Protective role of zinc in the pathogenesis of respiratory diseases.

Respiratory diseases remain a major cause of morbidity and mortality worldwide. An imbalance of zinc, an essential trace element, is associated with a variety of lung diseases. We reviewed and summarized recent research (human subjects, animal studies, in vitro studies) on zinc in respiratory diseases to explore the protective mechanism of zinc from the perspective of regulation of oxidative stress, inflammation, lipid metabolism, and apoptosis. In the lungs, zinc has anti-inflammatory, antioxidant, and antiviral effects; can inhibit cancer cell migration; can regulate lipid metabolism and immune cells; and exerts other protective effects. Our comprehensive evaluation highlights the clinical and experimental effects of zinc in the pathogenesis of respiratory diseases. Our analysis also provides insight into the clinical application of zinc-targeted therapy for respiratory diseases.

Heat waves accelerate the spread of infectious diseases.

COVID-19 pandemic appeared summer surge in 2022 worldwide and this contradicts its seasonal fluctuations. Even as high temperature and intense ultraviolet radiation can inhibit viral activity, the number of new cases worldwide has increased to >78% in only 1 month since the summer of 2022 under unchanged virus mutation influence and control policies. Using the attribution analysis based on the theoretical infectious diseases model simulation, we found the mechanism of the severe COVID-19 outbreak in the summer of 2022 and identified the amplification effect of heat wave events on its magnitude. The results suggest that approximately 69.3% of COVID-19 cases this summer could have been avoided if there is no heat waves. The collision between the pandemic and the heatwave is not an accident. Climate change is leading to more frequent extreme climate events and an increasing number of infectious diseases, posing an urgent threat to human health and life. Therefore, public health authorities must quickly develop coordinated management plans to deal with the simultaneous occurrence of extreme climate events and infectious diseases.

COVID-19 and Urban Futures: Impacts on Business Closures in Miami-Dade County

The COVID-19 pandemic altered the local economic geographies of many U.S. cities, and it remains unclear how long these changes will persist. This study analyzed the sociospatial dynamics of business closures in Miami-Dade County, Florida, from August 2020 to August 2021 with an explicit focus on reconciling the pandemic's effects in the context of location theory. We found that traditional urban centers and transit-concentrated areas experienced disproportionately higher rates of business closures during the study period, suggesting a potential wave of commercial suburbanization in Miami. Middle-class and working-class Hispanic neighborhoods suffered the most business closures. The results of correlation analysis and spatial regression models suggested a positive association between the incidence of COVID-19 cases and business closures at both zip code and individual business levels. These results also beckon a revaluation of the role of certain urban externalities in traditional location theory. The importance of automobile accessibility and agglomeration effects are poised to persist beyond the pandemic, but the benefits of proximity to the public transport system might decline. The trends observed in Miami suggest that the pandemic could generate more automobile-reliant employment subcenters in U.S. cities and amplify problems of intraurban inequality and urban sprawl. (English) [ FROM AUTHOR] La pandemia del COVID-19 alteró las geografías económicas locales de muchas ciudades de los Estados Unidos, y aún no hay claridad por cuánto tiempo más persistirán estos cambios. Este estudio analizó la dinámica socioespacial del cierre de negocios en el Condado de Miami-Dade, Florida, de agosto del 2020 hasta agosto del 2021, centrándose explícitamente en reconciliar los efectos de la pandemia dentro del contexto de la teoría locacional. Descubrimos que los centros urbanos tradicionales y las áreas de tránsito concentrado experimentaron tasas desproporcionadamente más altas de cierres de negocios durante el período del estudio, lo cual sugiere una ola potencial de suburbanización comercial en Miami. Los vecindarios hispánicos de clase media y de la clase trabajadora sufrieron al máximo de cierres de negocios. Los resultados del análisis de los modelos de correlación y regresión espacial sugirieron una asociación positiva entre la incidencia de los casos de COVID-19 y los cierres de negocios, tanto al nivel de los códigos zip como de los negocios individuales. Estos resultados también invitan a la revaluación del papel de ciertas externalidades urbanas en la teoría locacional tradicional. La importancia de la accesibilidad al automóvil y los efectos de la aglomeración muestran disposición a persistir más allá de la pandemia, opero los beneficios de la proximidad del sistema de transporte público podría declinar. La tendencia observada en Miami sugiere que la pandemia podría generar más subcentros de empleo dependientes del automóvil en las ciudades americanas y ampliar los problemas de desigualdad intraurbana y la dispersión urbana. (Spanish) [ FROM AUTHOR] COVID-19疫情改变了美国许多城市的地方经济地理。目前, 尚不清楚这些变化会持续多久。本研究分析了2020年8月至2021年8月期间佛罗里达州迈阿密-戴德县商业倒闭的社会空间变化, 根据区位理论探讨了对疫情影响的缓解。我们发现, 在此期间, 传统的城市中心和交通密集地区经历了不成比例的更高的商业倒闭率, 这表明迈阿密可能会出现商业郊区化浪潮。西班牙裔中产阶级和工人阶级社区出现了最多的商业倒闭。相关性分析和空间回归模型结果表明, 在邮政编码尺度和个体尺度, COVID-19发病率与商业倒闭都存在着正相关性。这些结果也呼吁, 需要重新评估某些城市外部特性在传统区位理论中的作用。汽车可及性和聚集效应的重要性将会一直持续到疫情之后, 但公共交通系统的临近优势可能会下降。迈阿密的趋势表明, COVID-19可能会在美国城市产生更多依赖于汽车的就业分中心, 加剧城市内部不平等、城市扩张等问题。 (Chinese) [ FROM AUTHOR] Copyright of Annals of the American Association of Geographers is the property of Taylor & Francis Ltd 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 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 . (Copyright applies to all s.)

Genetics, structure, transmission, epidemiology, immune response, and vaccine efficacies of the SARS-CoV-2 Delta variant: A comprehensive review.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Delta variant (B.1.617.2) was the predominant variant behind the surges of COVID-19 in the United States, Europe, and India in the second half of 2021. The information available regarding the defining mutations and their effects on the structure, transmission, and vaccine efficacy of SARS-CoV-2 is constantly evolving. With waning vaccine immunity and relaxation of social distancing policies across the globe driving the increased spread of the Delta variant, there is a great need for a resource aggregating the most recent information for clinicians and researchers concerning the Delta variant. Accordingly, this narrative review comprehensively reviews the genetics, structure, epidemiology, clinical course, and vaccine efficacy of the Delta variant. Comparison with the omicron variant is also discussed. The Delta variant is defined by 15 mutations in the Spike protein, most of which increase affinity for the ACE-2 receptor or enhance immune escape. The Delta variant causes similar symptoms to prototypical COVID-19, but it is more likely to be severe, with a greater inflammatory phenotype and viral load. The reproduction number is estimated to be approximately twice the prototypical strains present during the early pandemic, and numerous breakthrough infections have been reported. Despite studies demonstrating breakthrough infection and reduced antibody neutralisation, full vaccination effectively reduces the likelihood of severe illness and hospitalisation.

A novel attention-based enhancement framework for face mask detection in complicated scenarios☆

In the context of COVID-19 pandemic prevention and control, it is of vital significance to realize accurate face mask detection via computer vision technique. In this paper, a novel attention improved Yolo (AI-Yolo) model is proposed, which can handle existing challenges in the complicated real-world scenarios with dense distribution, small-size object detection and interference of similar occlusions In particular, a selective kernel (SK) module is set to achieve convolution domain soft attention mechanism with split, fusion and selection operations;a spatial pyramid pooling (SPP) module is applied to enhance the expression of local and global features, which enriches the receptive field information;and a feature fusion (FF) module is utilized to promote sufficient fusions of multi-scale features from each resolution branch, which adopts basic convolution operators without excessive computational complexity. In addition, the complete intersection over union (CIoU) loss function is adopted in the training stage for accurate positioning. Experiments are carried out on two challenging public face mask detection datasets, and the results demonstrate the superiority of the proposed AI-Yolo against other seven state-of-the-art object detection algorithms, which achieves the best results in terms of mean average precision and F1 score on both datasets. Furthermore, effectiveness of the meticulously designed modules in AI-Yolo is validated through extensive ablation studies. In a word, the proposed AI-Yolo is competent to accomplish face mask detection tasks under extremely complex situations with precise localization and accurate classification.

Progressive attention integration-based multi-scale efficient network for medical imaging analysis with application to COVID-19 diagnosis.

In this paper, a novel deep learning-based medical imaging analysis framework is developed, which aims to deal with the insufficient feature learning caused by the imperfect property of imaging data. Named as multi-scale efficient network (MEN), the proposed method integrates different attention mechanisms to realize sufficient extraction of both detailed features and semantic information in a progressive learning manner. In particular, a fused-attention block is designed to extract fine-grained details from the input, where the squeeze-excitation (SE) attention mechanism is applied to make the model focus on potential lesion areas. A multi-scale low information loss (MSLIL)-attention block is proposed to compensate for potential global information loss and enhance the semantic correlations among features, where the efficient channel attention (ECA) mechanism is adopted. The proposed MEN is comprehensively evaluated on two COVID-19 diagnostic tasks, and the results show that as compared with some other advanced deep learning models, the proposed method is competitive in accurate COVID-19 recognition, which yields the best accuracy of 98.68% and 98.85%, respectively, and exhibits satisfactory generalization ability as well.

Melting the Psychological Boundary: How Interactive and Sensory Affordance Influence Users' Adoption of Digital Heritage Service

As a result of the post-pandemic situation, enhancing digital heritage services has become one of the key issues for the recovery of tourism. Disruptive innovation in human–computer interaction technology has brought new opportunities for digitalization and intelligent transformation in the contemporary cultural tourism industry. Existing research on the adoption behavior of digital heritage services primarily focuses on users' assessments of behavior results. There is a considerable gap in research about the interaction and value co-creation between users and digital intelligence services and users' cognitive construction logic of digital heritage services. Following reciprocal determinism, we propose a conceptual model to deconstruct the detailed transmission path of interactive affordance and sensory affordance to digital heritage adoption. In Study 1, a lab experiment in an AI-assisted smart screen digital heritage service context revealed that interactive affordance and user adoption of digital heritage services were partially mediated by psychological distance. Findings from a between-subject online experiment in Study 2 confirmed that embodied cognition and psychological distance play a parallel intermediary role in the impact of sensory affordance on adoption. In Study 3, a lab experiment in a VR-based digital museum context further verified that information overload moderates the influence of embodied cognition on psychological distance. This research reveals the deep-bounded, rational decision-making logic of digital heritage service adoption and provides significant practical enlightenment for the optimization of the affordance experience.

Six-month follow-up after recovery of COVID-19 Delta variant survivors via CT-based deep learning.

Purpose: Using computer-aided diagnosis (CAD) methods to analyze the discharge and 6-month follow-up data of COVID-19 Delta variant survivors, evaluate and summarize the recovery and prognosis, and improve people's awareness of this disease. Methods: This study collected clinical data, SGRQ questionnaire results, and lung CT scans (at both discharge and 6-month follow-up) from 41 COVID-19 Delta variant survivors. Two senior radiologists evaluated the CT scans before in-depth analysis. Deep lung parenchyma enhancing (DLPE) method was used to accurately segment conventional lesions and sub-visual lesions in CT images, and then quantitatively analyze lung injury and recovery. Patient recovery was also measured using the SGRQ questionnaire. The follow-up examination results from this study were combined with those of the original COVID-19 for further comparison. Results: The participants include 13 males (31.7%) and 28 females (68.3%), with an average age of 42.2 ± 17.7 years and an average BMI of 25.2 ± 4.4 kg/m2. Compared discharged CT and follow-up CT, 48.8% of survivors had pulmonary fibrosis, mainly including irregular lines (34.1%), punctuate calcification (12.2%) and nodules (12.2%). Compared with discharged CT, the ground-glass opacity basically dissipates at follow-up. The mean SGRQ score was 0.041 (0-0.104). The sequelae of survivors mainly included impaired sleep quality (17.1%), memory decline (26.8%), and anxiety (21.9%). After DLPE process, the lesion volume ratio decreased from 0.0018 (0.0003, 0.0353) at discharge to 0.0004 (0, 0.0032) at follow-up, p < 0.05, and the absorption ratio of lesion was 0.7147 (-1.0303, 0.9945). Conclusion: The ground-glass opacity of survivors had dissipated when they were discharged from hospital, and a little fibrosis was seen in CT after 6-month, mainly manifested as irregular lines, punctuate calcification and nodules. After DLPE and quantitative calculations, we found that the degree of fibrosis in the lungs of most survivors was mild, which basically did not affect lung function. However, there are a small number of patients with unabsorbed or increased fibrosis. Survivors mainly had non-pulmonary sequelae such as impaired sleep quality and memory decline. Pulmonary prognosis of Delta variant patients was better than original COVID-19, with fewer and milder sequelae.

COVID-19 susceptibility and clinical outcomes in inflammatory bowel disease: An updated systematic review and meta-analysis.

The susceptibility, risk factors, and prognosis of COVID-19 in patients with inflammatory bowel disease (IBD) remain unknown. Thus, our study aims to assess the prevalence and clinical outcomes of COVID-19 in IBD. We searched PubMed, EMBASE, and medRxiv from 2019 to 1 June 2022 for cohort and case-control studies comparing the prevalence and clinical outcomes of COVID-19 in patients with IBD and in the general population. We also compared the outcomes of patients receiving and not receiving 5-aminosalicylates (ASA), tumour necrosis factor antagonists, biologics, systemic corticosteroids, or immunomodulators for IBD. Thirty five studies were eligible for our analysis. Pooled odds ratio of COVID-19-related hospitalisation, intensive care unit (ICU) admission, or death in IBD compared to in non-IBD were 0.58 (95% confidence interval (CI) = 0.28-1.18), 1.09 (95% CI = 0.27-4.47), and 0.67 (95% CI = 0.32-1.42), respectively. Inflammatory bowel disease was not associated with increased hospitalisation, ICU admission, or death. Susceptibility to COVID-19 did not increase with any drugs for IBD. Hospitalisation, ICU admission, and death were more likely with 5-ASA and corticosteroid use. COVID-19-related hospitalisation (Odds Ratio (OR): 0.53; 95% CI = 0.38-0.74) and death (OR: 0.13; 95% CI = 0.13-0.70) were less likely with Crohn's disease than ulcerative colitis (UC). In conclusion, IBD does not increase the mortality and morbidity of COVID-19. However, physicians should be aware that additional monitoring is needed in UC patients or in patients taking 5-ASA or systemic corticosteroids.

Effectiveness and Safety of COVID-19 Vaccination in Patients with Malignant Disease.

A novel virus named SARS-CoV-2 has caused a worldwide pandemic, resulting in a disastrous impact to the public health since 2019. The disease is much more lethal among patients with malignant disease. Vaccination plays an important role in the prevention of infection and subsequent severe COVID-19. However, the efficacy and safety of vaccines for cancer patients needs further investigation. Encouragingly, there have been important findings deduced from research so far. In this review, an overview of the immunogenicity, effectiveness, and safeness of COVID-19 vaccines in patients with cancer to date is to be shown. We also highlight important questions to consider and directions that could be followed in future research.

The Effect of the COVID-19 Pandemic on Digital Health-Seeking Behavior: Big Data Interrupted Time-Series Analysis of Google Trends.

BACKGROUND: Due to the emergency responses early in the COVID-19 pandemic, the use of digital health in health care increased abruptly. However, it remains unclear whether this introduction was sustained in the long term, especially with patients being able to decide between digital and traditional health services once the latter regained their functionality throughout the COVID-19 pandemic. OBJECTIVE: We aim to understand how the public interest in digital health changed as proxy for digital health-seeking behavior and to what extent this change was sustainable over time. METHODS: We used an interrupted time-series analysis of Google Trends data with break points on March 11, 2020 (declaration of COVID-19 as a pandemic by the World Health Organization), and December 20, 2020 (the announcement of the first COVID-19 vaccines). Nationally representative time-series data from February 2019 to August 2021 were extracted from Google Trends for 6 countries with English as their dominant language: Canada, the United States, the United Kingdom, New Zealand, Australia, and Ireland. We measured the changes in relative search volumes of the keywords online doctor, telehealth, online health, telemedicine, and health app. In doing so, we capture the prepandemic trend, the immediate change due to the announcement of COVID-19 being a pandemic, and the gradual change after the announcement. RESULTS: Digital health search volumes immediately increased in all countries under study after the announcement of COVID-19 being a pandemic. There was some variation in what keywords were used per country. However, searches declined after this immediate spike, sometimes reverting to prepandemic levels. The announcement of COVID-19 vaccines did not consistently impact digital health search volumes in the countries under study. The exception is the search volume of health app, which was observed as either being stable or gradually increasing during the pandemic. CONCLUSIONS: Our findings suggest that the increased public interest in digital health associated with the pandemic did not sustain, alluding to remaining structural barriers. Further building of digital health capacity and developing robust digital health governance frameworks remain crucial to facilitating sustainable digital health transformation.

Simultaneous determination of twenty-nine active compounds in fuzhengjiedu granules by HPLC-QQQ-MS/MS.

As an empirical medicine of traditional Chinese medicine, Fuzhengjiedu Granules have shown an effect against COVID-19 in clinical and inflammatory animal models. It is formulated with eight herbs, including Aconiti Lateralis Radix Praeparata, Zingiberis Rhizoma, Glycyrrhizae Radix Et Rhizoma, Lonicerae Japonicae Flos, Gleditsiae Spina, Fici Radix, Pogostemonis Herba, and Citri Reticulatae Pericarpium. This study established a high-performance liquid chromatography-triple quadrupole mass spectrometry (HPLC-QQQ-MS/MS) method by simultaneously determining 29 active compounds in the granules with significant content differences. Separation by gradient elution using acetonitrile and water (0.1% formic acid) as mobile phases was performed on a Waters Acquilty UPLC T3 column (2.1 mm × 100 mm, 1.7 µm). A triple quadrupole mass spectrometer, operating in positive and negative ionization modes, was used for multiple reaction monitoring to detect the 29 compounds. All calibration curves showed good linear regression (r2 > 0.998). RSDs of precision, reproducibility, and stability of active compounds were all lower than 5.0%. The recovery rates were 95.4-104.9%, with RSDs< 5.0%. This method was successfully used to analyze the samples, and the results showed that 26 representative active components from 8 herbs were detected in the granules. While aconitine, mesaconitine, and hypaconitine were not detected, indicating that the existing samples were safe. The granules had the maximum and minimum content of hesperidin (27.3 ± 0.375 mg/g) and benzoylaconine (38.2 ± 0.759 ng/g). To conclude, a fast, accurate, sensitive, and reliable HPLC-QQQ-MS/MS method was established, which can simultaneously detect 29 active compounds that have a considerable difference in the content of Fuzhengjiedu Granules. This study can be used to control the quality and safety of Fuzhengjiedu Granules and provide a basis and guarantee for further experimental research and clinical application.

Analysis on the energy efficiency, thermal performance and infection intervention characteristics of interactive cascade ventilation (ICV)

Floor radiation (FR) is one of the widely used heating modes in winter. However, the widespread and high outbreak of Corona Virus Disease 2019 (COVID-19) has made the disadvantage of floor radiation that lacks fresh air and air movement exposed as a deficiency. To seek a heating mode that can realize a comfortable and healthy indoor environment with low cost, the interactive cascade ventilation (ICV) coupling with multiple low-grade sources was proposed in this study. Energy efficiency, thermal comfort and air quality were investigated by comparing with FR and floor radiation with mixing ventilation (FRMV). The results showed that by elevating the same indoor temperature, ICV can reduce indoor heat transfer by 28.41% and 30.94% than FR and FRMV, respectively. And ICV also presented the highest system COP by introducing multiple low-grade sources. In terms of thermal comfort, the indoor environment served by ICV was closer to thermal neutrality, and the subjective thermal comfort can also be enhanced by 10% and 8% relative to FR and FRMV. The CO2 test results indicated that by introducing the ICV, indoor air quality can be improved by 36.68% and 61.45% over FR and FRMV with the contaminant removal rate significantly accelerated. During the pandemic, ICV can reduce the COVID-19 infection rate by 9.6% and 55.5% within 8 h and 30 min compared with FRMV. The conclusions obtained in this paper can provide new ideas for designing air conditioning systems in the epidemic and the context of carbon reduction.

Epidemiological, clinical, and household transmission characteristics of children and adolescents infected with SARS-CoV-2 Omicron variant in Shanghai, China: a retrospective, multicenter observational study.

OBJECTIVES: To describe the epidemiological, clinical, and household transmission characteristics of pediatric COVID-19 cases in Shanghai, China. METHODS: Pediatric patients with COVID-19 hospitalized in Shanghai from March-May 2022 were enrolled in this retrospective, multicenter cohort study. The symptoms and the risk factors associated with disease severity were analyzed. RESULTS: In total, 2620 cases (age range, 24 days-17 years) were enrolled in this study. Of these, 1011 (38.6%) were asymptomatic, whereas 1415 (54.0%), 190 (7.3%), and 4 (0.2%) patients developed mild, moderate, and severe illnesses, respectively. Household infection rate was negatively correlated with household vaccination coverage. Children aged 0-3 years, those who are unvaccinated, those with underlying diseases, and overweight/obese children had a higher risk of developing moderate to severe disease than children aged 12-17 years, those who were vaccinated, those without any underlying disease, and those with normal weight, respectively (all P <0.05). A prolonged duration of viral shedding was associated with disease severity, presence of underlying diseases, vaccination status, and younger age (all P <0.05). CONCLUSION: Children aged younger than 3 years who were not eligible for vaccination had a high risk of developing moderate to severe COVID-19 with a prolonged duration of viral shedding. Vaccination could protect children from COVID-19 at the household level.

Investigation on the cross-infection control performance of interactive cascade ventilation in multi-scenario of winter

With the wide spread of COVID-19, numerous cases demonstrate that proper ventilation method can reduce the cross-infection risk obviously. Interactive cascade ventilation (ICV) as a recently proposed ventilation method, the advantage of indoor environment construction has been proven. However, few studies are conducted to investigate the virus prevention and control characteristics of ICV, which is particularly important under epidemic normalizing. Hence, this study explored and compared the cross-infection control performance of three ventilation strategies, namely mixing ventilation (MV), stratum ventilation (SV), and interactive cascade ventilation (ICV), with a validated CFD model. A typical office was selected as the background scene, where an infected person coughs, sneezes with standing or sitting at different positions. Exposure doses, health infection risk, and disease burden (DB) were employed as the evaluation indicators under different ventilation methods of multi-scenario. The research results indicated that the average aerosol exposure dose among the human respiratory region under ICV was 0.29 g/day, which was reduced by 67 % and 50 % compared with MV and SV. In addition, only in ICV can the health infection risk meets the EPA standard. The average disease health burden for exposed persons under ICV was 0.93 × 10−6 DALYs pppy, which was 37 % and 70 % lower than SV and MV. The findings obtained from this study confirm that ICV performs excellently in reducing the cross-infection risk, providing the theoretical basis for future epidemic prevention and control.

Mental health during the COVID-19 pandemic: Impacts of disease, social isolation, and financial stressors.

BACKGROUND: Although research shows that the Covid-19 pandemic has led to declines in mental health, the existing research has not identified the pathways through which this decline happens. AIMS: The current study identifies the distinct pathways through which COVID-induced stressors (i.e., social distancing, disease risk, and financial stressors) trigger mental distress and examines the causal impact of these stressors on mental distress. METHODS: We combined evidence of objective pandemic-related stressors collected at the county level (e.g., lack of social contact, infection rates, and unemployment rates) with self-reported survey data from over 11.5 million adult respondents in the United States collected daily for eight months. We used mediation analysis to examine the extent to which the objective stressors influenced mental health by influencing individual respondents' behavior and fears. RESULTS: County-level, day-to-day social distancing predicted significantly greater mental distress, both directly and indirectly through its effects on individual social contacts, worries about getting ill, and concerns about finances. Economic hardships were indirectly linked to increased mental distress by elevating people's concerns about their household's finances. Disease threats were both directly linked to mental distress and indirectly through its effects on individual worries about getting ill. Although one might expect that social distancing from people outside the home would have a greater influence on people who live alone, sub-analyses based on household composition do not support this expectation. CONCLUSION: This research provides evidence consistent with the thesis that the COVID-19 pandemic harmed the mental well-being of adults in the United States and identifies specific stressors associated with the pandemic that are responsible for increasing mental distress.

Pricing Extreme Mortality Risk in the Wake of the COVID-19 Pandemic

In pricing extreme mortality risk, it is commonly assumed that interest rate and mortality rate are independent. However, the COVID-19 pandemic calls this assumption into question. In this paper, we employ a bivariate affine jump-diffusion model to describe the joint dynamics of interest rate and excess mortality, allowing for both correlated diffusions and joint jumps. Utilizing the latest U.S. mortality and interest rate data, we find a significant negative correlation between interest rate and excess mortality, and a much higher jump intensity when the pandemic experience is considered. Moreover, we construct a risk-neutral pricing measure that accounts for both diffusion and jump risk premia, and we solve for the market prices of risk based on mortality bond prices. Our results show that the pandemic experience can drastically change investors' perception of the mortality risk market in the post-pandemic era.

Mental health symptoms and sleep quality of asymptomatic/mild SARS-CoV-2 infected individuals during the Omicron wave of the COVID-19 pandemic in Shanghai China.

OBJECTIVE: To investigate mental health symptoms (anxiety, depression, and sleep status) and their associated factors among people infected with the SARS-CoV-2 omicron variant during the quarantine period in Shanghai. METHODS: To investigate the mental health symptoms among participants with SARS-CoV-2 omicron infection, an anonymous online survey questionnaire was used. The survey panel included the 9-item Patient Health Questionnaire-9 (PHQ-9), 7-item Generalized Anxiety Disorder Scale (GAD-7), Pittsburgh Sleep Quality Index (PSQI), and 22-item Ruminative Responses Scale (RRS). Group comparisons and correlation analyses were employed to explore the epidemiological characteristics of patients and factors related to depression and anxiety symptoms. RESULTS: A total of 960 participants completed the survey. Of the total respondents, 583 participants (60.7%) were male, and the mean (SD) age was 34.33 (9.21) years (95% CI: 33.74-34.91). The prevalence of depressive and anxiety symptoms among the participants was 13.7% (n = 151, 95% CI: 11.6%-15.7%) and 8.6% (n = 90, 95% CI: 6.9%-10.3%), respectively. Age-stratified analysis showed that the prevalence of anxiety among the 36- to 45-year-old group (12.9%; n = 35, 8.9%-16.9%) was significantly higher than that of the 18- to 15-year-old group (7.4%; n = 42, 5.3%-9.6%, p = .011). Spearman's correlation analyses showed that rumination (assessed by the RRS) was significantly and positively correlated with depression (rho = .706, p < .001) and anxiety symptoms (rho = .758, p < .001). CONCLUSION: The results suggest that female and middle-aged populations manifest higher susceptibility to mental health distress during the current Omicron wave of the COVID-19 pandemic. Population-specific psychological crisis intervention is warranted to improve the quality of epidemic prevention methods and to promote the mental well-being of the public.