Modelling COVID-19 Contagion: Risk Assessment and Targeted Mitigation Policies

62 Pages Posted: 2 Sep 2020

See all articles by Rama Cont

Rama Cont

University of Oxford

Artur Kotlicki

University of Oxford - Mathematical Institute

Renyuan Xu

University of Southern California - Epstein Department of Industrial & Systems Engineering

Date Written: August 26, 2020

Abstract

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 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.

Note: Funding: None to declare

Declaration of Interest: None to declare

Keywords: epidemic modeling, COVID-19, coronavirus, compartmental models, SIR model, stochastic epidemic model

JEL Classification: I1, I18

Suggested Citation

Cont, Rama and Kotlicki, Artur and Xu, Renyuan, Modelling COVID-19 Contagion: Risk Assessment and Targeted Mitigation Policies (August 26, 2020). Available at SSRN: https://ssrn.com/abstract=3681507 or http://dx.doi.org/10.2139/ssrn.3681507

Rama Cont (Contact Author)

University of Oxford ( email )

Mathematical Institute
Oxford, OX2 6GG
United Kingdom

HOME PAGE: http://www.maths.ox.ac.uk/people/rama.cont

Artur Kotlicki

University of Oxford - Mathematical Institute ( email )

Andrew Wiles Building
Radcliffe Observatory Quarter (550)
Oxford, OX2 6GG
United Kingdom

HOME PAGE: http://https://www.maths.ox.ac.uk/people/artur.kotlicki

Renyuan Xu

University of Southern California - Epstein Department of Industrial & Systems Engineering ( email )

United States

HOME PAGE: http://renyuanxu.github.io

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