Mathematical Modelling of Lockdown Policy for COVID-19 | Zendy

Yuting Fu | Zendy; Haitao Xiang | Zendy; Hanqing Jin | Zendy; Ning Wang | Zendy

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Mathematical Modelling of Lockdown Policy for COVID-19

Author(s) -

Yuting Fu,

Haitao Xiang,

Hanqing Jin,

Ning Wang

Publication year - 2021

Publication title -

procedia computer science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.334

H-Index - 76

ISSN - 1877-0509

DOI - 10.1016/j.procs.2021.04.083

Subject(s) - computer science , covid-19 , cournot competition , consumption (sociology) , balance (ability) , operations research , control (management) , epidemic model , welfare , mathematical economics , economics , artificial intelligence , market economy , medicine , social science , population , demography , disease , pathology , sociology , infectious disease (medical specialty) , engineering , physical medicine and rehabilitation

In this paper, we extend the classic SIR model to find an optimal lockdown policy to balance between the economy and people's health during the outbreak of COVID-19. In our model, we intend to solve a two phases optimisation problem: policymakers control the lockdown rate to maximise the overall welfare of the society; people in different health statuses take different decisions on their working hours and consumption to maximise their utility. We develop a novel method to estimate parameters for the model through various additional sources of data. We use the Cournot equilibrium to model people's behaviour. The analysis of simulation results provides scientific suggestions for policymakers to make critical decisions on when to start the lockdown and how strong it should be during the whole period of the outbreak.

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