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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]

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]

Background: China witnessed a surge of Omicron infections after abandoning 'zero COVID' strategies on 7 December 2022. The authorities report very sparse deaths based on very restricted criteria, but massive deaths are speculated. Methods: We aimed to estimate the COVID‐19 fatalities in Mainland China until summer 2023 using the experiences of Hong Kong and of South Korea in 2022 as prototypes. Both these locations experienced massive Omicron waves after having had very few SARS‐CoV‐2 infections during 2020–2021. We estimated age‐stratified infection fatality rates (IFRs) in Hong Kong and South Korea during 2022 and extrapolated to the population age structure of Mainland China. We also accounted separately for deaths of residents in long‐term care facilities in both Hong Kong and South Korea. Results: Infection fatality rate estimates in non‐elderly strata were modestly higher in Hong Kong than South Korea and projected 987,455 and 619,549 maximal COVID‐19 deaths respectively, if the entire China population were infected. Expected COVID‐19 deaths in Mainland China until summer 2023 ranged from 49,962 to 691,219 assuming 25–70% of the non‐elderly population being infected and variable protection of elderly (from none to three‐quarter reduction in fatalities). The main analysis (45% of non‐elderly population infected and fatality impact among elderly reduced by half) estimated 152,886–249,094 COVID‐19 deaths until summer 2023. Large uncertainties exist regarding potential changes in dominant variant, health system strain and impact on non‐COVID‐19 deaths. Conclusions: The most critical factor that can affect total COVID‐19 fatalities in China is the extent to which the elderly can be protected. [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]

We trace the crafting of expert narratives during the initial months of the COVID‐19 pandemic in Mainland China, Hong Kong, and the United States. By expert narratives, we refer to how experts drew different lessons from past disease experiences to guide policymakers and the public amidst uncertainty. These expert narratives were mobilized in different sociopolitical contexts, resulting in varying configurations of expertise networks and allies that helped contain and mitigate COVID‐19. In Mainland China, experts carefully advanced a managed narrative, emphasizing the new pandemic akin to the 2003 SARS outbreak can be managed while destressing the similar mistakes the government made during the two crises. In Hong Kong, experts invoked a distrust narrative, pointing to a potential coverup of COVID‐19 similar to SARS, activating allies in civil society to pressure policymakers to act. In the United States, experts were mired in a contested narrative and COVID‐19 was compared to different diseases; varying interpretations of COVID‐19's consequences was exacerbated by political polarization. In expert narratives, the resonance of the past is emergent: the past becomes a site of struggle and a cultural object that is presented as potentially useful in solving problems of the present. [ABSTRACT FROM AUTHOR]

Purpose: This study investigated the associations between some factors related to working from home status (WFHS) and positive/negative experiences due to social distancing and their interactions effects on depressive symptoms during the COVID-19 pandemic. Methods: A random population-based telephone survey interviewed income-earning adults in the Hong Kong general population during April 21–28, 2020 (n = 200). Results: Mild to severe depression (according to PHQ-9) was reported by 12% of the participants. The prevalence of WFHS categories was 14% for 3–7 days and 13% for ≥ 8 days (past 2 weeks). The multivariable regression analysis showed that, social isolation (β = 0.36; p < 0.001), relaxation feeling in daily life (β = − 0.22; p = 0.002), and WFHS ≥ 8 days (β = 0.15; p = 0.027), but not perceived huge inconvenience and improved family relationship, were associated with depressive symptoms. Statistically significant interaction effects were found. Some positive experiences buffered the potential harms of some negative experiences of social distancing on depressive symptoms; WFHS ≥ 8 days significantly moderated the risk/protective effects of social isolation, improved family relationship, and relaxation feeling on depressive symptoms. Conclusions: Social distancing is double-edged. Positive experiences should be maximized while negative experiences be minimized, as both were directly and interactively associated with depression. Intensive but not mild to moderate (< 80%) WFHS may impact depressive symptoms negatively via its direct association with depression; it also moderated the associations between positive/negative experiences due to social distancing and depression. Further research is required to discern the inter-relationships among WFHS, positive/negative experiences of social distancing, and depression to better cope with the stressful pandemic. [ABSTRACT FROM AUTHOR]

Background: Uptake of social distancing behaviors may be determined by a combination of individual perceptions and social values. The study investigated (1) the associations between individual perception of perceived response efficacy and social distancing behaviors, (2) the association between social value of perceived freedom infringement and social distancing behaviors, and (3) whether perceived freedom infringement would moderate the association between perceived response efficacy and social distancing behaviors. Methods: A cross-sectional telephone survey interviewed 300 adults in the Hong Kong adult general population during April 21-28, 2020. The instruments of social distancing behaviors, perceived response efficacy, and perceived freedom infringement assessed the frequencies of practicing seven types of social distancing behaviors in the past week, perceived response efficacy of four types of governmental social distancing measures/instructions, and a 5-point Likert scale item on perceived infringement on personal freedom regarding a governmental social distancing measure of banning gatherings of >4 people in public areas. Linear regression adjusted for background factors was performed; the interaction term of perceived response efficacy × perceived freedom infringement was tested. Results: About 40.4%-83.0% of the respondents practiced various types of social distancing behaviors; 57.3%-75.0% perceived response efficacies of related governmental measures; about 20% showed perceived freedom infringement. Perceived response efficacy, but not perceived freedom infringement, was independently and positively associated with social distancing behaviors. Perceived freedom infringement significantly moderated the association between perceived response efficacy and social distancing behaviors; such a positive association was significant at higher (those scored "extremely agree"), but not lower (those scored "extremely disagree"), levels of perceived freedom infringement. Conclusion: Perceived response efficacy is a potential determinant of social distancing. However, the strength of such an association may be modified by opposing social values about personal freedom. Future studies are warranted to verify above findings and explore other potential determinants. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic, an exceptional crisis, sparked the introduction of new digital infrastructure to halt the novel coronavirus's spread. This paper explores how such digital infrastructure's impact might reverberate over the long term, by comparing Singapore, Hong Kong, and mainland China's utilization of digital technology in response to the 2003 SARS outbreak, and their responses to the 2020 COVID-19 pandemic. We find that advancements in digital technology since 2003 have boosted governments' surveillance and segregation abilities substantially—most dramatically so in China. Even though some of these new digital interventions are ostensibly designed to be temporary ones to address the needs of the immediate crisis, we argue that the resultant extensions of state power experienced during COVID-19 are likely to have profound long-term effects because they fundamentally affect sociopolitical contexts, institutional capabilities, and digital cultures. We also find that the extent to which governments can extend digital surveillance and segregation abilities during the pandemic is contingent on their respective sociopolitical, institutional, and digital cultural contexts. • COVID-19 pandemic sparked calls for a new digital infrastructure. • We compare 2003 SARS outbreak to COVID-19 pandemic. • New digital technologies increased governments' ability to surveil and segregate. • Their impact on surveillance and segregation will persist post COVID-19. [ABSTRACT FROM AUTHOR]

This study aimed to establish a new COVID‐19 Fear (Higher Education) scale to investigate the relationship between fear and generalised anxiety symptoms among Chinese students in mainland China, Hong Kong, and other countries. 219 Chinese university students studying in universities in mainland China (n = 76, 34.7%), Hong Kong (n = 66, 30.1%), and overseas (i.e., outside of China as international students, n = 77, 35.2%) participated in an online study from March 31, 2020 to April 4. Participants completed a newly developed COVID‐19 Fear (Higher Education) scale to measure three domains of fear including fear of infection, fear of instability and fear of insecurity related to the COVID‐19 pandemic. They also completed the Generalized Anxiety Disorder 7‐item scale (GAD‐7) on the severity of anxiety symptoms. About 9.6% of the participants could be classified as exhibiting high anxiety level according to the GAD‐7. More students studying overseas (about 15%) were classified into the high GAD group when compared to students studying in both mainland China (6.6%) and Hong Kong (6.1%). MANOVA results showed that students studying in Hong Kong and overseas had more concerns related to preventive measures related to COVID‐19 than their mainland counterparts did. We concluded that international students studying away from their home country would have higher risk to develop anxiety problems during a collective trauma such as the COVID‐19 pandemic. Education institutions should provide support services including online support groups, social media groups for mutual support to alleviate the fear and anxiety of international students. [ABSTRACT FROM AUTHOR]