When to be vaccinated? What to consider? Modelling decision-making and time preference for COVID-19 vaccine through a conjoint experiment.

How do citizens choose COVID-19 vaccines, and when do they wish to be vaccinated? A choice-based conjoint experiment was conducted in Hong Kong to examine factors that shape citizens' preference toward COVID-19 vaccines and their time preference to be vaccinated, which is overlooked in extant literature. Results suggest people are most concerned about vaccines' efficacy and severe side-effects, and that cash incentives are not useful in enhancing vaccine appeal. The majority of respondents show low intention for immediate vaccination, and many of them want to delay their vaccination. Further analysis shows that their time preference is shaped more by respondent characteristics than vaccine attributes. In particular, confidence in the vaccine, trust in government, and working in high-risk professions are associated with earlier timing for vaccine uptake. Meanwhile, forced COVID testing would delay vaccination. The findings offer a novel view in understanding how people decide whether and when to receive new vaccines, which have pivotal implications for a head start of any mass vaccination programs.

Understanding the societal factors of vaccine acceptance and hesitancy: evidence from Hong Kong.

OBJECTIVES: Vaccination is considered to be an important public health strategy for controlling the COVID-19 pandemic. Besides subjective evaluations of the vaccine and the health threat, societal factors have been seen as crucial to vaccination decisions. Based on a socioecological perspective, this study examines the role of societal factors in COVID-19 vaccine hesitancy in Hong Kong. STUDY DESIGN AND METHOD: An online survey was fielded between 25 and 28 June 2021, collecting 2753 complete responses. Multinomial logistic regression was conducted to examine how subjective evaluations of the vaccine (summarised by the 5C model - Confidence, Collective responsibility, Constraints, Complacency and Calculation), threat perception, interpersonal influences and institutional trust contribute to explaining three types of decision - acceptant (vaccinated, scheduled or indicated 'Yes'), hesitant (unvaccinated and indicated 'Maybe' on intention) and resistant (unvaccinated and indicated 'No'). RESULTS: A total of 43.2%, 21.7% and 35.1% of respondents were acceptant, hesitant and resistant. Although the 5C model remained useful in explaining vaccination decisions, respondents were heavily influenced by the decisions of their family, although they were less influenced by friends. Second, respondents tended to accept the vaccine when they had a weaker perception that the act is supportive of the government and were less resistant if they had stronger institutional trust. CONCLUSION: Under the low-incidence and low-trust environment such as Hong Kong, vaccination decisions are heavily influenced by family's decision and the perception of vaccination as socially and politically desirable. Our findings highlight the importance of a nuanced conception of interpersonal and political influence towards vaccine acceptance/hesitancy.

Pandemic vulnerability, policy feedback and support for immigration: Evidence from Asia.

Past studies have shown that disease threat increases people's hostility towards immigrants. However, in our survey (N = 9571) conducted in five advanced Asian economies during the outbreak of COVID-19, we found that COVID-19 vulnerability was positively associated with support for immigration. Drawing on insight from policy feedback theories, we propose that the positive association is caused by the presence of widespread border crossing restrictions, which have changed the meaning and cost implications of COVID-19. As the outbreak expands, the pandemic has become not just a threat to people's health but also a barrier to globalization. Consequently, people who are worried about the disease may see globalization processes, including migration, as signs of pandemic relief. We find supportive evidence in our analysis. First, the positive association between COVID-19 vulnerability and support for immigration is more salient among respondents who considered restrictions on international travel to be stringent. Second, the positive association between COVID-19 vulnerability and immigration attitude was mediated by perceived economic threat from the pandemic and contribution by immigrants towards the containment of the pandemic. These findings suggest that disease control measures adopted at the global level may alter certain widely accepted effects of disease threat on immigration attitudes.

A tale of two city-states: A comparison of the state-led vs civil society-led responses to COVID-19 in Singapore and Hong Kong.

The East Asian experience in tackling COVID-19 has been highly praised, but this high-level generalisation neglects variation in pandemic response measures adopted across countries as well as the socio-political factors that shaped them. This paper compares the early pandemic response in Singapore and Hong Kong, two Asian city-states of similar sizes, a shared history of SARS, and advanced medical systems. Although both were able to contain the virus, they did so using two very different approaches. Drawing upon data from a cross-national, probability sample Internet survey conducted in May 2020 as well as media and mobility data, we argue that the different approaches were the result of the relative strength of civil society vs. the state at the outset of the outbreak. In protest-ridden Hong Kong, low governmental trust bolstered civil society, which focused on self-mobilisation and community mutual-help. In Singapore, a state-led response model that marginalised civil society brought early success but failed to stem an outbreak among its segregated migrant population. Our findings show that an active civil society is pivotal to effective outbreak response and that trust in government may not have been as important as a factor in these contexts.

Erratum: Tang, G., et al. Politically Motivated Internet Addiction: Relationships among Online Information Exposure, Internet Addiction, FOMO, Psychological Well-being, and Radicalism in Massive Political Turbulence. Int. J. Environ. Res. Public Health 2020, 17, 633.

Due to an error during the editorial process, the article published was not the finalized one [...].

Politically Motivated Internet Addiction: Relationships among Online Information Exposure, Internet Addiction, FOMO, Psychological Well-being, and Radicalism in Massive Political Turbulence.

This research examines the mediating role of the tendency for Internet addiction, fear of missing out (FOMO), and psychological well-being in the relationship between online exposure to movement-related information and support for radical actions. A questionnaire survey that targets tertiary students was conducted during the Anti-Extradition Law Amendment Bill (Anti-ELAB) Movement (N = 290). The findings reveal the mediating effect of Internet addiction and depression as the main relationship. These findings enrich the literature of political communication by addressing the political impact of Internet use beyond digital architecture. From the perspective of psychology, this research echoes the literature that concerns depression symptoms driven by a protest environment. Radical political attitudes driven by depression during protests should also be concerned based on the findings of this survey.

Towards a Physiological Scale of Vocal Fold Agent-Based Models of Surgical Injury and Repair: Sensitivity Analysis, Calibration and Verification.

Agent based models (ABM) were developed to numerically simulate the biological response to surgical vocal fold injury and repair at the physiological level. This study aimed to improve the representation of existing ABM through a combination of empirical and computational experiments. Empirical data of vocal fold cell populations including neutrophils, macrophages and fibroblasts were obtained using flow cytometry up to four weeks following surgical injury. Random Forests were used as a sensitivity analysis method to identify model parameters that were most influential to ABM outputs. Statistical Parameter Optimization Tool for Python was used to calibrate those parameter values to match the ABM-simulation data with the corresponding empirical data from Day 1 to Day 5 following surgery. Model performance was evaluated by verifying if the empirical data fell within the 95% confidence intervals of ABM outputs of cell quantities at Day 7, Week 2 and Week 4. For Day 7, all empirical data were within the ABM output ranges. The trends of ABM-simulated cell populations were also qualitatively comparable to those of the empirical data beyond Day 7. Exact values, however, fell outside of the 95% statistical confidence intervals. Parameters related to fibroblast proliferation were indicative to the ABM-simulation of fibroblast dynamics in final stages of wound healing.