia (UNEB), Rua Silveira Martins, 2555 - Cabula, Salvador - BA, 41150-000, Brazil., Costa DP; Programa de Pós-graduação em Energia e Ambiente, UFBA/Pavilhão de Aulas Raul Seixas Universidade Federal da Bahia, Av. Adhemar de Barros, s/n, Brazil., Duverger SG; Instituto de Física, Universidade Federal da Bahia (UFBA), Rua Barão de Jeremoabo, 147, Campus Universitário de Ondina, CEP: 40170-115, Salvador, Bahia, Brazil., Oliveira MT; Universidade Estadual de Feira de Santana (UEFS), Avenida Transnordestina, s/n, CEP: 44036-900, Novo Horizonte, Feira de Santana, Bahia, Brazil., Neto HSA; Universidade Estadual de Feira de Santana (UEFS), Avenida Transnordestina, s/n, CEP: 44036-900, Novo Horizonte, Feira de Santana, Bahia, Brazil., Franca-Rocha WJS; Universidade Estadual de Feira de Santana (UEFS), Avenida Transnordestina, s/n, CEP: 44036-900, Novo Horizonte, Feira de Santana, Bahia, Brazil., Jorge DCP; Instituto de Física, Universidade Federal da Bahia (UFBA), Rua Barão de Jeremoabo, 147, Campus Universitário de Ondina, CEP: 40170-115, Salvador, Bahia, Brazil., de Oliveira JF; Center of Data and Knowledge Integration for Health (CIDACS), Instituto Gonçalo Moniz, Fundação Oswaldo Cruz, Parque Tecnológico da Edf. Tecnocentro, sala 315, Rua Mundo, no 121, BA, Brazil.; Centro de Matemática da Universidade do Porto, Portugal., Andrade RFS; Instituto de Física, Universidade Federal da Bahia (UFBA), Rua Barão de Jeremoabo, 147, Campus Universitário de Ondina, CEP: 40170-115, Salvador, Bahia, Brazil.; Center of Data and Knowledge Integration for Health (CIDACS), Instituto Gonçalo Moniz, Fundação Oswaldo Cruz, Parque Tecnológico da Edf. Tecnocentro, sala 315, Rua Mundo, no 121, BA, Brazil., do Rosário RS; Instituto de Física, Universidade Federal da Bahia (UFBA), Rua Barão de Jeremoabo, 147, Campus Universitário de Ondina, CEP: 40170-115, Salvador, Bahia, Brazil.
Jazyk: angličtina
Zdroj: Physica D. Nonlinear phenomena [Physica D] 2021 Jan; Vol. 415, pp. 132792. Date of Electronic Publication: 2020 Nov 04.
DOI: 10.1016/j.physd.2020.132792
Abstrakt: The new Covid-19 pandemic has left traces of suffering and devastation to individuals of almost all countries worldwide and severe impact on the global economy. Understanding the clinical characteristics, interactions with the environment, and the variables that favor or hinder its dissemination help the public authorities in the fight and prevention, leading for a rapid response in society. Using models to estimate contamination scenarios in real time plays an important role. Population compartments models based on ordinary differential equations (ODE) for a given region assume two homogeneous premises, the contact mechanisms and diffusion rates, disregarding heterogeneous factors as different contact rates for each municipality and the flow of contaminated people among them. This work considers a hybrid model for covid-19, based on local SIR models and the population flow network among municipalities, responsible for a complex lag dynamic in their contagion curves. Based on actual infection data, local contact rates ( β ) are evaluated. The epidemic evolution at each municipality depends on the local SIR parameters and on the inter-municipality transport flow. When heterogeneity of β values and flow network are included, forecasts differ from those of the homogeneous ODE model. This effect is more relevant when more municipalities are considered, hinting that the latter overestimates new cases. In addition, mitigation scenarios are assessed to evaluate the effect of earlier interventions reducing the inter-municipality flux. Restricting the flow between municipalities in the initial stage of the epidemic is fundamental for flattening the contamination curve, highlighting advantages of a contamination lag between the capital curve and those of other municipalities in the territories.
Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(© 2020 Elsevier B.V. All rights reserved.)
Databáze: MEDLINE
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