Your browser doesn't support javascript.
loading
Modinterv COVID-19: An online platform to monitor the evolution of epidemic curves
Arthur A. Brum; Giovani L. Vasconcelos; Gerson C. Duarte-Filho; Raydonal Ospina; Francisco A. G. Almeida; Antônio M. S. Macêdo.
Afiliação
  • Arthur A. Brum; Universidade Federal de Pernambuco
  • Giovani L. Vasconcelos; Universidade Federal do Paraná
  • Gerson C. Duarte-Filho; Universidade Federal de Sergipe
  • Raydonal Ospina; Universidade Federal de Pernambuco
  • Francisco A. G. Almeida; Universidade Federal de Sergipe
  • Antônio M. S. Macêdo; Universidade Federal de Pernambuco
Preprint em Inglês | medRxiv | ID: ppmedrxiv-22270192
ABSTRACT
We present the software ModInterv as an informatics tool to monitor, in an automated and user-friendly manner, the evolution and trend of COVID-19 epidemic curves, both for cases and deaths. The ModInterv software uses parametric generalized growth models, together with LOWESS regression analysis, to fit epidemic curves with multiple waves of infections for countries around the world as well as for states and cities in Brazil and the USA. The software automatically accesses publicly available COVID-19 databases maintained by the Johns Hopkins University (for countries as well as states and cities in the USA) and the Federal University of Vicosa (for states and cities in Brazil). The richness of the implemented models lies in the possibility of quantitatively and reliably detecting the distinct acceleration regimes of the disease. We describe the backend structure of software as well as its practical use. The software helps the user not only to understand the current stage of the epidemic in a chosen location but also to make short term predictions as to how the curves may evolve. The app is freely available on the internet (http//fisica.ufpr.br/modinterv), thus making a sophisticated mathematical analysis of epidemic data readily accessible to any interested user.
Licença
cc_no
Texto completo: Disponível Coleções: Preprints Base de dados: medRxiv Tipo de estudo: Estudo prognóstico Idioma: Inglês Ano de publicação: 2022 Tipo de documento: Preprint
Texto completo: Disponível Coleções: Preprints Base de dados: medRxiv Tipo de estudo: Estudo prognóstico Idioma: Inglês Ano de publicação: 2022 Tipo de documento: Preprint
...