On the effectiveness of lockdown and the risk of easing lockdown
- Associate Professor Tatsushi Oka, Dr Dan Zhu, and Dr Wei Wei, Department of Econometrics and Business Statistics, Monash Business School
Background and objectives
The outbreak of COVID-19 causes multiple crises: a health crisis, an economic crisis, and a financial crisis, which interact in a complex manner. Although policymakers are providing substantial support to stimulate the economy and financial markets, lockdown is one of few effective policies to mitigate the spread of COVID-19, until the development of therapeutics and vaccines. After the introduction of lockdown policy, infection rates of COVID-19 decreases slowly across many countries. Still, important questions, such as the timing of lifting lockdown restrictions, how to lift the lockdown (gradually, regionally or depending on risk groups), and how likely that another outbreak happens, are yet to be answered. To answer those questions, we shall analyse the effectiveness of lockdown and the risk of lockdown easing (either sifting or lifting lockdown) in the proposed project.
This research aims to analyse data in China, where the first lockdown against COVID-19 took place and gradually eased.
We will use cutting-edge statistical methods to analyse the spatial-temporal data and will examine the effectiveness of lockdown and the risk of lockdown easing.
Potential policy implications
Our data analysis will provide critical insights for policymakers on how to lift or soften lockdown and its possible threats. Also, the methods developed under this proposal can be applied to regional data in Australia and predicting the potential risk of lockdown easing. Our approach will be able to quantify the effectiveness of the hard lockdown policy to prevent the spread of coronavirus, even if the infection rate is very high locally. At country-level, a sort of this hard lockdown is currently employed, and our research will examine the effectiveness of the lockdown policy at regional or community level