Public acceptability of COVID-19 control measures in Singapore, Hong Kong, and Malaysia: A cross-sectional survey

Public acceptance of COVID-19 control measures and associated factors during Omicron-dominant period in China: a cross-sectional survey

OBJECTIVES

This study aims to evaluate the public acceptance of coronavirus disease 2019 (COVID-19) control measures during the Omicron-dominant period and its associated factors.

METHODS

A cross-sectional design was conducted and 1391 study participants were openly recruited to participate in the questionnaire survey. Logistic regression model was performed to assess the association between the public acceptance and potential factors more specifically.

RESULTS

By August 26, 2022, 58.9% of the study participants were less acceptive of the control measures while 41.1% expressed higher acceptance. Factors associated with lower acceptance included young age, such as < 18 (OR = 8.251, 95% CI: 2.009 to 33.889) and 18-29 (OR = 2.349, 95% CI: 1.564 to 3.529), and household per capita monthly income lower than 5000 yuan (OR = 1.512, 95% CI: 1.085 to 2.105). Furthermore, individuals who perceived that the case fatality rate (CFR) of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) was very low (OR = 6.010, 95% CI: 2.475 to 14.595) and that the restrictions could be eased once the CFR dropped to 2-3 times of the influenza (OR = 2.792, 95% CI: 1.939 to 4.023) showed greater oppositional attitudes. Likewise, respondents who were dissatisfied with control measures (OR = 9.639, 95% CI: 4.425 to 20.998) or preferred fully relaxation as soon as possible (OR = 13.571, 95% CI: 7.751 to 23.758) had even lower acceptability. By contrast, rural residents (OR = 0.683, 95% CI: 0.473 to 0.987), students (OR = 0.510, 95% CI: 0.276 to 0.941), public (OR = 0.417, 95% CI: 0.240 to 0.727) and private (OR = 0.562, 95% CI: 0.320 to 0.986) employees, and vaccinated participants (OR = 0.393, 95% CI: 0.204 to 0.756) were more compliant with control measures.

CONCLUSION

More than half of the Chinese public were less supportive of COVID-19 control measures during Omicron-dominant period, which varied based on their different demographic characteristics, cognition and overall attitude towards SARS-CoV-2 infection. Control measures that struck a balance between public safety and individual freedom would be more acceptable during the pandemic.

Screening Hesitancy of a Universal Voluntary-based Rapid Antigen Test for coronavirus disease 2019 (COVID-19) During Omicron Wave in Hong Kong

BACKGROUND

The Hong Kong government distributed rapid antigen test (RAT) kits to households across the city and called for a universal voluntary testing exercise for three consecutive days during the Omicron wave to identify infected persons early for quarantine and disrupt transmission chains in the community. We conducted a survey to evaluate the participation rates and explore the determinants of voluntary RAT adoption and hesitancy.

METHODS

This cross-sectional survey was conducted through computer-assisted telephone interviews from 19 May to 16 June 2022 using an overlapping dual-frame telephone number sampling design. Information on willingness to adopt voluntary RAT, four themes of personal qualities, attitudes toward the government's health policies, incentives to motivate RAT adoption, and personal sociodemographic factors were collected. Logistic regression analysis was used to examine the factors associated with RAT adoption.

RESULTS

Of the 1010 participants, 490 successfully responded to the fixed-line and 520 to the mobile phone survey, with response rates of 1.42% and 1.63% and screen hesitancy rates of 36.1% and 39.3%, respectively. Participants of adoption RAT were those aged 30-49 years, with high perceived COVID-19 infection severity, ≥ 3 doses of COVID-19 vaccination, and more agreement with the health policies on material resources and quarantine orders. Individuals who were less risk seeking and more altruistic reported a higher adoption of voluntary RAT.

CONCLUSIONS

Understanding the willingness to participate in a voluntary universal testing programme might shed light on effective ways to minimise screening hesitancy in future public health strategies and campaigns.

The efficacy of health experts' communication in inducing support for COVID-19 measures and effect on trustworthiness: A survey in Hong Kong

To control the spread of COVID-19, governments may implement freedoms-infringing health measures. Therefore, citizens' support for these measures is important. This study investigates: (1) whether health experts' communication induces support for COVID-19 measures, and (2) whether health experts' agreeing or disagreeing with government directives affects their trustworthiness. A cross-sectional online questionnaire was completed by 1072 adults in the Hong Kong general population between May 26 and June 3, 2021. Three COVID-19 measures were examined: contact-tracing mobile application, restriction-testing, and ban of public assembly. For each, participants were randomly assigned to three groups to view, respectively: vignettes with a neutral government announcement only; vignettes with a government announcement and a health expert's quote supporting the government's decision; and vignettes with a government announcement and a health expert's quote disagreeing with the government's decision. The result shows that positive health experts' communication increased the support for banning public assembly; no effects were found for the support for contact-tracing mobile applications and restriction testing. Participants who only viewed health experts disagreeing with the government had higher trust in health experts relative to participants who viewed health experts agreeing with the government at least once. The results render doubtful the strategy that health experts can be involved for garnering support for unpopular health measures without jeopardizing public trust in them.

A network analysis and support vector regression approaches for visualising and predicting the COVID-19 outbreak in Malaysia

This study aims to (1) correlate and visualise the Coronavirus disease 19 (COVID-19) pandemic spread via Spearman rank coefficients of network analysis (NA) and (2) predict the cumulative number of COVID-19 confirmed and death cases via support vector regression (SVR) based on COVID-19 dataset in Malaysia between July 2020 to June 2021. The NA indicated increasing connectivity between different states throughout the time frame, revealing the most complex network of COVID-19 transmission in the second quarter of 2021. The SVR model predicted future COVID-19 cases and deaths in Malaysia in the second half of 2021. The study demonstrated that the NA and SVR could provide relatively simple yet valuable artificial intelligence techniques for visualising the degree of connectivity and predicting pandemic risk based on confirmed COVID-19 cases and deaths. The Malaysian health authorities used the NA and SVR model results for preventive measures in highly populated states.