Analyzing the anti-contagion policies of COVID-19 based on the epidemiological and economic coefficients

Shao, Z.; Sun, J.

In the early months of 2020, the regional propagation of COVID-19, a novel coronavirus, has evolved into a global public health emergency. Governments have not yet decided on an optimal plan to defend from COVID-19 due to lack of previous experience with such large-scale pandemics. Neither have researchers published a holistic approach of anticontagion policy analysis. In order to explore the middle ground of minimized negative effects on health and economy, this paper evaluated 1, 637 non-pharmaceutical anti-contagion policies from sub-regions in China, France, Italy, and South Korea. Inspired by previous research [1] [2], we utilized reduced-form approach and Computable General Equilibrium (CGE) model in the field of macroeconomics to calculate the effect of each individual policy on infection and GDP growth rates. These methods are based on filtered financial accounts (i.e. social accounting matrices) obtained from Global Trade Analysis Project (GTAP) database along with a published G-Cubed (G20) model, as well as the epidemiological data concerning the national conditions of each aforementioned country. We complete more than 1, 000 random samplings and iterations to average the policy coefficients of infection and GDP growth rates and minimize their standard errors. The major observation on the results is that an early implementation of travel ban for 2 weeks will effectively undermine the spread of COVID-19 at a low economic price. In addition, some policies (e.g. social distancing) require adjustment in their duration or range to improve their price-performance ratio (here, economic-health ratio). This form of hybrid policy analysis not only prevents further infectivity, but also ensures the stability of the global economy. © 2021 IEEE.