A real-time regional model for COVID-19: Probabilistic situational awareness and forecasting

The COVID-19 pandemic is challenging nations with devastating health and economic consequences. The spread of the disease has revealed major geographical heterogeneity because of regionally varying individual behaviour and mobility patterns, unequal meteorological conditions, diverse viral variants,...

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Veröffentlicht in:	PLoS computational biology 2023-01, Vol.19 (1), p.e1010860-e1010860
Hauptverfasser:	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
Format:	Artikel
Sprache:	eng
Schlagworte:	Analysis Awareness Bayes Theorem Bayesian analysis Bayesian statistical decision theory Biology and Life Sciences Cellular telephones Communicable Disease Control Contact tracing Coronaviruses COVID-19 COVID-19 - epidemiology COVID-19 - prevention & control COVID-19 vaccines Datasets Disease transmission Epidemics Forecasting Forecasts and trends Geography Heterogeneity Hospitals Humans Immunization Infectious diseases Intensive care Laboratories Mathematical models Medicine and Health Sciences Metapopulations Methods Mobility Norway Pandemics People and Places Real time Regional development Sentinel health events Severe acute respiratory syndrome coronavirus 2 Situational awareness Statistical analysis Statistical models Statistics Stochasticity Telecommunications towers United Kingdom Vaccination Viral diseases
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