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Machine learning forecasts for seasonal epidemic peaks: Lessons learnt from an atypical respiratory syncytial virus season.
Morbey, Roger A; Todkill, Daniel; Watson, Conall; Elliot, Alex J.
Affiliation
  • Morbey RA; Real-Time Syndromic Surveillance Team, Field Services, Health Protection Operations, UK Health Security Agency, Birmingham, United Kingdom.
  • Todkill D; Real-Time Syndromic Surveillance Team, Field Services, Health Protection Operations, UK Health Security Agency, Birmingham, United Kingdom.
  • Watson C; Immunisation and Vaccine Preventable Diseases Division, UK Health Security Agency, London, United Kingdom.
  • Elliot AJ; Real-Time Syndromic Surveillance Team, Field Services, Health Protection Operations, UK Health Security Agency, Birmingham, United Kingdom.
PLoS One ; 18(9): e0291932, 2023.
Article in En | MEDLINE | ID: mdl-37738241
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Respiratory Syncytial Virus, Human / Epidemics Type of study: Prognostic_studies Country/Region as subject: Europa Language: En Journal: PLoS One Journal subject: CIENCIA / MEDICINA Year: 2023 Document type: Article Affiliation country: Country of publication:
Fulltext
Add to My VHL
Print
XML
PubMed Links
Search on Google

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Respiratory Syncytial Virus, Human / Epidemics Type of study: Prognostic_studies Country/Region as subject: Europa Language: En Journal: PLoS One Journal subject: CIENCIA / MEDICINA Year: 2023 Document type: Article Affiliation country: Country of publication: