Imperial College London
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Dr Kris V Parag

Faculty of Medicine, School of Public Health

Research Fellow
 
 
 
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Contact

 

k.parag

 
 
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Location

 

Wright Fleming WingSt Mary's Campus

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Summary

 

Publications

Citation

BibTex format

@article{Parag:2020:10.1101/2020.11.23.20236968,
author = {Parag, KV and Cowling, BJ and Donnelly, CA},
doi = {10.1101/2020.11.23.20236968},
title = {Deciphering early-warning signals of SARS-CoV-2 elimination and resurgence from limited data at multiple scales},
url = {http://dx.doi.org/10.1101/2020.11.23.20236968},
year = {2020}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - <jats:title>Abstract</jats:title><jats:p>Inferring the transmission potential of an infectious disease during low-incidence periods following epidemic waves is crucial for preparedness. In such periods, scarce data may hinder existing inference methods, blurring early-warning signals essential for discriminating between the likelihoods of resurgence versus elimination. Advanced insight into whether elevating caseloads (requiring swift community-wide interventions) or local elimination (allowing controls to be relaxed or refocussed on case-importation) might occur, can separate decisive from ineffective policy. By generalising and fusing recent approaches, we propose a novel early-warning framework that maximises the information extracted from low-incidence data to robustly infer the chances of sustained local-transmission or elimination in real time, at any scale of investigation (assuming sufficiently good surveillance). Applying this framework, we decipher hidden disease-transmission signals in prolonged low-incidence COVID-19 data from New Zealand, Hong Kong and Victoria, Australia. We uncover how timely interventions associate with averting resurgent waves, support official elimination declarations and evidence the effectiveness of the rapid, adaptive COVID-19 responses employed in these regions.</jats:p>
AU  - Parag,KV
AU  - Cowling,BJ
AU  - Donnelly,CA
DO  - 10.1101/2020.11.23.20236968
PY  - 2020///
TI  - Deciphering early-warning signals of SARS-CoV-2 elimination and resurgence from limited data at multiple scales
UR  - http://dx.doi.org/10.1101/2020.11.23.20236968
ER  -
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