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Mathematical modeling of COVID-19 in 14.8 million individuals in Bahia, Brazil.
Oliveira, Juliane F; Jorge, Daniel C P; Veiga, Rafael V; Rodrigues, Moreno S; Torquato, Matheus F; da Silva, Nivea B; Fiaccone, Rosemeire L; Cardim, Luciana L; Pereira, Felipe A C; de Castro, Caio P; Paiva, Aureliano S S; Amad, Alan A S; Lima, Ernesto A B F; Souza, Diego S; Pinho, Suani T R; Ramos, Pablo Ivan P; Andrade, Roberto F S.
Afiliación
  • Oliveira JF; Center of Data and Knowledge Integration for Health (CIDACS), Instituto Gonçalo Moniz, Fundação Oswaldo Cruz, Salvador, Bahia, Brazil. julianlanzin@gmail.com.
  • Jorge DCP; Centre of Mathematics of the University of Porto (CMUP), Department of Mathematics, Porto, Portugal. julianlanzin@gmail.com.
  • Veiga RV; Instituto de Física, Universidade Federal da Bahia, Salvador, Bahia, Brazil.
  • Rodrigues MS; Center of Data and Knowledge Integration for Health (CIDACS), Instituto Gonçalo Moniz, Fundação Oswaldo Cruz, Salvador, Bahia, Brazil.
  • Torquato MF; Fundação Oswaldo Cruz, Porto Velho, Rondônia, Brazil.
  • da Silva NB; College of Engineering, Swansea University, Swansea, Wales, UK.
  • Fiaccone RL; Instituto de Matemática e Estatística, Universidade Federal da Bahia, Salvador, Bahia, Brazil.
  • Cardim LL; Instituto de Matemática e Estatística, Universidade Federal da Bahia, Salvador, Bahia, Brazil.
  • Pereira FAC; Center of Data and Knowledge Integration for Health (CIDACS), Instituto Gonçalo Moniz, Fundação Oswaldo Cruz, Salvador, Bahia, Brazil.
  • de Castro CP; Instituto de Física, Universidade de São Paulo, São Paulo, Brazil.
  • Paiva ASS; Instituto de Física, Universidade Federal da Bahia, Salvador, Bahia, Brazil.
  • Amad AAS; Center of Data and Knowledge Integration for Health (CIDACS), Instituto Gonçalo Moniz, Fundação Oswaldo Cruz, Salvador, Bahia, Brazil.
  • Lima EABF; College of Engineering, Swansea University, Swansea, Wales, UK.
  • Souza DS; Oden Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, TX, USA.
  • Pinho STR; Center of Data and Knowledge Integration for Health (CIDACS), Instituto Gonçalo Moniz, Fundação Oswaldo Cruz, Salvador, Bahia, Brazil.
  • Ramos PIP; Instituto de Física, Universidade Federal da Bahia, Salvador, Bahia, Brazil.
  • Andrade RFS; Center of Data and Knowledge Integration for Health (CIDACS), Instituto Gonçalo Moniz, Fundação Oswaldo Cruz, Salvador, Bahia, Brazil.
Nat Commun ; 12(1): 333, 2021 01 12.
Article en En | MEDLINE | ID: mdl-33436608
COVID-19 is affecting healthcare resources worldwide, with lower and middle-income countries being particularly disadvantaged to mitigate the challenges imposed by the disease, including the availability of a sufficient number of infirmary/ICU hospital beds, ventilators, and medical supplies. Here, we use mathematical modelling to study the dynamics of COVID-19 in Bahia, a state in northeastern Brazil, considering the influences of asymptomatic/non-detected cases, hospitalizations, and mortality. The impacts of policies on the transmission rate were also examined. Our results underscore the difficulties in maintaining a fully operational health infrastructure amidst the pandemic. Lowering the transmission rate is paramount to this objective, but current local efforts, leading to a 36% decrease, remain insufficient to prevent systemic collapse at peak demand, which could be accomplished using periodic interventions. Non-detected cases contribute to a ∽55% increase in R0. Finally, we discuss our results in light of epidemiological data that became available after the initial analyses.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Pandemias / SARS-CoV-2 / COVID-19 / Modelos Teóricos Límite: Humans País/Región como asunto: America do sul / Brasil Idioma: En Revista: Nat Commun Asunto de la revista: BIOLOGIA / CIENCIA Año: 2021 Tipo del documento: Article País de afiliación: Brasil Pais de publicación: Reino Unido
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Pandemias / SARS-CoV-2 / COVID-19 / Modelos Teóricos Límite: Humans País/Región como asunto: America do sul / Brasil Idioma: En Revista: Nat Commun Asunto de la revista: BIOLOGIA / CIENCIA Año: 2021 Tipo del documento: Article País de afiliación: Brasil Pais de publicación: Reino Unido