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Complexity signatures in the COVID-19 epidemic: power law behaviour in the saturation regime of fatality curves
Giovani L. Vasconcelos; Antônio M.S. Macêdo; Gerson C. Duarte-Filho; Arthur A. Araújo; Raydonal Ospina; Francisco A. G. Almeida.
Afiliação
  • Giovani L. Vasconcelos; Universidade Federal do Paraná
  • Antônio M.S. Macêdo; Universidade Federal de Pernambuco
  • Gerson C. Duarte-Filho; Universidade Federal de Sergipe
  • Arthur A. Araújo; Universidade Federal de Pernambuco
  • Raydonal Ospina; Universidade Federal de Pernambuco
  • Francisco A. G. Almeida; Universidade Federal de Sergipe
Preprint em Inglês | medRxiv | ID: ppmedrxiv-20152140
ABSTRACT
ABSTRACWe apply a versatile growth model, whose growth rate is given by a generalised beta distribution, to describe the complex behaviour of the fatality curves of the COVID-19 disease for several countries in Europe and North America. We show that the COVID-19 epidemic curves not only may present a subexponential early growth but can also exhibit a similar subexponential (power-law) behaviour in the saturation regime. We argue that the power-law exponent of the latter regime, which measures how quickly the curve approaches the plateau, is directly related to control measures, in the sense that the less strict the control, the smaller the exponent and hence the slower the diseases progresses to its end. The power-law saturation uncovered here is an important result, because it signals to policymakers and health authorities that it is important to keep control measures for as long as possible, so as to avoid a slow, power-law ending of the disease. The slower the approach to the plateau, the longer the virus lingers on in the population, and the greater not only the final death toll but also the risk of a resurgence of infections.
Licença
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Texto completo: Disponível Coleções: Preprints Base de dados: medRxiv Tipo de estudo: Estudo prognóstico Idioma: Inglês Ano de publicação: 2020 Tipo de documento: Preprint
Texto completo: Disponível Coleções: Preprints Base de dados: medRxiv Tipo de estudo: Estudo prognóstico Idioma: Inglês Ano de publicação: 2020 Tipo de documento: Preprint
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