Search

The informational domain related to COVID-19 reflects the degree of uncertainty and pace of evolution of the pandemic. This places a burden on peoples' searches for information to guide their choices, importantly including for COVID-19 vaccines. Thus, it is important for health communications that support vaccination campaigns to attenuate vaccine hesitancy to be accessible, including in terms of readability, and adapted to the evolving pandemic. This paper aims to understand internet searches on COVID-19 vaccination, specifically the mix of sources and readability of the sources over a two-year period (2021–2023) in Singapore, Hong Kong, and the Philippines, for search results in English, as English is a main language for each of these locations. The sources accessed through online searches in June 2021 and May 2023 were categorized by type of source and whether they were from one of the focal locations or elsewhere. The readability of information from web-search results was assessed using a set of readability tests (Flesch–Kincaid Reading Ease, Flesch–Kincaid Grade Level, Gunning Fog Index, Coleman–Liau Index, and Simple Measure of Gobbledygook Grade level). Over the two-year period there was an increase in government sources and reduction in mass media sources with distinct local patterns. Local government sources increased in Singapore whereas foreign government and multi-lateral organization sources increased in Hong Kong, with the Philippines being an intermediate pattern. In contrast to the changing mix of sources, the readability tests indicate a low proportion of URLs scoring within recommended readability thresholds across locations and types of sources over the two years. Information on COVID-19 vaccine development and deployment is an important part of health communications that includes internet search. The paper contributes to understanding health communications during a pandemic, including mix of local and non-local sources and contingency on local social and health context. [ABSTRACT FROM AUTHOR]

In response to the COVID-19 pandemic, modular construction has been adopted for rapidly delivering healthcare facilities, but few have systematically explored the impacts of the pandemic and the contributions of modular construction. This paper aims to evaluate modular construction for delivering healthcare facilities in response to COVID-19, through the exploration of the challenges, strategies, and performance of using modular construction for emergency healthcare building project delivery. The study was conducted using 12 real-life healthcare building projects in Hong Kong with both within- and cross-case analyses. The results of the within-case study reveal critical challenges such as tight program but limited resources available and the corresponding strategies such as implementation of smart technologies. The results of the cross-case analysis indicate 106% improved time efficiency and 203% enhanced cost efficiency of using modular construction compared with conventional practices. Based on the multi-case studies, the paper develops an innovative framework which illustrates the roles of stakeholders, goals, engineering challenges, and management principles of using modular construction. Practically, the paper should assist both policymakers and industry stakeholders in addressing the critical challenges of delivering healthcare facilities under COVID-19 in an efficient and collaborative manner. Theoretically, it should set an exemplar of linking the building construction industry with emergency management and healthcare service systems to facilitate efficient response to pandemics. [ABSTRACT FROM AUTHOR]

The existing literature primarily examined the impact of unexpected events on the stock market at a single scale, posing the challenge of a lack of multiscale analysis. This paper investigates the impact of COVID-19 on stock markets (China, the U.S., and Hong Kong) from a multiscale perspective using an improved ensemble empirical mode decomposition (EEMD)-based event analysis method. First, the stock price series is decomposed into several independent intrinsic mode functions (IMFs) and a residue. Second, a novel composition method is proposed to reconstruct the IMFs into three components: high-frequency, low-frequency, and long-term trend. We find that the composition of low-frequency and long-term trend components is dominant, which is used to estimate the strength of COVID-19 impact on the stock markets. In addition, the outbreak of COVID-19 significantly increased the intensity of short-term fluctuations in stock prices. Finally, the high-frequency component is analyzed to capture the volatility spillover effects among the three stock markets by the BEKK(Baba-Engle-Kraft-Kroner)-GARCH model. The results show that before the outbreak, there are two-way volatility spillovers between any two of the three markets. After the outbreak, there is no spillover effect between China and Hong Kong, and Hong Kong has no spillover effect on the U.S. However, volatility in the U.S. market still has a significant spillover effect on the other two markets, implying that a mature market can absorb new information more quickly. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has caused unprecedented disruption to teaching and research in universities. This has prompted the publication of a considerable number of studies, frameworks, and guidelines on teaching adaptations. Less has been written on adaptations to empirical research projects, partly because such projects have been put on hold or redesigned entirely. This paper reflects on adaptations made, challenges encountered, and lessons learned while persisting with a qualitative study involving parents, teachers, tutors, and university academics during the second and third waves of the pandemic in Hong Kong in 2020. Specifically, we reflect on the reconsideration of research design and instruments, negotiation of different kinds of access to research sites and participants, optimization of existing data sources, streamlining of data collection approaches, and consideration of the mental well-being of both researchers and respondents. The paper includes lessons learned from the use of Zoom, WhatsApp Messenger, and phone calls as technological tools, and hashtag search on social media platforms such as Facebook and Instagram. Special consideration is given to the unexpected benefits of doing research during the pandemic and the convenience of using technology and adaptability approach. [ABSTRACT FROM AUTHOR]

COVID-19 spread dramatically across the world in the beginning of 2020. This paper presents a novel alert system that will detect abrupt changes in the COVID-19 or other pandemic incidence rate through the estimated time-varying reproduction number (Rt). We applied the system to detect abrupt changes in the COVID-19 pandemic incidence rates in thirteen world regions with eight in the US and five across the world. Subsequently, we also evaluated the system with the 2009 H1N1 pandemic in Hong Kong. Our system performs well in detecting both the abrupt increases and decreases. Users of the system can obtain accurate information on the changing trend of the pandemic to avoid being misled by low incidence numbers. The world may face other threatening pandemics in the future; therefore, it is crucial to have a reliable alert system to detect impending abrupt changes in the daily incidence rates. An added benefit of the system is its ability to detect the emergence of viral mutations, as different virus strains are likely to have different infection rates. [ABSTRACT FROM AUTHOR]

Digital contact-tracing systems have been widely implemented worldwide with different system designs and implementation policies for the purpose of tracking potentially exposed individuals. The use of a digital contact-tracing app in Hong Kong has been mandated for visiting certain premises by legislations. This paper reviewed the regulations promulgated specifically for the prevention and control of COVID-19 and identified those associated with the digital contact-tracing system. A comprehensive search in newspaper databases was performed to explore the enforcement of the mandated use of the digital contact-tracing app. The three facets of regulations in relation to digital contact tracing were examined: duty to disclose information, requirements and directions to businesses, and compulsory testing. The use of digital contact-tracing data for non-public health purposes was also reported. Our analyses showed that prosecution of non-use or the use of fraudulent digital contact-tracing apps was not limited to COVID-19-specific legislations. The flexible approach ensured the enforcement of the use of the digital contact-tracing app, but the judiciary's test must be passed in future cases. [ABSTRACT FROM AUTHOR]

Background: The new waves of COVID-19 outbreaks caused by the SARS-CoV-2 Omicron variant are developing rapidly and getting out of control around the world, especially in highly populated regions. The healthcare capacity (especially the testing resources, vaccination coverage, and hospital capacity) is becoming extremely insufficient as the demand will far exceed the supply. To address this time-critical issue, we need to answer a key question: How can we effectively infer the daily transmission risks in different districts using machine learning methods and thus lay out the corresponding resource prioritization strategies, so as to alleviate the impact of the Omicron outbreaks? Methods: We propose a computational method for future risk mapping and optimal resource allocation based on the quantitative characterization of spatiotemporal transmission patterns of the Omicron variant. We collect the publicly available data from the official website of the Hong Kong Special Administrative Region (HKSAR) Government and the study period in this paper is from December 27, 2021 to July 17, 2022 (including a period for future prediction). First, we construct the spatiotemporal transmission intensity matrices across different districts based on infection case records. With the constructed cross-district transmission matrices, we forecast the future risks of various locations daily by means of the Gaussian process. Finally, we develop a transmission-guided resource prioritization strategy that enables effective control of Omicron outbreaks under limited capacity. Results: We conduct a comprehensive investigation of risk mapping and resource allocation in Hong Kong, China. The maps of the district-level transmission risks clearly demonstrate the irregular and spatiotemporal varying patterns of the risks, making it difficult for the public health authority to foresee the outbreaks and plan the responses accordingly. With the guidance of the inferred transmission risks, the developed prioritization strategy enables the optimal testing resource allocation for integrative case management (including case detection, quarantine, and further treatment), i.e., with the 300,000 testing capacity per day; it could reduce the infection peak by 87.1% compared with the population-based allocation strategy (case number reduces from 20,860 to 2689) and by 24.2% compared with the case-based strategy (case number reduces from 3547 to 2689), significantly alleviating the burden of the healthcare system. Conclusions: Computationally characterizing spatiotemporal transmission patterns allows for the effective risk mapping and resource prioritization; such adaptive strategies are of critical importance in achieving timely outbreak control under insufficient capacity. The proposed method can help guide public-health responses not only to the Omicron outbreaks but also to the potential future outbreaks caused by other new variants. Moreover, the investigation conducted in Hong Kong, China provides useful suggestions on how to achieve effective disease control with insufficient capacity in other highly populated countries and regions. [ABSTRACT FROM AUTHOR]

Despite the various socio-demographic vulnerabilities of Hong Kong to the COVID-19 pandemic, the city has successfully managed four waves of local outbreaks, as shown by its comparatively low numbers of confirmed cases and deaths. In this paper, we identify and differentiate the unique characteristics of Hong Kong's COVID-19 outbreaks from those of other territories, and analyse the factors that shaped these characteristics. In particular, we examine four local demographic factors -- older age structure, high population density, poor housing conditions and a large migrant population -- which, according to current scientific evidence, would likely indicate that the city faces a relatively high risk of the significant spread of COVID-19.We analyse and explain how multiple policies related to border controls, social distancing, testing and tracing, partial lockdowns and housing management, as well as sustained community actions, helped to mitigate the effects of these significant disadvantages. [ABSTRACT FROM AUTHOR]

Background: The purpose of this paper is to describe the effects on preparation for sprinting performance in Hong Kong university-level athletes during the COVID-19 pandemic. Changes in training methods, and well-being of athletes due to COVID-19 pandemic were also investigated. Methods: Using Google Form, the study recall period was established during the closure of sports facilities in Hong Kong (2/2020-2/2021) during the COVID-19 pandemic. Physical state preparation (PSP), Mental state preparation (MSP), Nutritional preparation (NP), and Major changes in training methods (MTM) were analyzed. Results: The results demonstrated no significant mean difference between male and female athletes on the effects of COVID-19 regarding the PSP, MSP, NP, and MTM. However, both males and females were highly disrupted in relation to performance preparation. Conclusions: The pandemic affected physical performance, stress, and mental state, impacted on nutritional regimes, changed training locations and recovery strategies, and lowered training quantity and quality. In addition, athletes received less coaching, and had less accessibility to training equipment. Athletes and coaches should reflect on the effects of the COVID-19 pandemic to address personal training needs, while sports professionals need to carefully prepare themselves for sprinting performance, in relation to the current COVID-19 situation. [ABSTRACT FROM AUTHOR]

Online messaging app Telegram has increased in popularity in recent years surpassing Twitter and Snapchat by the number of active monthly users in late 2020. The messenger has also been crucial to protest movements in several countries in 2019-2020, including Belarus, Russia and Hong Kong. Yet, to date only few studies examined online activities on Telegram and none have analyzed the platform with regard to the protest mobilization. In the present study, we address the existing gap by examining Telegram-based activities related to the 2019 protests in Hong Kong. With this paper we aim to provide an example of methodological tools that can be used to study protest mobilization and coordination on Telegram. We also contribute to the research on computational text analysis in Cantonese—one of the low-resource Asian languages,—as well as to the scholarship on Hong Kong protests and research on social media-based protest mobilization in general. For that, we rely on the data collected through Telegram's API and a combination of network analysis and computational text analysis. We find that the Telegram-based network was cohesive ensuring efficient spread of protest-related information. Content spread through Telegram predominantly concerned discussions of future actions and protest-related on-site information (i.e., police presence in certain areas). We find that the Telegram network was dominated by different actors each month of the observation suggesting the absence of one single leader. Further, traditional protest leaders—those prominent during the 2014 Umbrella Movement,—such as media and civic organisations were less prominent in the network than local communities. Finally, we observe a cooldown in the level of Telegram activity after the enactment of the harsh National Security Law in July 2020. Further investigation is necessary to assess the persistence of this effect in a long-term perspective. [ABSTRACT FROM AUTHOR]

INTRODUCTION Tobacco use is associated with an increased risk of Coronavirus Disease 2019 (COVID-19) infection, severe COVID-19 outcomes requiring intensive care, and mortality. We investigated the perceived risk of and changes in cigarette, e-cigarette (EC) and heated tobacco product (HTP) use in relation to COVID-19 in Hong Kong adolescent tobacco users. METHODS We conducted semi-structured telephone interviews from January to April 2021 and in February 2022 on 40 adolescents (65% boys, Secondary school grades 2-6) who participated in our previous smoking surveys and were using cigarettes, ECs or HTPs before the first wave of the COVID-19 pandemic in January 2020. RESULTS Adolescents generally perceived higher risks of contracting and having more severe COVID-19 from using cigarettes than ECs/HTPs, but they had limited knowledge of COVID-19 risks from EC/HTP use, particularly. Both increased and reduced consumption were found in tobacco, with EC use being the less affected product. Changes also included switching to ECs for convenience and lower cost and shifting from smoking cigarettes outside to mainly at home or in hidden areas. COVID-related policies, fear of infection, non-COVID-related health concerns, less social opportunities and pocket money, and limited access to tobacco products were barriers to tobacco use. In contrast, greater freedom at home versus school and negative emotions due to social distancing were facilitators. Family/peer influence had mixed impacts. CONCLUSIONS Adolescent tobacco users perceived lower COVID risks associated with HTPs and ECs than cigarettes, and various changes in tobacco use were found amid the pandemic in Hong Kong. COVID-19 and related social changes may both facilitate or deter adolescent tobacco use. [ABSTRACT FROM AUTHOR]

INTRODUCTION Observational and experimental studies have suggested that messaging on smoking-related COVID-19 risk may promote smoking abstinence, but evidence from randomized clinical trials (RCTs) is lacking. METHODS This was a pragmatic RCT in Hong Kong, China, to compare the effectiveness of communicating smoking-related COVID-19 risk with generic cessation support on abstinence. Both groups received brief cessation advice at baseline. The intervention group received messaging on smoking-related COVID-19 risk and cessation support via instant messaging for three months (16 messages in total), which highlighted the increased risk of severe COVID-19 and deaths, and potentially higher risk of viral exposure (e.g. due to mask removal) for smokers. The control group received generic text messaging support for three months (16 messages). The primary outcomes were biochemically validated 7-day point prevalence abstinence (PPA) at 3 and 6 months. Intention to treat analyses was used. RESULTS Between 13 June and 30 October 2020, 1166 participants were randomly assigned to an intervention (n=583) or control (n=583) group. By intention-totreat, validated 7-day PPA did not significantly differ between the intervention and control groups at three months (9.6% and 11.8%, relative risk, RR=0.81; 95% CI: 0.58-1.13, p=0.22) or six months (9.3% and 11.7%, RR=0.79; 95% CI: 0.57-1.11, p=0.18). A higher perceived severity of COVID-19 in smokers at baseline was associated with a greater validated 7-day PPA at six months, and a marginally significant intervention effect on changes in perceived severity from baseline through 6 months was found (p for group x time interaction = 0.08). CONCLUSIONS Communicating smoking-related COVID-19 risk via instant messaging was not more effective in increasing smoking abstinence than generic cessation support. [ABSTRACT FROM AUTHOR]

INTRODUCTION Perceived risk of COVID-19 infection is associated with smoking behaviors, but the change in smoking across different settings are uncertain. We examined the associations of perceived increased susceptibility to COVID-19 due to smoking with change in smoking at home and on the streets. METHODS We analyzed data of 1120 current cigarette smokers aged >15 years from a population-based telephone survey in Hong Kong. Perceived increased susceptibility to COVID-19 due to smoking, change in smoking, intention to quit, and tobacco dependence were measured. We used Poisson regression with robust variance to estimate adjusted risk ratio (ARR) for associations, adjusting for sociodemographic characteristics, intention to quit, and time to first cigarette after waking. RESULTS More current smokers reduced smoking on the streets (46.1%; 95% CI: 42.8-50.0) than at home (8.7%; 95% CI: 7.0-10.8). Perceived increased susceptibility to COVID-19 due to smoking was associated with smoking reduction at home (ARR=3.29; 95% CI: 1.80-6.00, p<0.001) but not on the streets (ARR=1.13; 95% CI: 0.98-1.30, p=0.09). More smokers with stronger quit intention and lower tobacco dependence reduced smoking at home but not on the streets in those with high perceived increased susceptibility to COVID-19 due to smoking. CONCLUSIONS This is the first report showing that more cigarette smokers reduced smoking on the streets than at home, and the perceived increased susceptibility to COVID-19 due to smoking was only associated with smoking reduction at home but not on the streets. Improving smokers' awareness of the susceptibility to COVID-19 may be an effective strategy to reduce tobacco consumption and secondhand smoke exposure at home within the context of future respiratory pandemics. [ABSTRACT FROM AUTHOR]

As social inequalities during the COVID-19 pandemic have been recognised, emerging research showed that lesbian, gay and bisexual (LGB) people may be additionally affected during the pandemic. This paper adds to the understanding of the experiences of LGB people during the pandemic with a focus on Hong Kong, where issues of space significantly influence LGB people's lives in this city with high population density. As part of a larger community study of LGB lives in Hong Kong, COVID-19-related impact on 434 Chinese-speaking LGB people was explored. Data collection was conducted from 20 May to 30 June 2020. Inductive thematic analysis of the open-text response survey data found that the LGB participants described both negative and positive impacts brought by COVID-19. Such impacts could be dimensionalised into those related to personal space and privacy, romantic and sexual space, and community space. It was also found that the experiences of COVID-19 among LGB people in Hong Kong were intersectional, along the lines of living arrangement and relationship status. Such findings make unique contributions to the emerging literature. First, there needs to be a more nuanced understanding of sexual minority individuals' experiences during COVID-19 across cultural contexts. Second, COVID-19 was described as having brought positive impact in addition to its widely known negative impact. [ABSTRACT FROM AUTHOR]

INTRODUCTION How changes in smoking routine due to COVID-19 restrictions (e.g. refraining from smoking outdoors and stockpiling tobacco products) influence smoking behaviors remains understudied. We examined the associations of changes in smoking-related practices with quit attempts and smoking consumption in current smokers using a mixed-methods design. METHODS In a community-based telephone survey conducted between the second and third wave of the COVID-19 pandemic in Hong Kong, 659 smokers (87.1% male; 45.2% aged 40--59 years) were asked about quit attempts and changes in cigarette consumption and five smoking-related practices since the COVID-19 outbreak. Logistic regression was used to calculate adjusted odds ratio (AOR), adjusting for sex, age, education level, chronic disease status, heaviness of smoking (HSI), psychological distress (PHQ-4) and perceived danger of COVID-19. A subsample of 34 smokers provided qualitative data through semi-structured interviews for thematic analyses. RESULTS Favorable changes in smoking-related practices, including having avoided smoking on the street (prevalence: 58.9%) and reduced going out to buy cigarettes (33.5%), were associated with a quit attempt (AOR: 2.09 to 2.26; p<0.01) and smoking reduction (AOR: 1.76 to 4.97; p<0.05). Avoiding smoking with other smokers (50.5%) was associated with smoking reduction (AOR=1.76; p<0.05) but not quit attempt (AOR=1.26; p>0.05). Unfavorable changes, including having increased smoking at home (25.0%) and stockpiled tobacco products (19.6%), were associated with increased smoking (AOR: 2.84 to 6.20; p<0.05). Low HSI (0--2) was associated with favorable changes (p<0.01), while high HSI score (3--6) was associated with unfavorable changes (p<0.01). Qualitative interviews revealed a double-edged effect of staying at home on smoking consumption and that pandemic precautionary measures (e.g. mask-wearing) reduced outdoor smoking. CONCLUSIONS Amid the pandemic, favorable changes in smoking-related practices in smokers were mostly associated with quit attempts and smoking reduction, while unfavorable changes were associated with increased smoking. Smokers with higher nicotine dependence were more negatively impacted. [ABSTRACT FROM AUTHOR]

INTRODUCTION Changes in tobacco use since the COVID-19 outbreak differed by countries and little is known about changes in the use of specific tobacco products. METHODS We analyzed data from four cross-sectional telephone/online surveys from April to June 2020 to investigate such changes since the 1st and 2nd wave outbreaks (February to April 2020) in Hong Kong. The respondents were 1595 adults (83.2% male) who used tobacco before the COVID-19 outbreak from our previous intervention study and surveys. We investigated the changes in tobacco use, intention to quit and quit attempts during the outbreak. RESULTS About two-thirds (65.3%) of respondents reported no change in overall tobacco use, while 23.1% used less (including cessation) and 11.6% used more, resulting in a net decrease of 11.5 percentage points. A greater net decrease was observed for cigarettes (14.3% points) than heated tobacco products (HTPs, 3.3% points) and electronic cigarettes (e-cigarettes, 2.5% points). Decreased use was mainly due to the more extended stay at home (63.2%), health considerations (52.6%) and mask-wearing (47.4%), while increased use was for passing time (75.0%) and releasing stress (46.4%). Eight percent of cigarette, HTP and e-cigarette users reported a higher intention to quit since the pandemic outbreak. Nineteen percent of tobacco users (176/948) attempted to quit during the pandemic. Only 2.9% (46/1569) were abstinent at the time of the survey. CONCLUSIONS Overall tobacco use decreased after the first two waves of the COVID-19 outbreak in Hong Kong. A greater proportion of cigarette users decreased use than HTP and e-cigarette users. Given the different methods used in the four surveys, future studies should aim for a large and representative sample. [ABSTRACT FROM AUTHOR]

Background: Psychiatric patients are susceptible to adverse mental health outcome during COVID-19 pandemic, but its associated factors are understudied. This observational cross-sectional study aimed to comprehensively examine prevalence and correlates of psychological distress, in terms of depression, anxiety and post-traumatic-stress-disorder (PTSD)-like symptoms, among Chinese adult psychiatric outpatients amidst the peak of fifth COVID-19 wave in Hong-Kong. Methods: A total of 415 patients (comprising 246 patients with common-mental-disorders [CMD] and 169 with severe-mental-disorders [SMD]) and 399 demographically-matched controls without mental disorders were assessed with self-rated questionnaires between 28-March and 8-April-2022, encompassing illness profile, mental health symptoms, psychosocial measures (loneliness, resilience, coping styles) and COVID-19 related factors. Univariate and multivariable logistic regression analyses were conducted to determine variables associated with moderate-to-severe depressive, anxiety and PTSD-like symptoms among psychiatric patients. Results: Our results showed that CMD patients had the greatest psychological distress relative to SMD patients and controls. Approximately 40–55% CMD patients and 25% SMD patients exhibited moderate-to-severe depression, anxiety and PTSD-like symptoms. Multivariable regression analyses revealed that female gender, lower educational attainment, single marital status, being housewife, more severe insomnia, psychotic-like symptoms and cognitive complaints, self-harm behavior, lower resilience, avoidance coping, never contracting COVID-19 infection, greater fear of contagion, and longer exposure to pandemic-related information were independently associated with depression, anxiety and/or PTSD-like symptoms in psychiatric patients. Conclusions: Our results affirm increased vulnerability of psychiatric patients toward psychological distress during pandemic. An array of identified correlates facilitates early detection of high-risk psychiatric patients for targeted strategies to minimize pandemic-related negative psychological impact. [ABSTRACT FROM AUTHOR]

Rapid design and construction of mobile cabin hospitals (MCHs) have become imperative in the COVID-19 response. However, due to unique design specifications (e.g., parallel design and model pre-revision), collaboration in emergency construction projects (ECPs) like MCHs presents data security vulnerabilities, including a lack of traceability and transparency. These hazards invariably reduce design effectiveness, leading to undesirable rework and project delay. Blockchain technology is a potential solution to address the aforementioned security issues in ECPs because it offers immutable and traceable data storage. Nevertheless, directly implementing blockchain in ECPs is impractical, for the blockchain has a complex deployment process and provides limited functions supporting BIM-based design. Therefore, this paper develops a lightweight blockchain-as-a-service (LBaaS) prototype to enhance the ECPs design efficiency by securing and automating information exchange while eliminating the difficulties of deploying and using blockchain. This paper contributes three elements: (1) Security vulnerabilities of design in ECP are identified. Taking an MCH in Hong Kong as an example, this paper investigates its design process and determines two design characteristics and associated security flaws. (2) Key technologies to support easy deployment and usage of blockchain in ECPs are developed. New technical elements, including a Multi-to-One mapping (MtOM) kit for easy blockchain registration, an integrated workflow retaining existing design practices, and smart contracts for secure interaction with blockchain, are developed to support LBaaS functionality. (3) An LBaaS prototype is validated and evaluated. The prototype is illustrated and evaluated using design examples based on actual MCH project data. Results show that the LBaaS is a feasible and secure approach for ECPs collaboration. This paper deepens the understanding of data security issues in ECPs and offers technical guidance in establishing blockchain solutions. • Identified security vulnerabilities of BIM-based collaboration in emergency construction projects (ECPs). • Exploring the mechanism of integrating ECPs design with a lightweight blockchain-as-a-service (LBaaS). • Developed key technical elements to support functionalities of an LBaaS prototype. • Validated LBaaS prototype via three design examples from an actual mobile cabin hospital project. • Results show that the LBaaS is a practical solution for improving data security and ECP design efficiency. [ABSTRACT FROM AUTHOR]

Background: Psychiatric patients are susceptible to adverse mental health impacts during COVID-19, but complex interplays between psychopathology and pandemic-related variables remain elusive. This study aimed to investigate concomitant associations between psychopathological symptoms, psychological measures and COVID-19 related variables in Chinese psychiatric patients during the peak of fifth pandemic wave in Hong Kong. Methods: We employed network analysis to investigate inter-relationships among psychopathological symptoms (including depression, anxiety, post-traumatic stress disorder-like [PTSD-like] symptoms, insomnia, psychotic symptoms), cognitive complaints, health-related quality of life, loneliness, resilience and selected pandemic-related factors in 415 psychiatric outpatients between 28 March and 8 April, 2022. Network comparisons between genders, diagnosis (common mental disorders [CMD] vs. severe mental disorders [SMD]), and history of contracting COVID-19 at fifth wave were performed as exploratory analyses. Results: Our results showed that anxiety represented the most central node in the network, as indicated by its highest node strength and expected influence, followed by depression and quality of life. Three comparatively strong connections between COVID-19 and psychopathological variables were observed including: fear of contagion and PTSD-like symptoms, COVID-19 stressor burden and PTSD-like symptoms, and COVID-19 stressor burden and insomnia. Network comparison tests revealed significant network structural difference between participants with history of contracting COVID-19 and those without, but showed no significant difference between genders as well as between CMD and SMD patients. Conclusions: Our findings suggest the pivotal role of anxiety in psychopathology network of psychiatric patients amidst COVID-19. Pandemic-related variables are critically associated with trauma/stress and insomnia symptoms. Future research is required to elucidate potential network structural changes between pandemic and post-COVID periods. [ABSTRACT FROM AUTHOR]

Introduction: Previous coronavirus, 2019 (COVID-19) research has applied network analysis to examine relationships between psychopathological symptoms but rarely extended to potential risk and protective factors or the influence of COVID-19 infection history. This study examined complex interrelationships between psychopathological symptoms, COVID-19-related stressors, perceived social support, and COVID-19 infection history among Chinese university/college students during the peak of fifth pandemic wave using a network analysis approach. Methods: A Least Absolute Shrinkage and Selection Operator-regularized partial correlation network using Gaussian graphical model was constructed in 1,395 Chinese university/college students in Hong Kong who completed a survey between 15 March and 3 April, 2022. Depressive, anxiety, and acute/traumatic stress symptoms were measured by Patient Health Questionnaire-9, Generalized Anxiety Disorder-7, and Impact of Event Scale-6, respectively. COVID-19-related stressors and perceived social support were measured. Network differences by COVID-19 infection history (COVID-network vs. no_COVIDnetwork) and network communities were examined. Results: Our results showed that the most influential nodes were depressed mood, uncontrollable worries, and uncontrollable thoughts about COVID-19. The main bridging symptoms were concentration problems and psychomotor problems. The COVID-network, comprising participants with a history of COVID-19 infection only, was significantly stronger than the no_COVIDnetwork. Perceived social support and stress from conflicts with family/friends formed a unique community with negative cognition and suicidal idea in the COVID-network only. Conclusion: Our findings indicate that specific interventions targeting interpersonal conflicts and concentration problems as well as facilitating stress buffering effects of social support may represent effective strategies to reduce psychological distress in university/college students during COVID-19 and should be considered for future pandemic preparedness. [ABSTRACT FROM AUTHOR]

The reduction of social interactions through non-pharmaceutical interventions (NPIs) has been shown to effectively curb COVID-19 transmission. However, these control measures were often accompanied by changes in people's daily routines and constraints on their activity space, which could lead to mental distress (i.e., anxiety and depression). This study examined the interplay among individuals' anxiety, depression, daily activities, and perceptions of COVID-19 and neighborhood cohesion. Taking Hong Kong as an example, an online survey (N = 376) was conducted to collect data from participants between March 14 to May 11, 2022. The data include respondents' self-reported anxiety and depressive symptoms, daily activities (e.g., smartphone use), perceptions of COVID-19 (e.g., the possibility of infecting COVID-19), and perceptions of neighborhood cohesion. Using network analysis, we found that excessive smartphone use, life disturbance by COVID-19, and a community with people getting along well with each other were significant factors associated with participants' anxiety and depression. Using critical path analysis, we observed that NPIs reduced human mobility, led to delayed bedtime, and increased smartphone use, which were associated with participants' mental distress. We also found that NPIs and COVID-19 were associated with people's perceptions of infection and the severity of COVID-19 and human mobility flexibility, which may further lead to mental distress. Our results also demonstrated that people with high education levels were vulnerable. These results provided important insights for designing appropriate interventions without generating deleterious impacts on people's mental health in the future. [ABSTRACT FROM AUTHOR]

Understanding the economic impact of COVID-19 is the foundation for formulating targeted policies promoting economic recovery. This study uses panel data of the county economy in the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) from 2017 to 2022. Firstly, the evolution characteristics of the economic structure in the GBA were analyzed using the standard deviation ellipse, geographical concentration, and spatial autocorrelation methods. Then, we revealed the changes in various economic indicators. Finally, a spatial Durbin model was constructed to study the factors affecting economic growth and spatial spillover effects in different periods. The results reveal that the economic distribution in the GBA presents a "core–edge" structure. The FDI, consumption, and exports of the Greater Bay Area fluctuate greatly, while investment growth is relatively stable. There is a significant spatial spillover effect in the county economy of the GBA. Investment, consumption, exports, labor, and innovation all have significant positive effects on economic growth, with investment having the greatest impact, while FDI has a significant negative impact. The impact of COVID-19 on the economy of the GBA is mainly reflected in the weakening of spatial spillovers, the strengthening of economic agglomeration, the decline in factor growth, and the change in the driving effect of factors on the economy. These findings can provide a reference for formulating targeted economic development policies. [ABSTRACT FROM AUTHOR]

Although the COVID-19 pandemic has caused many problems for university students, there are several research gaps in the study of psychological well-being of Hong Kong university students. First, few studies have examined different ecological correlates of mental health in a single study. Second, few studies have used both psychological morbidity and positive well-being as indicators of mental health. Third, we know little about the relationships between university students’ perceived need satisfaction, difficulties, service utilization, and their mental health. Hence, we conducted a study (N  =  1,020 university students) in the later stage of the COVID-19 pandemic in Hong Kong. For mental health, we included measures of negative mental health (psychological morbidity) and positive mental health. We addressed several research questions in this study: (1) what is the mental health status of Hong Kong university students? (2) what is the relationship between COVID-19 stress and student mental health? (3) what are the intrapersonal correlates of student mental health? (4) are interpersonal factors related to student mental health? (5) are need satisfaction, difficulties encountered, and service utilization related to students’ mental health? (6) are there gender differences in the effects of correlates in different ecological systems? Analyses using structural equation modeling showed several observations. First, the prevalence of mental health symptoms among university students was alarming. Second, COVID-19 related socio-economic stress positively predicted psychological morbidity but negatively predicted well-being. Third, beliefs about adversity, resilience, and emotional competence predicted mental health. Fourth, family functioning was related to psychological morbidity negatively but connected with wellbeing positively. Fifth, while need satisfaction predicted psychological morbidity negatively, difficulties encountered showed the opposite direction. Besides, the perceived usefulness of university services positively predicted mental health. Finally, there were no gender differences in the effects of different predictors. The present findings enable public health researchers to formulate theoretical models on different ecological determinants of university students’ mental health under the pandemic. For public health practitioners, the study highlights the importance of reducing COVID-19 associated stress, strengthening internal and external developmental assets, and meeting the psychosocial needs of university students as strategies to promote their mental health under the pandemic. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has had a distinctive impact on Hong Kong, especially given the city's prior experience with the SARS outbreak. The resulting psychological distress has been exacerbated by Hong Kong's extreme density and compactness, which places residents in proximity on the streets searching for outdoor activities. Streets are a precious source of space for social interactions, but, unfortunately, the pandemic has forced them to empty, leading to increased distress and challenging the psychological well-being of the urban population. In this study, we explore street vibrancy patterns in terms of outdoor activities, here addressed through a decision-making psychological perspective as volitional behaviors determined by psychological factors and essential for well-being, in one of the densest neighborhoods in Hong Kong. We statistically analyzed behavioral monitoring data in relation to spatial and morphological characteristics of their environments under COVID-19 psychological distress. The results highlighted the relevance of specific parcels of the streets acting as clusters and vibrancy initiators, stressing their significance in terms of affective and cognitive inputs determining context-based outdoor activities. The decision-making psychological perspective adopted here to address outdoor activities has relevant implications for design and planning strategies for post-pandemic scenarios, for psychological well-being, and for the future of urban density. [ABSTRACT FROM AUTHOR]

Background: The COVID-19 pandemic has had a significant impact on individuals' social lives, mental health status, and meaning in life (MIL). Globally, the use of different types of digital media has become a proxy for pre-COVID social lives for many people. This study investigated gender differences in the relationship between use of digital media, mental health status and MIL, during COVID-19 in Hong Kong. Methods: This cross-sectional study surveyed 1,488 young people recruited via city-wide random sampling in 2021. Respondents completed a phone survey on digital media use, Patient Health Questionnaire (PHQ-2), Generalized Anxiety Disorder (GAD-2), COVID-19 impact, meaning in life, and demographics. Gender differences in MIL were tested with an independent sample t-test. Gender-specific multiple linear regression models tested associations between MIL and explanatory variables of age, educational level, history of diagnosis, digital media use, and mental health status. Results: There was a significant gender difference in MIL (males (M = 12.90, SD = 4.12); females (M = 13.45, SD = 3.96); t (1485) = -2.656, p =.008). For males, all variables significantly associated to MIL (F (9, 759) = 15.731, p <.000, R2 =.157). However, for females, while the overall model for MIL was significant (F (9, 709) = 12.105, p <.001, R2 =.133), the only significant associated variable was mental health status. Conclusion: Females had significantly better MIL under COVID-19 than males. Digital media use contributed to MIL in males but not females, and there were gender-specific associated factors of MIL. [ABSTRACT FROM AUTHOR]

This article critically examines the experience of Hong Kong (HK) with the COVID-19 pandemic and highlights the urgent need for effective public health responses in an aging society. As one of the world's fastest aging societies, Hong Kong's vulnerability to the consequences of pandemics is particularly pronounced due to low birth rates and high life expectancies. The city has experienced multiple waves of the COVID-19 virus, with the fifth wave causing some of the highest mortality rates in the world. However, through continuous learning and adaptation, HK's public health response has evolved to combat the crisis effectively. The discussion aims to highlight the importance of drawing from both positive and negative lessons from past epidemics and the critical role of public health systems in ensuring the well-being of older adults and the wider community. It emphasizes the need for sustained efforts to maintain and strengthen public health systems to tackle the ongoing and future public health challenges in an aging society. [ABSTRACT FROM AUTHOR]

Under COVID‐19 outbreak, retail operations are seriously threatened. There are lots of cases in which physical stores basically have to stop operating. This creates problems to the firm, its employees, and consumers. Recently, Timberland in Hong Kong and various other brands such as Joyce Boutiques and The North Face have established the "WhatsApp Shopping Service Operation" (WSO) in which consumers can shop by using the well‐established communication tool "WhatsApp." Salespeople in stores provide services via WhatsApp to assist the consumers without them having to visit the stores. We collect primary data from real‐world cases and theoretically explore WSO. We build a standard consumer utility based model to derive the firm's optimal pricing and employment decisions under different cases. We evaluate the impacts of COVID‐19 and values of WSO implementation from the "Worker‐Consumer‐Company" (WCC) welfare perspective. Our results interestingly imply that WSO is superior to the traditional online channel in terms of keeping business under the pandemic; meanwhile, implementing WSO can help stimulate demand in the physical store under COVID‐19. However, whether WSO is effective to help increase the firm's profit and WCC welfare depends on both consumer type' distribution and consumers' fear of infection. When consumers' fear of infection is very polarized (i.e., extremely low or high), WSO is not recommended. We further propose that the government's subsidy for WSO implementation could be an effective way to help the firm improve its profit and WCC welfare. We also check the robustness of our study by extending the model to consider endogenous consumer type, endogenous service level, and WCC‐welfare‐oriented firm. [ABSTRACT FROM AUTHOR]

This study examined the latent structure of the broad range of complex neuropsychiatric morbidities occurring 1 year after COVID-19 infection. As part of the CU-COVID19 study, 248 (response rate=39.3%) of 631 adults hospitalized for COVID-19 infection in Hong Kong completed an online survey between March-2021 and January-2022. Disorder prevalence was compared against a random non-infected household sample (n=1834). 248 surveys were received on average 321 days post-infection (Mean age: 48.9, 54% female, moderate/severe/critical infection: 58.2%). 32.4% were screened to have at least one mental disorder, 78.7% of whom had concurrent fatigue/subjective cognitive impairment (SCI). Only PTSD (19.1%) was significantly more common than control (14%, p=0.047). Latent profile analysis classified individuals into P1 (12·4%)-no current neuropsychiatric morbidities, P2 (23.1%)-SCI/fatigue, P3 (45.2%)-anxiety/PTSD, P4 (19.3%)-depression. SCI and fatigue pervaded in all profiles (P2-4) with neuropsychiatric morbidities one-year post-infection. PTSD, anxiety and depressive symptoms were most important in differentiating P2-4. Past mental health and P4 independently predicted functional impairment. Neuropsychiatric morbidity was associated with past mental health, reduced resilience, financial problems, but not COVID-19 severity. Their confluence with depressive and anxiety symptoms predicted impairment and are associated with psychological and environmental factors. [ABSTRACT FROM AUTHOR]

Since the beginning of 2022, the Hong Kong government has imposed strict social distancing measures and changed its stance on various regional policies with the aim to contain the so-called ‘fifth wave’ of COVID-19. In these pandemic and ‘infodemic’ times filled with uncertainty and fear, Hong Kong netizens used local online discussion forums as a resource to establish an innovative form of ‘helping network.’ This study is based on 230 posts from a popular local online discussion forum ‘LIHKG’ in February 2022 when the pandemic was regarded as most critical by the Department of Health. Speech Acts theoretic approach was adopted to explore how forum users employed speech acts to perform various communicative practices such as expressing concerns, asking for information, and engaging with others in a CMC environment amid a global health crisis. Representatives were found to be the most dominant text-based speech acts, followed by directives, expressives and commissives. Speech acts provide forum users a context in which emoji usage occurs. Forum users not only make use of words to ‘do’ things in the online self-help forum, but they also employ emojis to either supplement or complement speech acts. This study also shows that emojis perform multiple functions in the discussion posts and argues that they do not merely function as emotion indicators of their textual company, but also carry significant pragmatic meanings by illustrating how they can also carry illocutionary force and in some cases, even alter the illocutionary force of their preceding texts. The findings of this study enhance our understanding of how forum users communicate via verbal and nonverbal means within the underexplored ‘helping domain’ of online discussion forums. It also suggests that online discussion forum interactions need to be approached differently than other better understood alternatives. [ABSTRACT FROM AUTHOR]

Background: The COVID-19 pandemic has brought challenges to families around the world. The prolonged school closures in Hong Kong have forced young students to stay at home and adapt to remote learning for over a year, putting their mental health conditions at risk. Focusing on primary school students and their parents, the main objective of our research is to investigate the socioemotional factors and their associations with mental health conditions. Methods: A total of 700 Hong Kong primary schoolers (mean age = 8.2) reported their emotional experiences, loneliness, and academic self-concept via a user-friendly online survey; 537 parents reported depression and anxiety, perceived child depression and anxiety, and social support. Responses from students and parents were paired to account for the family context. Structural Equation Modeling was used for correlations and regressions. Results: The results of students' responses showed that positive emotional experiences were negatively associated with loneliness and positively related to academic self-concept among students. Furthermore, the paired sample results showed that, during the one-year societal lockdown and remote learning period, the socioemotional factors were associated with mental health conditions among primary school students and their parents. Among our family sample in Hong Kong, evidence supports the unique negative association between students-reported positive emotional experiences and parents-reported child depression and anxiety, as well as between social support and parents' depression and anxiety. Conclusions: These findings highlighted the associations between socioemotional factors and mental health among young primary schoolers during the societal lockdown. We thus call for more attention to the societal lockdown and remote learning context, especially since the social distancing practice could be "the new normal" for our society to handle the future pandemic crisis. [ABSTRACT FROM AUTHOR]

This research studies the impact of shopping tourism on retail sales and rents, using the COVID-19 pandemic as a quasi-experiment. Shopping tourism refers to individuals who travel primarily for shopping purposes, and their spending patterns can have significant effects on the retail sector. The COVID-19 pandemic disrupted global travel and resulted in a decline in shopping tourist arrivals, leading to a downturn in sales for retailers dependent on shopping tourism. Additionally, the decline in shopping tourism affected retail rents, as the reduced demand for retail spaces posed challenges for property owners in attracting tenants. The study focuses on Hong Kong, a prominent shopping destination, which experienced a significant decline in tourist arrivals and retail sales during the pandemic. The research analyses the relationship between tourist arrivals, retail sales, and rents using time series analysis and identifies the impact of shopping tourism on retail rents. The findings suggest a positive association between tourist arrivals and retail sales and rents, particularly during the period of shopping tourism growth. However, the pandemic severely reduced this effect, revealing the impact of shopping tourists on the retail sector. The study concludes by discussing the implications for retail resilience and highlighting the need for further research on the impacts of shopping tourism on retail sales and rents. [ABSTRACT FROM AUTHOR]

The fifth wave of COVID-19 in Hong Kong (2022) had brought a series of chaos to society. Nevertheless, its Asian neighbours, namely Singapore and Macao, have avoided such chaos. By investigating the well-rounded preventive measures and social environment in Singapore and Macao, this article highlights the Hong Kong government's "idleness". It reveals that the relationship between a government and its people does play a significant role in operating COVID-19 measures, which could directly prevent a large-scale outbreak. [ABSTRACT FROM AUTHOR]

Background: The levels of resource losses due to coronavirus disease 2019 (COVID-19) and mental distress may change during the pandemic period. Based on the Conservation of Resource (COR) Theory, this study investigated such changes and the mediation between survey time (Round 2 versus Round 1) and depression via resource losses. Methods: Two serial random population-based telephone surveys interviewed 209 and 458 Hong Kong Chinese adults in April 2020 and May 2021, respectively. Probable depression was defined as 9-item Patient Health Questionnaire (PHQ-9) score ≥ 10. The validated Conservation of Resources Scale for COVID-19 (CORS-COVID-19) scale was used to assess resource losses due to COVID-19. Multivariable logistic regression analysis, hierarchical logistic regression analysis, and structural equation modeling (SEM) was conducted to test the association, interaction, and mediation hypotheses, respectively. Results: The prevalence of probable depression declined from 8.6% to 1.0% over time, together with reductions in losses of financial resource (Cohen's d = 0.88), future control (Cohen's d = 0.39), social resource (Cohen's d = 0.60), and family resource (Cohen's d = 0.36) due to COVID-19. All the overall scale/subscales of the CORS-COVID-19 were positively and associated with probable depression [adjusted odds ratio (aOR) ranged from 2.72 to 42.30]. In SEM, the survey time was negatively associated with the latent variable of resource loss (β = − 0.46), which in turn was positively associated with probable depression (β = 0.73). In addition, the direct effect of survey time on probable depression was statistically non-significant (β = − 0.08), indicating a full mediation effect of resource losses. Conclusions: The lessening of the resource losses might have fully accounted for the significant decline in probable depression from Month 3 to 15 since the first COVID-19 outbreak in Hong Kong, China. The level of depression might have increased during the first phase of the pandemic, but might decline in the later phases if resources losses could be lessened. All stakeholders should hence work together to minimize individuals' COVID-19-related resource losses to prevent depression in the general population, as COVID-19 might be lasting. [ABSTRACT FROM AUTHOR]

Background: The Hong Kong Poison Information Centre has provided consultation service to healthcare professionals and collected epidemiological data on poisoning in Hong Kong since 2005. Objective: To analyse and report the poisoning data of Hong Kong Poison Information Centre in 2020 during the COVID-19 pandemic. Methods: A retrospective review of all poisoning cases recorded in the Poison Information and Clinical Management System of Hong Kong Poison Information Centre in 2020. Results: A total of 3633 poisoning cases were analysed. Compared to 2019 (pre-COVID era), there was a reduction of ~10% of total poisoning cases recorded (383 cases), with a majority (> 90%) of reduction from poisoning cases with no clinical effect (353 cases). A greater proportion of reduction was observed among the children (0–12 years), patients with general unintentional poisoning, poisoning due to therapeutic error and food poisoning. An increased number of cases was noted from abusive use, adverse herb/proprietary Chinese medicine reaction and poisoning related to household bleaches. Teenage (13–19 years) poisoning seemed to be unaffected by the COVID-19 pandemic and the previously observed increasing trend continued (up to 11.8% of total poisoning cases this year). Despite a total reduction in poisoning cases recorded, the number of deaths increased by 37% from 35 in 2019 to 48 in 2020 (mortality rate 1.5%). A total of seven interesting cases were discussed. Conclusion: This 15th annual report provides updated epidemiological information on poisoning patterns in Hong Kong during the COVID-19 pandemic. It also highlighted important changes and possible effects of the COVID-19 pandemic on poisoning in Hong Kong in comparison with our previous reports. [ABSTRACT FROM AUTHOR]

This study investigates how health literacy (HL) and trust in health information affected COVID-19 vaccine hesitancy among Chinese Hong Kong adults. A cross-sectional study was conducted in August 2022. A total of 401 participants completed the study. Participants completed a newly developed Hong Kong HL scale and self-reported their trust levels in health information from different resources. The proportions of early uptake of the first dose and booster dose of COVID-19 vaccine were 69.1% and 71.8%, respectively. The risk of delaying the first dose was higher among participants with inadequate functional HL (OR = 0.58, p = 0.015), adequate levels of two subdomains of critical HL (OR = 1.82, p = 0.013; OR = 1.91, p < 0.01), and low-level trust in health information from the government (OR = 0.57, p = 0.019). Respondents with adequate interactive HL (OR = 0.52, p = 0.014) and inadequate level of one subdomain of critical HL (OR =1.71, p = 0.039) were more likely to delay the booster dose. This negative association between critical HL and vaccination was suppressed by trust in health information from the government. This study shows that HL and trust in health information from the government are associated with COVID-19 vaccine hesitancy. Efforts should be directed at providing tailored communication strategies with regard to people's HL and increasing public confidence in health authorities to decrease vaccine hesitancy. [ABSTRACT FROM AUTHOR]

Understanding the space–time pattern of the transmission locations of COVID-19, as well as the relationship between the pattern, socioeconomic status, and environmental factors, is important for pandemic prevention. Most existing research mainly analyzes the locations resided in or visited by COVID-19 cases, while few studies have been undertaken on the space–time pattern of the locations at which the transmissions took place and its associated influencing factors. To fill this gap, this study focuses on the space–time distribution patterns of COVID-19 transmission locations and the association between such patterns and urban factors. With Hong Kong as the study area, transmission chains of the four waves of COVID-19 outbreak in Hong Kong during the time period of January 2020 to June 2021 were reconstructed from the collected case information, and then the locations of COVID-19 transmission were inferred from the transmission chains. Statistically significant clusters of COVID-19 transmission locations at the level of tertiary planning units (TPUs) were detected and compared among different waves of COVID-19 outbreak. The high-risk areas and the associated influencing factors of different waves were also investigated. The results indicate that COVID-19 transmission began with the Hong Kong Island, further moved northward towards the New Territories, and finally shifted to the south Hong Kong Island, and the transmission population shows a difference between residential locations and non-residential locations. The research results can provide health authorities and policy-makers with useful information for pandemic prevention, as well as serve as a guide to the public in the avoidance of activities and places with a high risk of contagion. [ABSTRACT FROM AUTHOR]

Background: The heterogeneity of COVID-19 spread dynamics is determined by complex spatiotemporal transmission patterns at a fine scale, especially in densely populated regions. In this study, we aim to discover such fine-scale transmission patterns via deep learning. Methods: We introduce the notion of TransCode to characterize fine-scale spatiotemporal transmission patterns of COVID-19 caused by metapopulation mobility and contact behaviors. First, in Hong Kong, China, we construct the mobility trajectories of confirmed cases using their visiting records. Then we estimate the transmissibility of individual cases in different locations based on their temporal infectiousness distribution. Integrating the spatial and temporal information, we represent the TransCode via spatiotemporal transmission networks. Further, we propose a deep transfer learning model to adapt the TransCode of Hong Kong, China to achieve fine-scale transmission characterization and risk prediction in six densely populated metropolises: New York City, San Francisco, Toronto, London, Berlin, and Tokyo, where fine-scale data are limited. All the data used in this study are publicly available. Results: The TransCode of Hong Kong, China derived from the spatial transmission information and temporal infectiousness distribution of individual cases reveals the transmission patterns (e.g., the imported and exported transmission intensities) at the district and constituency levels during different COVID-19 outbreaks waves. By adapting the TransCode of Hong Kong, China to other data-limited densely populated metropolises, the proposed method outperforms other representative methods by more than 10% in terms of the prediction accuracy of the disease dynamics (i.e., the trend of case numbers), and the fine-scale spatiotemporal transmission patterns in these metropolises could also be well captured due to some shared intrinsically common patterns of human mobility and contact behaviors at the metapopulation level. Conclusions: The fine-scale transmission patterns due to the metapopulation level mobility (e.g., travel across different districts) and contact behaviors (e.g., gathering in social-economic centers) are one of the main contributors to the rapid spread of the virus. Characterization of the fine-scale transmission patterns using the TransCode will facilitate the development of tailor-made intervention strategies to effectively contain disease transmission in the targeted regions. [ABSTRACT FROM AUTHOR]

Mass gatherings provide conditions for the transmission of infectious diseases and pose complex challenges to public health. Faced with the COVID-19 pandemic, governments and health experts called for suspension of gatherings in order to reduce social contact via which virus is transmitted. However, few studies have investigated the contribution of mass gatherings to COVID-19 transmission in local communities. In Hong Kong, the coincidence of the relaxation of group gathering restrictions with demonstrations against the National Security Law in mid-2020 raised concerns about the safety of mass gatherings under the pandemic. Therefore, this study examines the impacts of mass gatherings on the local transmission of COVID-19 and evaluates the importance of social distancing policies. With an aggregated dataset of epidemiological, city-level meteorological and socioeconomic data, a Synthetic Control Method (SCM) is used for constructing a 'synthetic Hong Kong' from over 200 Chinese cities. This counterfactual control unit is used to simulate COVID-19 infection patterns (i.e., the number of total cases and daily new cases) in the absence of mass gatherings. Comparing the hypothetical trends and the actual ones, our results indicate that the infection rate observed in Hong Kong is substantially higher than that in the counterfactual control unit (2.63% vs. 0.07%). As estimated, mass gatherings increased the number of new infections by 62 cases (or 87.58% of total new cases) over the 10–day period and by 737 cases (or 97.23%) over the 30-day period. These findings suggest the necessity of tightening social distancing policies, especially the prohibition on group gathering regulation (POGGR), to prevent and control COVID-19 outbreaks. [ABSTRACT FROM AUTHOR]

Under COVID-19, there is an increasing demand for collecting health information from citizens by the government. It is commonly argued that there is a positive relationship between trust and willingness to disclose data. This finding has rarely been tested in the context of public health emergencies—for example, during COVID-19, when governments claim that data collection is necessary. Using a web survey result conducted in Hong Kong (N = 906), the moderated mediation model suggested that the indirect effect of trust in the Hong Kong government on citizens’ willingness to disclose personal and health data through the perceived legitimacy of the government’s actions is conditionally affected by COVID-19 infection concern. The direct effect involves normative thinking in considering the social norm of whether the government is legitimate to do so. Under strict law enforcement by the government, it creates an impression that personal concerns outweigh societal benefits, which can be explained by “data egoism,” which would lower the indirect effect onto the willingness to disclose personal and health data. Theoretical and practical implications of the findings are discussed. [ABSTRACT FROM AUTHOR]

Copyright of Turkish Journal of Public Health is the property of Turkish Journal of Public Health and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: The purpose of this study was: [1] to evaluate the infectivity of two SARS-CoV-2 lineage A variants on human ocular tissues in vitro, and [2] to evaluate the stability of SARS-CoV-2 lineage A variants in corneal preservation medium. Methods: Primary cultures of donor corneal, conjunctival, and limbal epithelium were inoculated with two lineage A, GISAID clade S isolates of SARS-CoV-2 (Hong Kong/VM20001061/2020, USA-WA1/2020), to evaluate the susceptibility of the ocular tissue to infection. Flat-mounted Descemet's Stripping Automated Endothelial Keratoplasty (DSAEK) grafts were inoculated with SARS-CoV-2 to evaluate the susceptibility of the endothelium to infection. All inoculated samples were immunostained for SARS-CoV-2 nucleocapsid (N)-protein expression to confirm positive infection. SARS-CoV-2 Hong Kong was then inoculated into cornea preservation media (Life4°C, Numedis, Inc.). Inoculated media was stored at 4oC for 14 days and assayed over time for changes in infectious viral titers. Results: Corneal, conjunctival, and limbal epithelial cells all demonstrated susceptibility to infection by SARS-CoV-2 lineage A variants. Conjunctiva demonstrated the highest infection rate (78% of samples infected [14/18]); however, infection rates did not differ statistically between cell types and viral isolates. After inoculation, 40% (4/10) of DSAEK grafts had active infection in the endothelium. SARS-CoV-2 lineage A demonstrated < 1 log decline in viral titers out to 14 days in corneal preservation media. Conclusions: SARS-CoV-2 lineage A variants can infect corneal, limbal, and conjunctival epithelium, as well as corneal endothelium. There was no statistical difference in infectivity between different lineage A variants. SARS-CoV-2 lineage A can survive and remain infectious in corneal preservation media out to 14 days in cold storage. [ABSTRACT FROM AUTHOR]

Objective: As Hong Kong faced the 5th wave of the COVID‐19 pandemic, the facilitators and hurdles toward effective vaccination is important for healthcare professionals to understand the vaccination gap among patients with epilepsy. Methods: A cross‐sectional, pragmatic study of COVID‐19 vaccination was performed at a tertiary epilepsy center with regards to patterns of vaccination and any unusually high rate of adverse events. Patients having recent visits at the epilepsy center (4 months) had their anonymized electronic linkage records examined 12 months after the inception of vaccination program for types of vaccines, seizure demographics, and adverse events following immunization (AEFI). Results: A total of 200 patients with epilepsy and their anonymized data were analyzed. The vaccine uptake was approximately 60% of that of the general population. Twice as many patients with epilepsy chose to receive mRNA vaccine as compared with inactivated vaccine. The proportion of patients who kept up‐to‐date with all available dosing was 7%. Patients with epilepsy with genetic etiology were least likely to receive vaccination (13/38, 34%, P =.02). There was no unreasonably high rate of unacceptable side effects after vaccination among patients with epilepsy. Only 3 patients reported worsening of seizures without meeting the criteria for AEFI. Refractory epilepsy, allergy to antiseizure medications and elder age (≥65) did not confer any significant difference in vaccination patterns or adverse effects. Significance: A vaccination gap exists among epilepsy patients which calls for actionable strategies for improving vaccine uptake, including education and outreach programs. [ABSTRACT FROM AUTHOR]

We conducted a statistical study and developed a machine learning model to triage COVID-19 patients affected during the height of the COVID-19 pandemic in Hong Kong based on their medical records and test results (features) collected during their hospitalization. The correlation between the values of these features is studied against discharge status and disease severity as a preliminary step to identify those features with a more pronounced effect on the patient outcome. Once identified, they constitute the inputs of four machine learning models, Decision Tree, Random Forest, Gradient and RUSBoosting, which predict both the Mortality and Severity associated with the disease. We test the accuracy of the models when the number of input features is varied, demonstrating their stability; i.e., the models are already highly predictive when run over a core set of (6) features. We show that Random Forest and Gradient Boosting classifiers are highly accurate in predicting patients' Mortality (average accuracy ∼99%) as well as categorize patients (average accuracy ∼91%) into four distinct risk classes (Severity of COVID-19 infection). Our methodical and broad approach combines statistical insights with various machine learning models, which paves the way forward in the AI-assisted triage and prognosis of COVID-19 cases, which is potentially generalizable to other seasonal flus. [ABSTRACT FROM AUTHOR]

Background: During the COVID-19 pandemic, educational interventions have become necessary to prevent the spread of health-related misinformation among Hong Kong older adults. The primary objective of this study was to assess the feasibility of a student-led, telephone-delivered intervention to improve COVID-19-related health knowledge among Hong Kong older adults. The secondary objective was to evaluate the impact of the intervention on the student volunteers. Methods: Twenty-five participants aged 65 or above who were able to communicate in Cantonese and had no hearing or cognitive impairments were recruited for this longitudinal pre–post-study from a community center in Hong Kong. The pilot telephone-delivered intervention consisted of five telephone call sessions conducted by 25 student volunteers. Each participant was paired with the same volunteer throughout the intervention. The first four sessions included pre-tests that assessed the participants' understanding of three COVID-19-related themes: medication safety, healthcare voucher scheme, and COVID-19 myth-busting. Standardized explanations of the pre-test questions were offered to participants during the phone calls. In the last session, a post-test on all the themes was conducted. The intervention's feasibility was assessed based on (a) percentage changes in the participants' test scores, (b) attrition rate, and (c) the acceptability of the intervention by the participants. The impact of the intervention on the student volunteers was evaluated based on a student feedback survey. There was no control group. Results: Significant improvements in the participants' test scores (out of 100%) for all themes were observed after the intervention: from 76 to 95.2% for medication safety, from 64.0 to 88.8% for the healthcare voucher scheme, and from 78.0 to 93.2% for COVID-19 myth-busting. The average improvement in test scores of the three themes was 18.4% (95% CI 12.2 to 24.6%). Most participants were satisfied with the program. The student feedback survey suggested that the intervention enhanced students' communication skills and understanding of Hong Kong older adults. Conclusion: This pilot study offers initial evidence of the potential and feasibility of student-led, telephone-delivered educational interventions for the transfer of COVID-19-related knowledge to older adults and their benefits for the student volunteers. Future studies should include larger samples and a control group. [ABSTRACT FROM AUTHOR]

Our study (NCT04800133) aimed to determine the safety and immunogenicity in patients with IEIs receiving a 3-dose primary series of mRNA vaccine BNT162b2 (age 12+) or inactivated whole-virion vaccine CoronaVac (age 3+) in Hong Kong, including Omicron BA.1 neutralization, in a nonrandomized manner. Intradermal vaccination was also studied. Thirty-nine patients were vaccinated, including 16 with homologous intramuscular 0.3ml BNT162b2 and 17 with homologous intramuscular 0.5ml CoronaVac. Two patients received 3 doses of intradermal 0.5ml CoronaVac, and 4 patients received 2 doses of intramuscular BNT162b2 and the third dose with intradermal BNT162b2. No safety concerns were identified. Inadequate S-RBD IgG and surrogate virus neutralization responses were found after 2 doses in patients with humoral immunodeficiencies and especially so against BA.1. Dose 3 of either vaccine increased S-RBD IgG response. T cell responses against SARS-CoV-2 antigens were detected in vaccinated IEI patients by intracellular cytokine staining on flow cytometry. Intradermal third dose vaccine led to high antibody response in 4 patients. The primary vaccination series of BNT162b2 and CoronaVac in adults and children with IEIs should include 3 doses for optimal immunogenicity. [ABSTRACT FROM AUTHOR]

Background: The COVID-19 pandemic has imposed a profound negative impact on the mental health and wellbeing of societies and individuals worldwide. Older adults may be more vulnerable to the mental health effects of the pandemic, either directly from the infection itself or indirectly through the preventive measures. However, the existing literature on mental health in the older age groups has not been consistent so far. The aim of this study was therefore to assess the prevalence of common mental disorders (CMD; including depression and anxiety disorders) given their association with dementia risk, and to further examine age-related differences between older (≥60 years old) and younger (18-59 years old) adult's psychological status during the COVID-19 pandemic. Method: This was a secondary analysis of a cross-sectional survey-study conducted during the second wave of COVID-19 pandemic in Hong Kong. The survey was disseminated through different social media platforms to the general population and included sociodemographic questions, self-reported physical health, and previous encounter with SARS or COVID-19. CMD was the primary outcome and was assessed using the 6-item Kessler Scale. A total of 1030 adults fulfilled inclusion criteria. Results: The prevalence of CMD during the pandemic was 16.1%. Compared to younger adults, older adults were significantly less likely to have a CMD (unadjusted OR = 0.07, 95% CI = 0.02-0.30, p < 0.001), with 18.1% of younger adults having CMD compared to 1.6% in the older cohort. Age differences remained significant after controlling for sociodemographic factors, physical health, and previous encounter with SARS or COVID-19 (adjusted OR = 0.12, 95% CI = 0.02-0.57, p = 0.008). Conclusion: Common mental disorders are highly prevalent during the COVID-19 pandemic in Hong Kong, though older adults appeared to be less affected mentally. Present findings highlight the urgent need to implement measures and strategies tomitigate themental health problems, with particular Frontiers in attention to the younger cohort. Given their association with higher dementia risk, early detection and treatment of depression and anxiety disorders will be of critical importance in providing some relief to the already pressurized dementia burden in the longer term. [ABSTRACT FROM AUTHOR]

The worldwide spread of COVID-19 has caused significant damage to people's health and economics. Many works have leveraged machine learning models to facilitate the control and treatment of COVID-19. However, most of them focus on clinical medicine and few on understanding the spatial dynamics of the high-risk population for transmission of COVID-19 in real-world settings. This study aims to investigate the association between population features and COVID-19 transmission risk in Hong Kong, which can help guide the allocation of medical resources and the implementation of preventative measures to control the spread of the pandemic. First, we built machine learning models to predict the number of COVID-19 cases based on the population features of different tertiary planning units (TPUs). Then, we analyzed the distribution of cases and the prediction results to find specific characteristics of TPUs leading to large-scale outbreaks of COVID-19. We further evaluated the importance and influence of various population features on the prediction results using SHAP values to identify indicators for high-risk populations for COVID-19 transmission. The evaluation of COVID-19 cases and the TPU dataset in Hong Kong shows the effectiveness of the proposed methods. The top three most important indicators are identified as people in accommodation and food services, low income, and high population density. [ABSTRACT FROM AUTHOR]

Studies show that coronavirus disease 2019 (COVID-19) vaccine hesitancy exists among healthcare workers (HCWs). Past personal experiences of vaccination, such as the seasonal influenza vaccination, influence individuals' intention to receive future vaccinations. This study aimed to explore the experience of COVID-19 vaccination among primary care HCWs in Hong Kong. A qualitative study using semi-structured interviews was conducted. Twenty-eight HCWs (ten doctors, ten nurses, and eight supporting staff) working in nine government-funded primary care clinics in Hong Kong who had completed at least one dose of COVID-19 vaccination were interviewed. Four themes were generated, namely, the cognitive and emotional battle of vaccine hesitancy, catalysts for vaccine acceptance, blasting vaccination myths, and being a positive influence. Providing timely, adequate, and transparent vaccine information and addressing the specific concerns of HCWs about the COVID-19 vaccine could enhance their vaccination uptake in future. Specific vaccine promotion strategies, such as the sharing of vaccination experiences targeted at different subgroups of HCWs, may improve vaccine acceptance through informational social influence. [ABSTRACT FROM AUTHOR]

Objectives: This study aimed to evaluate the effects of Chinese Medicine (CM) on the health condition of the post-COVID-19 patients, particularly with the CM Syndrome diagnosis and Body Constitutions (BC), as well as related clinical characteristics. Methods: 150 participants who had COVID-19 and discharged from Hong Kong public hospitals were recruited. They were provided with three to six months of CM treatments, during which assessments were made per month and at follow-up on their CM syndromes, BC, lung functions, and other medical conditions. This study was divided into two parts: (1) Retrospective survey: medical history of participants during COVID-19 hospitalization was collected during the baseline visit; (2) Prospective observation and assessments: clinical symptoms, lung functions, and BC status were evaluated in participants receiving CM treatment based on syndrome differentiation and clinical symptoms. Results: The median hospitalization period was 16 days. Symptoms were presented in 145 (96.6%) patients at the day they were diagnosed with COVID-19. Fever, fatigue, and dry cough were the most common symptoms, exhibiting in 59.3% (89 of 150), 55.3% (83 of 150), and 46% (70 of 150) participants, respectively. Among the 150 post-COVID patients, majority (71.3%) were of the two particular post-COVID CM Syndromes (Qi Deficiency of Lung and Spleen, and Qi and Yin Deficiency). Upon CM treatment, there was an observable increase in participants reaching a balanced BC (i.e. healthy body conditions). The increase was observed to be more prominent in those without the particular CM Syndromes compared to those with the CM Syndromes. Main clinical symptoms in participants with the CM Syndromes decreased upon CM treatment. Occurrence of fatigue also dropped after CM treatment though not all accompanied clinical symptoms were resolved fully. Further to the improvement in terms of CM assessments, lung functions of the participants were found to show improvement after treatment. Both the performance in 6MWT and scores in the LFQ improved upon CM treatments (P < 0.05). Conclusion: This study provided evidence for individualized CM treatment on COVID-19 rehabilitation concerning the clinical symptoms improvements, lung functions improvement, and achieving a balanced BC. It is believed that CM may be a key to further promote rehabilitation and resolution of residual symptoms. Long-term large scale follow-up studies on sub-categorising post-COVID patients according to different CM syndromes would be required to further elucidate treatment of persistent symptoms that may be associated with long-COVID. [ABSTRACT FROM AUTHOR]

Background: Adversity coping capability (ACC) is important amid the COVID-19 pandemic. We examined the associations of ACC as measured by our one-item ACC scale (ACC-1) with mental health, family well-being and validity of ACC-1 in Hong Kong. Methods: A cross-sectional survey was conducted on Hong Kong Chinese adults aged ≥ 18 years by landline, mobile phone, and online survey from February to March 2021, when the fourth wave of COVID-19 was under control. ACC-1 consisted of the question: "How do you rate your capability to cope with adversities?" with higher scores (0–10) indicating stronger ACC. The associations of ACC with socioeconomic characteristics, resilience, mental health, and family wellbeing were examined by linear regression coefficients (βs). Data were weighted by sex, age, and education of the general population. Results: Of 7441 respondents, after weighing, 52.2% were female and 79.1% were aged 18 to 64 years. ACC-1 showed good construct validity, with higher ACC being associated with higher levels of resilience (adjusted β = 0.29), personal happiness (0.55), family happiness (0.42), family wellbeing (0.41), and family communication quality (0.41), and lower levels of depressive symptoms (-0.30), anxiety (-0.30), loneliness (-0.15); incremental validity with additional contributions of ACC to mental health and family wellbeing; and known-group validity with older age and favorable socioeconomic characteristics showing higher ACC (all P < 0.02). Females (mean ± standard deviation: 6.04 ± 1.82 vs 6.15 ± 1.96 [male]) and unemployed respondents (5.30 ± 1.99 vs 6.11 ± 2.03 [in paid employment]) had lower ACC (all P ≤ 0.02). Conclusions: We have first shown that stronger ACC was associated with better mental health and family wellbeing, and the results support ACC-1 as a simple and valid measure of ACC. [ABSTRACT FROM AUTHOR]