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A real-time regional model for COVID-19: Probabilistic situational awareness and forecasting.
Engebretsen, Solveig; Diz-Lois Palomares, Alfonso; Rø, Gunnar; Kristoffersen, Anja Bråthen; Lindstrøm, Jonas Christoffer; Engø-Monsen, Kenth; Kamineni, Meghana; Hin Chan, Louis Yat; Dale, Ørjan; Midtbø, Jørgen Eriksson; Stenerud, Kristian Lindalen; Di Ruscio, Francesco; White, Richard; Frigessi, Arnoldo; de Blasio, Birgitte Freiesleben.
Afiliación
  • Engebretsen S; SAMBA, Norwegian Computing Center, Oslo, Norway.
  • Diz-Lois Palomares A; Department of Method Development and Analytics. Norwegian Institute of Public Health, Oslo, Norway.
  • Rø G; Department of Method Development and Analytics. Norwegian Institute of Public Health, Oslo, Norway.
  • Kristoffersen AB; Department of Method Development and Analytics. Norwegian Institute of Public Health, Oslo, Norway.
  • Lindstrøm JC; Department of Method Development and Analytics. Norwegian Institute of Public Health, Oslo, Norway.
  • Engø-Monsen K; Telenor Research, Fornebu, Norway.
  • Kamineni M; Oslo Centre for Biostatistics and Epidemiology. University of Oslo and Oslo University Hospital, Oslo, Norway.
  • Hin Chan LY; Department of Method Development and Analytics. Norwegian Institute of Public Health, Oslo, Norway.
  • Dale Ø; Telenor Norge AS Fornebu, Norway.
  • Midtbø JE; Department of Method Development and Analytics. Norwegian Institute of Public Health, Oslo, Norway.
  • Stenerud KL; Telenor Norge AS Fornebu, Norway.
  • Di Ruscio F; Telenor Norge AS Fornebu, Norway.
  • White R; Department of Method Development and Analytics. Norwegian Institute of Public Health, Oslo, Norway.
  • Frigessi A; Department of Method Development and Analytics. Norwegian Institute of Public Health, Oslo, Norway.
  • de Blasio BF; Oslo Centre for Biostatistics and Epidemiology. University of Oslo and Oslo University Hospital, Oslo, Norway.
PLoS Comput Biol ; 19(1): e1010860, 2023 01.
Article en En | MEDLINE | ID: mdl-36689468
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: COVID-19 Tipo de estudio: Diagnostic_studies / Prognostic_studies Límite: Humans Idioma: En Revista: PLoS Comput Biol Asunto de la revista: BIOLOGIA / INFORMATICA MEDICA Año: 2023 Tipo del documento: Article País de afiliación: Noruega
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: COVID-19 Tipo de estudio: Diagnostic_studies / Prognostic_studies Límite: Humans Idioma: En Revista: PLoS Comput Biol Asunto de la revista: BIOLOGIA / INFORMATICA MEDICA Año: 2023 Tipo del documento: Article País de afiliación: Noruega