Modelling COVID-19.
Applied mathematics
Complex networks
Journal
Nature reviews. Physics
ISSN: 2522-5820
Titre abrégé: Nat Rev Phys
Pays: England
ID NLM: 101777089
Informations de publication
Date de publication:
2020
2020
Historique:
accepted:
07
04
2020
pubmed:
18
3
2021
medline:
18
3
2021
entrez:
17
3
2021
Statut:
ppublish
Résumé
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.
Identifiants
pubmed: 33728401
doi: 10.1038/s42254-020-0178-4
pii: 178
pmc: PMC7201389
doi:
Types de publication
Journal Article
Review
Langues
eng
Pagination
279-281Informations de copyright
© Springer Nature Limited 2020.
Déclaration de conflit d'intérêts
Competing interestsThe authors declare no competing interests.
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