Publications

BibTex format

@article{Cont:2020:10.1101/2020.08.26.20182477,
author = {Cont, R and Kotlicki, A and Xu, R},
doi = {10.1101/2020.08.26.20182477},
title = {Modelling COVID-19 contagion: Risk assessment and targeted mitigation policies},
url = {http://dx.doi.org/10.1101/2020.08.26.20182477},
year = {2020}
}

Download

RIS format (EndNote, RefMan)

TY  - JOUR
AB  - <jats:title>Abstract</jats:title><jats:p>We use a spatial epidemic model with demographic and geographic heterogeneity to study the regional dynamics of COVID-19 across 133 regions in England.</jats:p><jats:p>Our model emphasises the role of variability of regional outcomes and heterogeneity across age groups and geographic locations, and provides a framework for assessing the impact of policies targeted towards sub-populations or regions. We define a concept of efficiency for comparative analysis of epidemic control policies and show targeted mitigation policies based on local monitoring to be more efficient than country-level or non-targeted measures. In particular, our results emphasise the importance of shielding vulnerable sub-populations and show that targeted policies based on local monitoring can considerably lower fatality forecasts and, in many cases, prevent the emergence of second waves which may occur under centralised policies.</jats:p>
AU  - Cont,R
AU  - Kotlicki,A
AU  - Xu,R
DO  - 10.1101/2020.08.26.20182477
PY  - 2020///
TI  - Modelling COVID-19 contagion: Risk assessment and targeted mitigation policies
UR  - http://dx.doi.org/10.1101/2020.08.26.20182477
ER  -

Download

ProfessorRamaCont

Contact

Location

Summary

Citation

BibTex format

RIS format (EndNote, RefMan)