📖
Modelling COVID-19 contagion: risk assessment and targeted mitigation policies
Rama Cont, Artur Kotlicki, Renyuan Xu

Modelling COVID-19 contagion: risk assessment and targeted mitigation policies

Author / Organization:
Science & Mathematics Published 2020 Verification Pending

Overview & Synopsis

We use a spatial epidemic model with demographic and geographic heterogeneity to study the regional dynamics of COVID-19 across 133 regions in England. Our model emphasises the role of variability of regional outcomes and hetero-geneity 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 subpopulations 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.

Advertisement
SPONSOR CONTENT
Indexed from repository: HAL Open Science (hal.science)
Loading document from verified source...
Keyboard Shortcuts: ← / → for pages • + / - for zoom • 0 to fit width Powered by Mozilla PDF.js v3.11

Document Information

Document Title Modelling COVID-19 contagion: risk assessment and targeted mitigation policies
Author / Organization Rama Cont, Artur Kotlicki, Renyuan Xu
Subject & Discipline Multidisciplinary Academic Open Research
Categories Science & Mathematics
Publication Year 2020
License / Rights Open Access / Creative Commons
Resource Verification Listed PDF (Verification Pending)
Original Host Website HAL Open Science (hal.science)
File Format application/pdf (Portable Document Format)
Language EN
Catalog ID DOC-60691
Original Source Link Visit Source Page on hal.science »