Bayesian sequential data assimilation for COVID-19 forecasting

Author:

Daza-Torres Maria L.ORCID,Capistrán Marcos A.ORCID,Capella Antonio,Christen J. AndrésORCID

Funder

UNAM

CONACYT

Publisher

Elsevier BV

Subject

Virology,Infectious Diseases,Public Health, Environmental and Occupational Health,Microbiology,Parasitology,Epidemiology

Reference34 articles.

1. Forecasting Ebola with a regression transmission model;Asher;Epidemics,2018

2. The challenges of modeling and forecasting the spread of COVID-19;Bertozzi,2020

3. Epidemiology and transmission of COVID-19 in shenzhen China: Analysis of 391 cases and 1,286 of their close contacts;Bi,2020

4. Comparing ensemble approaches for short-term probabilistic COVID-19 forecasts in the US;Brooks;Int. Inst. Forecasters,2020

5. Forecasting hospital demand in metropolitan areas during the current COVID-19 pandemic and estimates of lockdown-induced 2nd waves;Capistran;PLoS One,2021

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