Forecasting upper respiratory tract infection burden using high-dimensional time series data and forecast combinations.
Upper respiratory tract infections (URTIs) represent a large strain on primary health resources. To mitigate URTI transmission and public health burdens, it is important to pre-empt and provide forward guidance on URTI burden, while taking into account various facets which influence URTI transmissio...
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| Principais autores: | , , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Public Library of Science (PLoS)
2023-02-01
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| coleção: | PLoS Computational Biology |
| Acesso em linha: | https://doi.org/10.1371/journal.pcbi.1010892 |
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