LOOKING BACK TO LOOK FORWARD: TRACKING ASEAN GOVERNMENTS’ RESPONSE TO COVID-19 IN THE PURSUIT OF POST-PANDEMIC RECOVERY

Abstract

ASEAN (Association of Southeast Asian Nation) member countries have the potential to continuously improve the region's efforts in containing the COVID-19 pandemic. The post-pandemic recovery plans have also been drafted and put in place. However, to ensure the success of these plans, policy responses of each member country towards the pandemic in the last two years need to be ascertained and mapped against the epidemic curve. This review aims to track these policy responses and to determine if there are any gross association between the responses and the number of daily new cases of COVID-19 within ASEAN. The data for this paper was sourced from the Oxford COVID-19 Government Response Tracker (OxCGRT) dataset. Twenty indicators and four indices of ASEAN governments’ responses between January 2020 to June 2021 were extracted and analysed descriptively. The results of this analysis were then compared against the epidemic curve of new cases within the same period. The findings show diversity in the responses among the ASEAN countries in managing the pandemic, based on the burden of disease. Indicators which seem to interrelate with changes in the epidemic curve are school and workplace closing, restrictions of gathering and movements both locally and internationally, and staying at home requirements. Several member countries have sustained income support, debt relief and public information campaigns, as well as testing, contact tracing and facial covering policies during the assessment period. Countries with high burden of disease seem to have higher and more uniformed scores of the Containment and Health Index, Stringency Index, and Government Response Index compared to countries with low burden of disease. These findings may be useful in the realization of the strategies in the ASEAN Comprehensive Recovery Framework (ACRF). Further statistical analysis can be done to obtain a more objective value of these data.