| Autor: |
Oliveira JF; Center of Data and Knowledge Integration for Health (CIDACS), Instituto Gonçalo Moniz, Fundação Oswaldo Cruz, Salvador, Bahia, Brazil. julianlanzin@gmail.com.; Centre of Mathematics of the University of Porto (CMUP), Department of Mathematics, Porto, Portugal. julianlanzin@gmail.com., Jorge DCP; Instituto de Física, Universidade Federal da Bahia, Salvador, Bahia, Brazil., Veiga RV; Center of Data and Knowledge Integration for Health (CIDACS), Instituto Gonçalo Moniz, Fundação Oswaldo Cruz, Salvador, Bahia, Brazil., Rodrigues MS; Fundação Oswaldo Cruz, Porto Velho, Rondônia, Brazil., Torquato MF; College of Engineering, Swansea University, Swansea, Wales, UK., da Silva NB; Instituto de Matemática e Estatística, Universidade Federal da Bahia, Salvador, Bahia, Brazil., Fiaccone RL; Instituto de Matemática e Estatística, Universidade Federal da Bahia, Salvador, Bahia, Brazil., Cardim LL; Center of Data and Knowledge Integration for Health (CIDACS), Instituto Gonçalo Moniz, Fundação Oswaldo Cruz, Salvador, Bahia, Brazil., Pereira FAC; Instituto de Física, Universidade de São Paulo, São Paulo, Brazil., de Castro CP; Instituto de Física, Universidade Federal da Bahia, Salvador, Bahia, Brazil., Paiva ASS; Center of Data and Knowledge Integration for Health (CIDACS), Instituto Gonçalo Moniz, Fundação Oswaldo Cruz, Salvador, Bahia, Brazil., Amad AAS; College of Engineering, Swansea University, Swansea, Wales, UK., Lima EABF; Oden Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, TX, USA., Souza DS; Center of Data and Knowledge Integration for Health (CIDACS), Instituto Gonçalo Moniz, Fundação Oswaldo Cruz, Salvador, Bahia, Brazil., Pinho STR; Instituto de Física, Universidade Federal da Bahia, Salvador, Bahia, Brazil., Ramos PIP; Center of Data and Knowledge Integration for Health (CIDACS), Instituto Gonçalo Moniz, Fundação Oswaldo Cruz, Salvador, Bahia, Brazil., Andrade RFS; Center of Data and Knowledge Integration for Health (CIDACS), Instituto Gonçalo Moniz, Fundação Oswaldo Cruz, Salvador, Bahia, Brazil.; Instituto de Física, Universidade Federal da Bahia, Salvador, Bahia, Brazil. |
| Abstrakt: |
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 R 0 . Finally, we discuss our results in light of epidemiological data that became available after the initial analyses. |
