Imperial College London
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Professor Christl Donnelly CBE FMedSci FRS

Faculty of Medicine, School of Public Health

Visiting Professor
 
 
 
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Contact

 

c.donnelly Website

 
 
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Location

 

School of Public HealthWhite City Campus

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Summary

 

Publications

Citation

BibTex format

@unpublished{Parag:2021:10.1101/2021.04.15.21255565,
author = {Parag, KV and Thompson, RN and Donnelly, CA},
doi = {10.1101/2021.04.15.21255565},
title = {Are epidemic growth rates more informative than reproduction numbers?},
url = {http://dx.doi.org/10.1101/2021.04.15.21255565},
year = {2021}
}
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RIS format (EndNote, RefMan)

TY  - UNPB
AB  - <jats:p>Summary statistics, often derived from simplified models of epidemic spread, inform public health policy in real time. The instantaneous reproduction number, <jats:italic>R</jats:italic><jats:sub><jats:italic>t</jats:italic></jats:sub>, is predominant among these statistics, measuring the average ability of an infection to multiply. However, <jats:italic>R</jats:italic><jats:sub><jats:italic>t</jats:italic></jats:sub> encodes no temporal information and is sensitive to modelling assumptions. Consequently, some have proposed the epidemic growth rate, <jats:italic>r</jats:italic><jats:sub><jats:italic>t</jats:italic></jats:sub>, i.e., the rate of change of the log-transformed case incidence, as a more temporally meaningful and model-agnostic policy guide. We examine this assertion, identifying if and when estimates of <jats:italic>r</jats:italic><jats:sub><jats:italic>t</jats:italic></jats:sub> are more informative than those of <jats:italic>R</jats:italic><jats:sub><jats:italic>t</jats:italic></jats:sub>. We assess their relative strengths both for learning about pathogen transmission mechanisms and for guiding public health interventions in real time.</jats:p>
AU  - Parag,KV
AU  - Thompson,RN
AU  - Donnelly,CA
DO  - 10.1101/2021.04.15.21255565
PY  - 2021///
TI  - Are epidemic growth rates more informative than reproduction numbers?
UR  - http://dx.doi.org/10.1101/2021.04.15.21255565
ER  -
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