The COVID-19 epidemic is the most significant global health disaster of this century and the greatest challenge to humanity since World War II. One of the most important research issues is to determine the effectiveness of measures implemented worldwide to control the spread of the corona virus. A dynamic simulated Autoregressive-Distributed Lag (ARDL) approach was adopted to analyze the policy response to COVID-19 in the ASEAN region using data from February 1, 2020, to November 8, 2021. The results of unit root concluded that the dependent variable is integrated of order one while the independent variables are stationarized at the level or first difference, and the use of a dynamic simulated ARDL technique is appropriate for this paper. The outcomes of the dynamic simulated ARDL model explored that government economic support and debt/contract relief for poor families is substantially important in the fight against COVID-19. The study also explored that closing schools and workplaces, restrictions on gatherings, cancellation of public events, stay at home, closing public transport, restrictions on domestic and international travel are necessary to reduce the spread of COVID-19. Finally, this study explored that public awareness campaigns, testing policy and social distancing significantly decrease the spread of COVID-19. Policy implications such as economic support from the government to help poor families, closing schools and public gatherings during the pandemic, public awareness among the masses, and testing policies must be adopted to reduce the spread of COVID-19. Moreover, the reduction in mortality shows that immunization could be a possible new strategy to combat COVID-19, but the factors responsible for the acceptability of the vaccine must be addressed immediately through public health policies.
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 27 January 2023.
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