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Multiple waves of COVID-19: a pathway model approach.
Vasconcelos, Giovani L; Pessoa, Nathan L; Silva, Natan B; Macêdo, Antônio M S; Brum, Arthur A; Ospina, Raydonal; Tirnakli, Ugur.
Affiliation
  • Vasconcelos GL; Departamento de Física, Universidade Federal do Paraná, Curitiba, Paraná 81531-980 Brazil.
  • Pessoa NL; Departamento de Física, Universidade Federal de Pernambuco, Recife, Pernambuco 50670-901 Brazil.
  • Silva NB; Centro de Apoio à Pesquisa, Universidade Federal Rural de Pernambuco, Recife, Pernambuco 52171-900 Brazil.
  • Macêdo AMS; Departamento de Física, Universidade Federal do Paraná, Curitiba, Paraná 81531-980 Brazil.
  • Brum AA; Departamento de Física, Universidade Federal de Pernambuco, Recife, Pernambuco 50670-901 Brazil.
  • Ospina R; Departamento de Física, Universidade Federal de Pernambuco, Recife, Pernambuco 50670-901 Brazil.
  • Tirnakli U; Departamento de Estatística, Universidade Federal de Pernambuco, Recife, Pernambuco 50740-540 Brazil.
Nonlinear Dyn ; 111(7): 6855-6872, 2023.
Article in En | MEDLINE | ID: mdl-36588986
A generalized pathway model, with time-dependent parameters, is applied to describe the mortality curves of the COVID-19 disease for several countries that exhibit multiple waves of infections. The pathway approach adopted here is formulated explicitly in time, in the sense that the model's growth rate for the number of deaths or infections is written as an explicit function of time, rather than in terms of the cumulative quantity itself. This allows for a direct fit of the model to daily data (new deaths or new cases) without the need of any integration. The model is applied to COVID-19 mortality curves for ten selected countries and found to be in very good agreement with the data for all cases considered. From the fitted theoretical curves for a given location, relevant epidemiological information can be extracted, such as the starting and peak dates for each successive wave. It is argued that obtaining reliable estimates for such characteristic points is important for studying the effectiveness of interventions and the possible negative impact of their relaxation, as it allows for a direct comparison of the time of adoption/relaxation of control measures with the peaks and troughs of the epidemic curve.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies Language: En Journal: Nonlinear Dyn Year: 2023 Document type: Article Country of publication: Netherlands

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies Language: En Journal: Nonlinear Dyn Year: 2023 Document type: Article Country of publication: Netherlands