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Modelling COVID-19
As the COVID-19 pandemic continues, mathematical epidemiologists share their views on what models reveal about how the disease has spread, the current state of play and what work still needs to be done.
| Autores principales: | , , , , , , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2020
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7201389/ https://www.ncbi.nlm.nih.gov/pubmed/33728401 http://dx.doi.org/10.1038/s42254-020-0178-4 |
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| author | Vespignani, Alessandro Tian, Huaiyu Dye, Christopher Lloyd-Smith, James O. Eggo, Rosalind M. Shrestha, Munik Scarpino, Samuel V. Gutierrez, Bernardo Kraemer, Moritz U. G. Wu, Joseph Leung, Kathy Leung, Gabriel M. |
| author_facet | Vespignani, Alessandro Tian, Huaiyu Dye, Christopher Lloyd-Smith, James O. Eggo, Rosalind M. Shrestha, Munik Scarpino, Samuel V. Gutierrez, Bernardo Kraemer, Moritz U. G. Wu, Joseph Leung, Kathy Leung, Gabriel M. |
| author_sort | Vespignani, Alessandro |
| collection | PubMed |
| description | As the COVID-19 pandemic continues, mathematical epidemiologists share their views on what models reveal about how the disease has spread, the current state of play and what work still needs to be done. |
| format | Online Article Text |
| id | pubmed-7201389 |
| institution | National Center for Biotechnology Information |
| language | English |
| publishDate | 2020 |
| publisher | Nature Publishing Group UK |
| record_format | MEDLINE/PubMed |
| spelling | pubmed-72013892020-05-06 Modelling COVID-19 Vespignani, Alessandro Tian, Huaiyu Dye, Christopher Lloyd-Smith, James O. Eggo, Rosalind M. Shrestha, Munik Scarpino, Samuel V. Gutierrez, Bernardo Kraemer, Moritz U. G. Wu, Joseph Leung, Kathy Leung, Gabriel M. Nat Rev Phys Viewpoint As the COVID-19 pandemic continues, mathematical epidemiologists share their views on what models reveal about how the disease has spread, the current state of play and what work still needs to be done. Nature Publishing Group UK 2020-05-06 2020 /pmc/articles/PMC7201389/ /pubmed/33728401 http://dx.doi.org/10.1038/s42254-020-0178-4 Text en © Springer Nature Limited 2020 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
| spellingShingle | Viewpoint Vespignani, Alessandro Tian, Huaiyu Dye, Christopher Lloyd-Smith, James O. Eggo, Rosalind M. Shrestha, Munik Scarpino, Samuel V. Gutierrez, Bernardo Kraemer, Moritz U. G. Wu, Joseph Leung, Kathy Leung, Gabriel M. Modelling COVID-19 |
| title | Modelling COVID-19 |
| title_full | Modelling COVID-19 |
| title_fullStr | Modelling COVID-19 |
| title_full_unstemmed | Modelling COVID-19 |
| title_short | Modelling COVID-19 |
| title_sort | modelling covid-19 |
| topic | Viewpoint |
| url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7201389/ https://www.ncbi.nlm.nih.gov/pubmed/33728401 http://dx.doi.org/10.1038/s42254-020-0178-4 |
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