PropertyValue
?:abstract
  • This primer describes the statistical uncertainty in mechanistic models and provides R code to quantify it. We begin with an overview of mechanistic models for infectious disease, and then describe the sources of statistical uncertainty in the context of a case study on SARS-CoV-2. We describe the statistical uncertainty as belonging to three categories: data uncertainty, stochastic uncertainty, and structural uncertainty. We demonstrate how to account for each of these via statistical uncertainty measures and sensitivity analyses broadly, as well as in a specific case study on estimating the basic reproductive number, $R_0$, for SARS-CoV-2.
?:arxiv_id
  • 2101.07329
?:creator
?:doi
?:doi
  • 10.1093/aje/kwab013
?:journal
  • American_journal_of_epidemiology
?:license
  • arxiv
?:pdf_json_files
  • document_parses/pdf_json/d6a6caea3d091cb95afb4c749356b34e29ae9ebc.json
?:pmid
?:pmid
  • 33475686.0
?:publication_isRelatedTo_Disease
?:sha_id
?:source
  • ArXiv; Medline
?:title
  • Quantifying Uncertainty in Infectious Disease Mechanistic Models
?:type
?:year
  • 2021-01-18

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