A Two-Phase Dynamic Contagion Model for COVID-19

29 Pages Posted: 16 Jun 2020

See all articles by Zezhun Chen

Zezhun Chen

London School of Economics & Political Science (LSE) - Department of Statistics

Angelos Dassios

London School of Economics & Political Science (LSE) - Department of Statistics

Valerie Kuan

University College London

Jia Wei Lim

Brunel University London

Yan Qu

University of Warwick - Department of Statistics

Budhi Surya

Victoria University of Wellington

Hongbiao Zhao

Shanghai University of Finance and Economics; London School of Economics & Political Science (LSE)

Date Written: June 10, 2020

Abstract

In this paper, we propose a continuous-time stochastic intensity model, namely, two-phase dynamic contagion process(2P-DCP),for modelling the epidemic contagion of COVID-19 and investigating the lockdown effect based on the dynamic contagion model introduced by Dassios and Zhao (2011). It allows randomness to the infectivity of individuals rather than a constant reproduction number as assumed by standard models. Key epidemiological quantities, such as the distribution of final epidemic size and expected epidemic duration, are derived and estimated based on real data for various regions and countries. The associated time lag of the effect of intervention in each country or region is estimated. Our results are consistent with the incubation time of COVID-19 found by recent medical study. We demonstrate that our model could potentially be a valuable tool in the modeling of COVID-19. More importantly, the proposed model of 2P-DCP could also be used as an important tool in epidemiological modelling as this type of contagion models with very simple structures is adequate to describe the evolution of regional epidemic and worldwide pandemic.

Note: Funding: There are no sources of funding to declare.

Conflict of Interest: There are no conflicts of interest to declare.

Keywords: COVID-19; SARS-CoV-2; Coronavirus; Stochastic intensity model; Stochastic epidemic model; Two-phase dynamic contagion process

JEL Classification: 60G55; 60J75

Suggested Citation

Chen, Zezhun and Dassios, Angelos and Kuan, Valerie and Lim, Jia Wei and Qu, Yan and Surya, Budhi and Zhao, Hongbiao, A Two-Phase Dynamic Contagion Model for COVID-19 (June 10, 2020). Available at SSRN: https://ssrn.com/abstract=3624102 or http://dx.doi.org/10.2139/ssrn.3624102

Zezhun Chen

London School of Economics & Political Science (LSE) - Department of Statistics ( email )

Houghton Street
London, England WC2A 2AE
United Kingdom

Angelos Dassios

London School of Economics & Political Science (LSE) - Department of Statistics ( email )

Houghton Street
London, England WC2A 2AE
United Kingdom

Valerie Kuan

University College London ( email )

Gower Street
London, WC1E 6BT
United Kingdom

Jia Wei Lim

Brunel University London ( email )

Kingston Lane
Uxbridge, Middlesex UB8 3PH
United Kingdom

Yan Qu (Contact Author)

University of Warwick - Department of Statistics ( email )

Coventry, CV47AL
United Kingdom

Budhi Surya

Victoria University of Wellington ( email )

P.O. Box 600
Wellington, 6140
New Zealand
+64 4 463 5669 (Phone)

HOME PAGE: http://homepages.ecs.vuw.ac.nz/Users/BudhiSurya/WebHome

Hongbiao Zhao

Shanghai University of Finance and Economics ( email )

No. 777 Guoding Road
Yangpu District
Shanghai, Shanghai 200433
China

HOME PAGE: http://hongbiaozhao.weebly.com/

London School of Economics & Political Science (LSE)

Houghton Street
London, WC2A 2AE
United Kingdom

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