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Big data assimilation to improve the predictability of COVID-19
The global outbreak of COVID-19 requires us to accurately predict the spread of disease and decide how adopting corresponding strategies to ensure the sustainable development. Most of the existing infectious disease forecasting methods are based on the classical Susceptible-Infectious-Removed (SIR)...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
The Authors. Published by Elsevier B.V. and Beijing Normal University Press (Group) Co., LTD. on behalf of Beijing Normal University.
2020
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7709616/ http://dx.doi.org/10.1016/j.geosus.2020.11.005 |