Reconciling early-outbreak estimates of the basic reproductive number and its uncertainty: framework and applications to the novel coronavirus (SARS-CoV-2) outbreak.
J R Soc Interface
; 17(168): 20200144, 2020 07.
Article
in English
| MEDLINE | ID: covidwho-665024
Preprint
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This scientific journal article is probably based on a previously available preprint. It has been identified through a machine matching algorithm, human confirmation is still pending.
See preprint
ABSTRACT
A novel coronavirus (SARS-CoV-2) emerged as a global threat in December 2019. As the epidemic progresses, disease modellers continue to focus on estimating the basic reproductive number [Formula see text]-the average number of secondary cases caused by a primary case in an otherwise susceptible population. The modelling approaches and resulting estimates of [Formula see text] during the beginning of the outbreak vary widely, despite relying on similar data sources. Here, we present a statistical framework for comparing and combining different estimates of [Formula see text] across a wide range of models by decomposing the basic reproductive number into three key quantities the exponential growth rate, the mean generation interval and the generation-interval dispersion. We apply our framework to early estimates of [Formula see text] for the SARS-CoV-2 outbreak, showing that many [Formula see text] estimates are overly confident. Our results emphasize the importance of propagating uncertainties in all components of [Formula see text], including the shape of the generation-interval distribution, in efforts to estimate [Formula see text] at the outset of an epidemic.
Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Pneumonia, Viral
/
Disease Outbreaks
/
Coronavirus Infections
/
Basic Reproduction Number
/
Betacoronavirus
/
Models, Biological
Type of study:
Observational study
/
Prognostic study
Limits:
Humans
Country/Region as subject:
Asia
Language:
English
Journal:
J R Soc Interface
Year:
2020
Document Type:
Article
Affiliation country:
Rsif.2020.0144
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