Quantifying Uncertainty in Mechanistic Models of Infectious Disease.
Am J Epidemiol
; 190(7): 1377-1385, 2021 07 01.
Article
in English
| MEDLINE | ID: covidwho-2255972
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 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We describe the statistical uncertainty as belonging to 3 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.
Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Epidemiologic Measurements
/
Models, Statistical
/
Uncertainty
/
COVID-19
Limits:
Humans
Language:
English
Journal:
Am J Epidemiol
Year:
2021
Document Type:
Article
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