An evaluation of community satisfaction with the government's COVID-19 pandemic response in Aceh, Indonesia

Abstract

Countries around the world are still struggling due to the COVID-19 pandemic. No exception with Indonesia, a developing country with the highest mortality rate and the lowest number of tests in Asia. Located in the northernmost, Aceh is one of the poorest provinces with a history of long-term conflict is not in the best condition to face a pandemic. This study's objective is to assess the local government's performance in responding to this pandemic according to the Acehnese community's level of satisfaction. Additionally, this study proposes a priority list for the local government to follow up on. A total of 529 respondents were collected within a week by the criteria of having internet access, being literate, and using WhatsApp messenger. The results show that the Acehnese are dissatisfied with the local government's performance in all districts or cities and at all stages, which include: anticipation, early detection, containment, control and mitigation, and elimination. Meanwhile, the top five priority recommendations are: conducting more rapid test and COVID-19 test; providing more test tools; performing detection; and inhibiting spread. These findings lead to many interpretations: lower trust towards the government, a poor health system, and potential influence on the political output. While vaccines are now being distributed in Aceh, the main focus is still to minimize spread and heal the sick. Looking at these results, the Aceh provincial government needs to work harder to improve both its performance and reputation with the Acehnese people.

An analysis of COVID-19 information sources

“…However, relatively higher than the USA (47.0%) and the UK (46.0%) [ 34 ]. Similarly, a study conducted in Indonesia reported lower satisfaction of communities with the local government's performances, which include: anticipation, early detection, containment, control and mitigation, and elimination [ 35 ].…”

Consumers’ Perspectives and Behaviors towards Corporate Social Responsibility—A Cross-Cultural Study

“…Indonesia, a country with the fourth highest population, is likely to be severely affected by the pandemic [20]. In November 2020, the death rate from COVID-19 in Indonesia was the highest in Asia (8% in 2020) [21]. On 22 December 2021, Indonesia recorded 4,261,000 total cases, 144,034 total deaths, and 15,340 total cases per million people, 519 total deaths/million of the population (https://www.worldometers.info/coronavirus/, accessed on 22 December 2021).…”

Research Progress and Improvement Ideas of Anti-Epidemic Resilience in China’s Urban Communities

“…To identify key CEPC factors, some scholars have studied the quantitative or qualitative relationship between influencing factors and the capacity of community resilience. For example, through Grounded Theory, identifying the factors as a result of which urban residents fail to respond to the governance of the community epidemic in a timely manner and the mechanism of action between them [ 33 ], or recognizing the influencing factors (political, economic, socio-cultural, infrastructure and human health) of community epidemic recovery [ 34 ]; validating the relationship model between community awareness, community resilience and mental health through Structural Equation Modeling [ 35 ]; using the Pearson Correlation Coefficient to characterize the correlation between the number of confirmed cases of COVID-19 in Wuhan and socioeconomic factors such as community characteristics and distance variables [ 36 ]; the impact of the level of urban governance on CEPC and the mental health risk of residents is analyzed by Ordinary Least Squares [ 37 , 38 , 39 ]; using Multiple Linear Regression to analyze the main influencing factors and influence degree of community resilience during the epidemic [ 5 ]; establishing a Relative Importance Matrix to analyze the relationship between community residents’ satisfaction and local government performance during the COVID-19 epidemic [ 40 ]; using Sensitivity Analysis to evaluate the impact of key influencing factors on the epidemic contribution of disaster response capability [ 41 ].…”