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

ABSTRACT: We use a spatial epidemic model with demographic and geographical heterogeneity to study the regional dynamics of COVID-19 across 133 regions in England. Our model emphasizes the role of variability of regional outcomes and heterogeneity across age groups and geographical locations, and provides a framework for assessing the impact of policies targeted towards subpopulations 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 emphasize 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 centralized policies.

SUBMITTER: Cont R

PROVIDER: S-EPMC8101016 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature

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

Cont Rama R Kotlicki Artur A Xu Renyuan R

Royal Society open science 20210331 3

We use a spatial epidemic model with demographic and geographical heterogeneity to study the regional dynamics of COVID-19 across 133 regions in England. Our model emphasizes the role of variability of regional outcomes and heterogeneity across age groups and geographical locations, and provides a framework for assessing the impact of policies targeted towards subpopulations or regions. We define a concept of efficiency for comparative analysis of epidemic control policies and show targeted miti ...[more]

PMID: 34035936

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