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Country-report pattern corrections of new cases allow accurate 2-week predictions of COVID-19 evolution with the Gompertz model.
Villanueva, I; Conesa, D; Català, M; López Cano, C; Perramon-Malavez, A; Molinuevo, D; de Rioja, V L; López, D; Alonso, S; Cardona, P J; Montañola-Sales, C; Prats, C; Alvarez-Lacalle, E.
Afiliação
  • Villanueva I; Department of Physics, Universitat Politècnica de Catalunya (BarcelonaTech), 08860, Castelldefels, Spain.
  • Conesa D; Department of Information and Communication Technologies, Universitat Pompeu Fabra, 08018, Barcelona, Spain.
  • Català M; Department of Physics, Universitat Politècnica de Catalunya (BarcelonaTech), 08860, Castelldefels, Spain.
  • López Cano C; Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDORMS), University of Oxford, Oxford, UK.
  • Perramon-Malavez A; Department of Physics, Universitat Politècnica de Catalunya (BarcelonaTech), 08860, Castelldefels, Spain.
  • Molinuevo D; Department of Physics, Universitat Politècnica de Catalunya (BarcelonaTech), 08860, Castelldefels, Spain.
  • de Rioja VL; Medical Image Processing Lab, École Polytechnique Fédérale de Laussane, Geneva, Switzerland.
  • López D; Department of Physics, Universitat Politècnica de Catalunya (BarcelonaTech), 08860, Castelldefels, Spain.
  • Alonso S; Department of Physics, Universitat Politècnica de Catalunya (BarcelonaTech), 08860, Castelldefels, Spain.
  • Cardona PJ; Department of Physics, Universitat Politècnica de Catalunya (BarcelonaTech), 08860, Castelldefels, Spain.
  • Montañola-Sales C; Microbiology Department, Laboratori Clínic Metropolitana Nord, Hospital Universitari Germans Trias i Pujol, Institut Universitari Germans Trias i Pujol (IGTP), Badalona, Catalonia, Spain.
  • Prats C; Departament of Genetics and Microbiology, Universitat Autònoma de Barcelona, Cerdanyola, Catalonia, Spain.
  • Alvarez-Lacalle E; Biomedical Research Networking Centre in Respiratory Diseases CIBERES, Instituto de Salud Carlos III, Madrid, Spain.
Sci Rep ; 14(1): 10775, 2024 05 11.
Article em En | MEDLINE | ID: mdl-38730261
ABSTRACT
Accurate short-term predictions of COVID-19 cases with empirical models allow Health Officials to prepare for hospital contingencies in a two-three week window given the delay between case reporting and the admission of patients in a hospital. We investigate the ability of Gompertz-type empiric models to provide accurate prediction up to two and three weeks to give a large window of preparation in case of a surge in virus transmission. We investigate the stability of the prediction and its accuracy using bi-weekly predictions during the last trimester of 2020 and 2021. Using data from 2020, we show that understanding and correcting for the daily reporting structure of cases in the different countries is key to accomplish accurate predictions. Furthermore, we found that filtering out predictions that are highly unstable to changes in the parameters of the model, which are roughly 20%, reduces strongly the number of predictions that are way-off. The method is then tested for robustness with data from 2021. We found that, for this data, only 1-2% of the one-week predictions were off by more than 50%. This increased to 3% for two-week predictions, and only for three-week predictions it reached 10%.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: SARS-CoV-2 / COVID-19 Limite: Humans Idioma: En Revista: Sci Rep Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Espanha

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: SARS-CoV-2 / COVID-19 Limite: Humans Idioma: En Revista: Sci Rep Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Espanha