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Structural identifiability of compartmental models for infectious disease transmission is influenced by data type.
Dankwa, Emmanuelle A; Brouwer, Andrew F; Donnelly, Christl A.
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  • Dankwa EA; Department of Statistics, University of Oxford, 24-29 St Giles', Oxford, United Kingdom.
  • Brouwer AF; Department of Epidemiology, University of Michigan, 1415 Washington Heights, Ann Arbor, MI 48109-2029, USA.
  • Donnelly CA; Department of Statistics, University of Oxford, 24-29 St Giles', Oxford, United Kingdom; Department of Infectious Disease Epidemiology, Faculty of Medicine, School of Public Health, Imperial College London, United Kingdom. Electronic address: christl.donnelly@stats.ox.ac.uk.
Epidemics ; 41: 100643, 2022 12.
Article in En | MEDLINE | ID: mdl-36308994
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Epidemiological Models / Models, Biological Type of study: Risk_factors_studies Language: En Journal: Epidemics Year: 2022 Document type: Article Affiliation country:
Fulltext
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Epidemiological Models / Models, Biological Type of study: Risk_factors_studies Language: En Journal: Epidemics Year: 2022 Document type: Article Affiliation country: