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Viral immunosuppression substantially affects the host immune response of infected patients and the protective efficacy of vaccines. Here, we found that the spike (S) protein, the major vaccine antigen of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), strongly suppresses host innate immunity by inhibiting interferon-stimulated gene (ISG) expression through both S1 and S2 subunits. Mechanistically, the S protein inhibited the formation of the classic interferon-stimulated gene factor 3 (ISGF3) complex composed of STAT1, STAT2, and IRF9 by competing with STAT2 for binding to IRF9, thereby impeding the transcription of ISGs. A strong interaction between S and the STAT1/STAT2 proteins further traps the ISGF3 complex in the endoplasmic reticulum and hinders the nuclear translocation of ISGF3. Notably, the interferon-inhibitory mechanism of the S protein was universal among SARS-CoV-2 variants and other human coronaviruses, including SARS-CoV, Middle East respiratory syndrome coronavirus (MERS-CoV), human coronavirus 229E (HCoV-229E), human coronavirus NL63 (HCoV-NL63), and human coronavirus HKU1 (HCoV-HKU1), through the most evolutionarily conserved region of S2 subunit. Taken together, the findings of this study reveal a new mechanism by which the coronavirus S protein attenuates the host antiviral immune response and provides new insights into the proper design of coronavirus S-based vaccines to prevent immunosuppressive effects., Importance: This study unveils a new mechanism by which the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike (S) protein attenuates the host's antiviral immune response. The interferon-inhibitory mechanism of the S protein was universal among SARS-CoV-2 variants and other human coronaviruses, including SARS-CoV, MERS-CoV, HCoV-229E, HCoV-NL63, and HCoV-HKU1, through conserved S2 domains. Our study expands the understanding of SARS-CoV-2 and other human coronaviruses in evading antiviral immune strategies, which is very important for the design and optimization of vaccine antigens, thus providing a theoretical basis for human anti-coronavirus immunity and understanding the interaction between the host and coronavirus., Competing Interests: The authors declare no conflict of interest.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has posed enormous challenges to global public health. The use of antibiotics has greatly increased during the SARS-CoV-2 epidemic owing to the presence of bacterial co-infection and secondary bacterial infections. The antibiotics daptomycin (DAP) is widely used in the treatment of infectious diseases caused by gram-positive bacteria owing to its highly efficient antibacterial activity. It is pivotal to study the antibiotics usage options for patients of coronavirus infectious disease (COVID-19) with pneumonia those need admission to receive antibiotics treatment for bacterial co-infection in managing COVID-19 disease. Herein, we have revealed the interactions of DAP with the S protein of SARS-CoV-2 and the variant Omicron (B1.1.529) using the molecular docking approach and Omicron (B1.1.529) pseudovirus (PsV) mimic invasion. Molecular docking analysis shows that DAP has a certain degree of binding ability to the S protein of SARS-CoV-2 and several derived virus variants, and co-incubation of 1-100 μM DAP with cells promotes the entry of the PsV into human angiotensin-converting enzyme 2 (hACE2)-expressing HEK-293T cells (HEK-293T-hACE2), and this effect is related to the concentration of extracellular calcium ions (Ca 2+ ). The PsV invasion rate in the HEK-293T-hACE2 cells concurrently with DAP incubation was 1.7 times of PsV infection alone. In general, our findings demonstrate that DAP promotes the infection of PsV into cells, which provides certain reference of antibiotics selection and usage optimization for clinicians to treat bacterial coinfection or secondary infection during SARS-CoV-2 infection.

Multivalent antigen display on nanoparticles can enhance the immunogenicity of nanovaccines targeting viral moieties, such as the receptor binding domain (RBD) of SARS-CoV-2. However, particle morphology and size of current nanovaccines are significantly different from those of SARS-CoV-2. Additionally, surface antigen patterns are not controllable to enable the optimization of B cell activation. Herein, we employ an icosahedral DNA origami (ICO) as a display particle for RBD nanovaccines, achieving morphology and diameter like the virus (91 ± 11 nm). The surface addressability of DNA origami permits facile modification of the ICO surface with numerous RBD antigen clusters (ICO-RBD) to form various antigen patterns. Using an in vitro screening system, we demonstrate that the antigen spacing, antigen copies within clusters and cluster number parameters of the surface antigen pattern all impact the ability of the nanovaccines to activate B cells. Importantly, the optimized ICO-RBD nanovaccines evoke stronger and more enduring humoral and T cell immune responses in female mouse models compared to soluble RBD antigens, and the multivalent display broaden the protection range of B cell responses to more mutant strains. Our vaccines activate similar humoral immunity, observable stronger cellular immunity and more memory immune cells compared to trimeric mRNA vaccines., (© 2024. The Author(s).)

Background: In this study, we aimed to identify bone mineral density (BMD) trajectories of hospitalised patients with coronavirus disease 2019 (COVID-19) and to determine the prognostic role of the trajectory groups., Methods: This is a retrospective study of hospitalised patients with COVID-19 treated in our hospital from November 2022 to February 2023. BMD was manually measured from the thoracic 12 (T12) and lumbar one (L1) vertebra using chest computed tomography images. We constructed group trajectory models using group-based trajectory modelling. We performed the logistic regression analysis to associate the BMD trajectory pattern with clinical outcomes., Results: This study included 1767 patients. The mean follow-up time after discharge was 181.5 days (standard deviation (SD) = 9.7). There were 1137 (64.3%) male patients, and more than 80% of patients were aged >60 years. We successfully identified three latent BMD trajectories to reveal the dynamic effects of COVID-19 infection on bone health in patients, namely, the early low-normal decline group, the average, and the early high-rapid decline group. All groups demonstrated consistent overall declining trends. A significant association was observed between BMD trajectory pattern (T12 or L1) and baseline characteristics of sex, age, and penetrating keratoplasty (P < 0.05). Our study showed that the BMD trajectories were significantly associated with mortality. Furthermore, we found that these trajectories were also associated with the length of hospital stay., Conclusions: This study provided evidence for the COVID-19 process to bone health, as well as evidence on strengthening bone health management before and after COVID-19 infection. BMD trajectories may help manage bone health and guide treatment in patients with COVID-19., Competing Interests: Disclosure of interest: The authors completed the ICMJE Disclosure of Interest Form (available upon request from the corresponding author) and disclose no relevant interests., (Copyright © 2024 by the Journal of Global Health. All rights reserved.)

Background: The COVID-19 pandemic resulted in greater use of remote patient monitoring (RPM). However, the use of RPM has been modest compared to other forms of telehealth., Objective: To identify and describe barriers to the implementation of RPM among primary care physicians (PCPs) that may be constraining its growth., Design: We conducted 20 semi-structured interviews with PCPs across the USA who adopted RPM. Interview questions focused on implementation facilitators and barriers and RPM's impact on quality. We conducted thematic analysis of semi-structured interviews using both inductive and deductive approaches. The analysis was informed by the NASSS (non-adoption and abandonment and challenges to scale-up, spread, and sustainability) framework., Participants: PCPs who practiced at least 10 h per week in an outpatient setting, served adults, and monitored blood pressure and/or blood glucose levels with automatic transmission of data with at least 3 patients., Key Results: While PCPs generally agreed that RPM improved quality of care for their patients, many identified barriers to adoption and maintenance of RPM programs. Challenges included difficulties handling the influx of data and establishing a manageable workflow, along with digital and health literacy barriers. In addition to these barriers, many PCPs did not believe RPM was profitable., Conclusions: To encourage ongoing growth of RPM, it will be necessary to address implementation barriers through changes in payment policy, training and education in digital and health literacy, improvements in staff roles and workflows, and new strategies to ensure equitable access., (© 2024. The Author(s).)

Objective: Since January 8, 2023, China has managed COVID-19 as a Class-B infectious disease, marking the epidemic's transition to a low-level stage. This study analyzes the relationship between the public's perceived a community with shared future for doctor-patient (PCSF), health self-consciousness, benefit finding, and anxiety in this stage. Additionally, it compares changes in these variables across different stages of COVID-19., Methods: Using a repeated cross-sectional design, three surveys were conducted respectively in three different stages of COVID-19 in China. Specifically, the first survey was conducted in Beijing, Dalian, Zhengzhou, Heihe, and Shangrao from November 13 to 20, 2021 in the outbreak stage of COVID-19, yielding 1,252 valid responses out of 1,534 collected questionnaires. The second survey was conducted in Dalian, Zhengzhou, Heihe, Shangrao, and Lanzhou from December 1 to 19, 2021 in the stable stage of COVID-19, with 872 valid responses obtained from 1,075 collected questionnaires. The third survey was conducted in Beijing, Dalian, Zhengzhou, Heihe, Shangrao, Lanzhou, and Chengdu from January 29 to February 4, 2023 in the low epidemic level stage of COVID-19, achieving 2,113 valid responses from the 2,461 questionnaires collected., Results: Unlike in the outbreak stage but similar to the stable stage, the public's anxiety, health self-consciousness and benefit finding decreased while PCSF was improved in the low epidemic level stage. Consistent with both the outbreak and stable stage, PCSF, health self-consciousness, benefit finding, and anxiety showed positive correlations in the low epidemic level stage, with health self-consciousness partially mediating the positive impact of PCSF on benefit finding. Unlike in the stable stage but similar to the outbreak stage, anxiety did not moderate the relationship between PCSF and health self-consciousness in the low epidemic level stage., Conclusions: The public's health self-consciousness, benefit finding, and anxiety decreased, while PCSF increased in the low epidemic level stage. Furthermore, PCSF had a greater impact on benefit finding, and anxiety's impact on health self-consciousness was significantly reduced. Across different stages of COVID-19, PCSF directly increased benefit finding and also enhanced benefit finding by improving health self-consciousness. Thus, comprehensive intervention measures are beneficial in the low epidemic level stage., (© 2024. The Author(s).)

Background: During the COVID-19 pandemic, teledermatology became a popular mode of health care delivery. Thus, deciphering which diagnoses are best suited for synchronous video visits is important to guide providers on appropriate patient care. Methods: We conducted a retrospective study of 1,647 submitted synchronous video visits from September 1, 2020 to March 31, 2021 at a single, large academic institution. Results: Video visits' follow-up rate was significantly associated with diagnosis subtype ( p < 0.001). Compared with patients with skin lesions and nonskin dermatologic conditions, patients with a rash had higher odds of being recommended to have their follow-up visit as a video visit (odds ratio [OR] = 0.222, p < 0.001; OR = 0.296, p < 0.001). Patients with a rash had lower odds of being recommended to have their follow-up visit as an in-person office visit when compared with skin lesions (OR = 9.679, p < 0.001), nonskin dermatologic conditions (OR = 4.055, p < 0.001), and other skin dermatologic conditions (OR = 2.23, p < 0.01). Demographically, employed, middle-aged patients with private insurance made up the majority of video visit usage. African American patients were less likely to utilize a video visit compared with Asian patients (OR = 2.06, p < 0.038). Conclusions: Certain dermatologic diagnoses, most notably rashes, are more conducive to video visit management. Rashes made up 86% of new patient video visits, were more likely to have video visit follow-up if needed and were more likely to not require further follow-up indicating that the management of rashes from initial diagnosis to completion in care is suitable for video visit management.

Background: Since December 2022, the Omicron variant has led to a widespread pandemic in China. The study was to explore the safety and effectiveness of Paxlovid for the treatment of coronavirus disease 2019 (COVID-19)., Research Design and Methods: We included patients at risk of developing severe COVID-19, all of whom exhibited mild to moderate symptoms and were admitted to three hospital centers. Patients were divided into two groups: one received Paxlovid alongside standard care, while the other was given only standard care. We compared clinical characteristics, hospital stay duration, and clinical outcomes between two groups. Multi-factor analysis determined the independent risk factors influencing the duration of hospitalization and disease progression., Results: In the study, those treated with Paxlovid shorter hospital stays than those in the control group ( p  < 0.001). Multivariate analysis indicated that the absence of Paxlovid treatment was a distinct risk factor for hospitalizations lasting over 7 days (OR: 4.983, 95% CI: 3.828-6.486, p  < 0.001) and 14 days (OR: 2.940, 95% CI: 2.402-3.597, p  < 0.001)., Conclusion: Amid the Omicron outbreak, Paxlovid has proven to be a safe and effective treatment for reducing hospitalization durations for patients with mild to moderate COVID-19.

Objectives: Prolonged distress is a risk factor for burnout among health-care providers (HCP) and may contribute to demoralization. We examined sources of distress during the COVID-19 pandemic and associations with demoralization., Methods: This prospective cross-sectional survey of HCP was conducted among palliative care providers of an academic medical center. Participants completed a survey evaluating sources of distress and the Demoralization Scale-II (DS-II) to measure the intensity of demoralization., Results: Of 106 eligible participants, 74 (70%) completed the survey. DS-II median (range) score was 2 (0-19). There were no statistically significant associations with demographic characteristics. Participants reported high rates of distress for multiple reasons and high rates of sense of fulfillment (90%) and satisfaction (89%) with their profession., Significance of Results: Our study identified high levels of distress but low demoralization rates. Further study to evaluate fulfillment and satisfaction as protective factors against demoralization and burnout is indicated.

The current coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus (SARS-CoV-2) remains a threat to pregnant women. However, the impact of early pregnancy SARS-CoV-2 infection on the maternal-fetal interface remains poorly understood. Here, we present a comprehensive analysis of single-cell transcriptomics and metabolomics in placental samples infected with SARS-CoV-2 during early pregnancy. Compared to control placentas, SARS-CoV-2 infection elicited immune responses at the maternal-fetal interface and induced metabolic alterations in amino acid and phospholipid profiles during the initial weeks post-infection. However, subsequent immune cell activation and heightened immune tolerance in trophoblast cells established a novel dynamic equilibrium that mitigated the impact on the maternal-fetal interface. Notably, the immune response and metabolic alterations at the maternal-fetal interface exhibited a gradual decline during the second trimester. Our study underscores the adaptive immune tolerance mechanisms and establishment of immunological balance during the first two trimesters following maternal SARS-CoV-2 infection., (© The Author(s) 2024. Published by Oxford University Press on behalf of Higher Education Press.)

The increasing demand for personal protective equipment such as single-use masks has led to large amounts of nondegradable plastic waste, aggravating economic and environmental burdens. This study reports a simple and scalable approach for upcycling waste masks via a chemical vapor deposition technique, realizing a trichome-like biomimetic (TLB) N95 respirator with superhydrophobicity (water contact angle ≥150°), N95-level protection, and reusability. The TLB N95 respirator comprising templated silicone nanofilaments with an average diameter of ∼150 nm offers N95-level protection and breathability comparable to those of commercial N95 respirators. The TLB N95 respirator can still maintain its N95-level protection against particulate matter and viruses after 10 disinfection treatment cycles (i.e., ultraviolet irradiation, microwave irradiation, dry heating, and autoclaving), demonstrating durable reusability. The proposed strategy provides new insight into upcycle waste masks, breaking the existing design and preparation concept of reusable masks.

Background: The CDC and ACIP recommend COVID-19 vaccination for patients with inborn errors of immunity (IEI). Not much is known about vaccine safety in IEI, and whether vaccination attenuates infection severity in IEI., Objective: To estimate COVID-19 vaccination safety and examine effect on outcomes in patients with IEI., Methods: We built a secure registry database in conjunction with the US Immunodeficiency Network to examine vaccination frequency and indicators of safety and effectiveness in IEI patients. The registry opened on January 1, 2022, and closed on August 19, 2022., Results: Physicians entered data on 1245 patients from 24 countries. The most common diagnoses were antibody deficiencies (63.7%). At least one COVID-19 vaccine was administered to 806 patients (64.7%), and 216 patients received vaccination prior to the development of COVID-19. The most common vaccines administered were mRNA-based (84.0%). Seventeen patients were reported to seek outpatient clinic or emergency room care for a vaccine-related complication, and one patient was hospitalized for symptomatic anemia. Eight hundred twenty-three patients (66.1%) experienced COVID-19 infection. Of these, 156 patients required hospitalization (19.0%), 47 required ICU care (5.7%), and 28 died (3.4%). Rates of hospitalization (9.3% versus 24.4%, p < 0.001), ICU admission (2.8% versus 7.6%, p = 0.013), and death (2.3% versus 4.3%, p = 0.202) in patients who had COVID-19 were lower in patients who received vaccination prior to infection. In adjusted logistic regression analysis, not having at least one COVID-19 vaccine significantly increased the odds of hospitalization and ICU admission., Conclusion: Vaccination for COVID-19 in the IEI population appears safe and attenuates COVID-19 severity., (© 2024. The Author(s).)

Background: The global coronavirus disease 2019 (COVID-19) pandemic seriously affected people's lives. We evaluated anxiety and depression among patients with insomnia in northeast China during the first wave and release of COVID-19, providing a basis for the clinical diagnosis and treatment of insomnia., Methods: We enrolled 4211 patients with insomnia from January 2016 to February 2020, August 2020 to February 2022, August 2022 to December 2022, and January 2023 to February 2023, from our institution. Sleep quality was evaluated using the Athens Insomnia Scale, Insomnia Severity Index (ISI), and Pittsburgh sleep quality index (PSQI), while mood disorder and fatigue were evaluated using the Hhospital anxiety and depression scale (HAD), Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder (GAD-7), and Fatigue Scale-14 (FS-14)., Results: Insomnia with depression increased in prevalence after COVID-19 compared with before (12.8 % vs. 15.3 %, P < 0.05), while the age of patients decreased [(50.2 ± 15.2) vs. (47.5 ± 16.8), P < 0.05]. The number of patients with insomnia and severe depression increased compared with before COVID-19 (20.3 % vs. 25.3 %, P < 0.05). A higher proportion of patients with insomnia for >2 years had depression (P < 0.05). As the epidemic subsided, insomnia increased among young and male patients (young patients: 55.2 % vs. 37.0 %; male patients: 41 % vs. 27.4 %, respectively; P < 0.05). The proportion of patients with insomnia with anxiety and depression increased (53.8 % vs. 51.8 %，P < 0.05), the proportion with moderate to severe anxiety increased (7.6 % vs. 13.5 %, P < 0.05), and moderate and severe depression decreased (moderate: 25.6 % vs. 19.1 %, severe: 25.8 % vs. 20.3 %, P < 0.05, respectively). Middle-aged and elderly patients had higher PQSI scores in sleep latency, habitual sleep efficiency, subjective sleep quality, and use of sleep medications than young patients (P < 0.05). The PSQI score was positively correlated with the PHQ-9 score (r = 0.526), GAD-7 score (r = 0.563), and FS-14 score (r = 0.316) (P < 0.05)., Limitations: The study was single-center, the sample size was small, and assessment data were lacking from early in the epidemic. The scale is subjective, which may affect the accuracy., Conclusion: Insomnia with depression increased during COVID-19. The patients were younger than before the epidemic, and a higher proportion with insomnia for >2 years had depression. The proportion of patients with insomnia with anxiety and depression was higher after the epidemic period, and the degree worsened. The proportion of insomnia with depression decreased after the epidemic period, and the degree alleviated. The proportion of young male patients with insomnia increased. Middle aged and elderly patients with insomnia had poor sleep quality, which was positively correlated with anxiety, depression, and fatigue., Competing Interests: Declaration of competing interest We declare that we have no financial and personal relationships with other people or organizations that can inappropriately influence our work, and there is no professional or other personal interests of any nature or kind in any product, service and/or company that could be construed as influencing the position presented in, or the review of, the manuscript entitled., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Objectives: To identify risk factors that contribute to outbreaks of COVID-19 in the workplace and quantify their effect on outbreak risk., Methods: We identified outbreaks of COVID-19 cases in the workplace and investigated the characteristics of the individuals, the workplaces, the areas they work and the mode of commute to work, through data linkages based on Middle Layer Super Output Areas in England between 20 June 2021 and 20 February 2022. We estimated population-level associations between potential risk factors and workplace outbreaks, adjusting for plausible confounders identified using a directed acyclic graph., Results: For most industries, increased physical proximity in the workplace was associated with increased risk of COVID-19 outbreaks, while increased vaccination was associated with reduced risk. Employee demographic risk factors varied across industry, but for the majority of industries, a higher proportion of black/African/Caribbean ethnicities and living in deprived areas, was associated with increased outbreak risk. A higher proportion of employees in the 60-64 age group was associated with reduced outbreak risk. There were significant associations between gender, work commute modes and staff contract type with outbreak risk, but these were highly variable across industries., Conclusions: This study has used novel national data linkages to identify potential risk factors of workplace COVID-19 outbreaks, including possible protective effects of vaccination and increased physical distance at work. The same methodological approach can be applied to wider occupational and environmental health research., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Portable assays for the rapid identification of lineages of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are needed to aid large-scale efforts in monitoring the evolution of the virus. Here we report a multiplexed assay in a microarray format for the detection, via isothermal amplification and plasmonic-gold-enhanced near-infrared fluorescence, of variants of SARS-CoV-2. The assay, which has single-nucleotide specificity for variant discrimination, single-RNA-copy sensitivity and does not require RNA extraction, discriminated 12 lineages of SARS-CoV-2 (in three mutational hotspots of the Spike protein) and detected the virus in nasopharyngeal swabs from 1,034 individuals at 98.8% sensitivity and 100% specificity, with 97.6% concordance with genome sequencing in variant discrimination. We also report a compact, portable and fully automated device integrating the entire swab-to-result workflow and amenable to the point-of-care detection of SARS-CoV-2 variants. Portable, rapid, accurate and multiplexed assays for the detection of SARS-CoV-2 variants and lineages may facilitate variant-surveillance efforts., (© 2023. The Author(s), under exclusive licence to Springer Nature Limited.)

Background: Multifaceted non-pharmaceutical interventions during the COVID-19 pandemic have not only reduced the transmission of SARS-CoV2, but have had an effect on the prevalence of other pathogens. This retrospective study aimed to compare and analyze the changes of respiratory pathogens in hospitalized children with community-acquired pneumonia., Methods: From January 2019 to December 2020, children with community-acquired pneumonia were selected from the Department of Respiratory Medicine, Shanghai Children's Medical Center. On the first day of hospitalization, sputum, throat swabs, venous blood samples from them were collected for detection of pathogens., Results: A total of 2596 children with community-acquired pneumonia were enrolled, including 1871 patients in 2019 and 725 in 2020. The detection rate in 2020 was lower than in 2019, whether single or multiple pathogens. Compared with 2019, the detection rate of virus, especially parainfluenza virus, influenza virus and respiratory syncytial virus, all decreased in 2020. On the contrary, the prevalence of human rhinovirus was much higher than that in 2019. In addition, the positivity rate for bacteria did not change much over the two years, which seemed to be less affected by COVID-19. And Mycoplasma pneumoniae which broke out in 2019 has been in low prevalence since March 2020 even following the reopening of school., Conclusions: Strict public health interventions for COVID-19 in China have effectively suppressed the spread of not only SARS-CoV2 but parainfluenza virus, influenza virus and Mycoplasma pneumonia as well. However, it had a much more limited effect on bacteria and rhinovirus. Therefore, more epidemiological surveillance of respiratory pathogens will help improve early preventive measures., (© 2023. The Author(s).)

Background: Depression and anxiety are common comorbidities in cardiovascular clinic outpatients. Timely identification and intervention of these mental and psychological disorders can contribute to correct diagnosis, better prognosis, less medical expenses, and improved quality of life. The convenience of online doctor-patient communication platforms has increasingly attracted patients to online consultations. However, online health care and offline health care are very different. Research on how to identify psychological disorders in patients who engage in an online cardiology consultation is lacking., Objective: This study aimed to explore the feasibility of using a self-rating scale to assess mental illness among patients who consult with a cardiologist online and to compare the differences in anxiety and depression between online and offline patients., Methods: From June 2022 to July 2022, we conducted follow-up visits with 10,173 patients on the Haodf platform. We conducted detailed consultations with 286 patients who visited the same cardiologist in the outpatient department. We used the self-rated Generalized Anxiety Disorder (GAD-7) and Patient Health Questionnaire (PHQ-9) scales to assess anxiety and depression, respectively. We analyzed the influencing factors related to the degree of coordination of online patients. We also compared the prevalence of anxiety or depression between online and offline patients and analyzed the factors related to anxiety or depression., Results: Of the 10,173 online consultation patients, only 186 (1.8%) responded effectively. The response rate of the offline consultation patients was 96.5% (276/286). Frequent online communication and watching live video broadcasts were significantly related to effective responses from online patients (P<.001). The prevalence of anxiety (70/160, 43.7% vs 69/266, 25.8%; P<.001) or depression (78/160, 48.7% vs 74/266, 27.7%; P<.001) in online consultation patients was significantly higher than that in offline patients. In bivariate analyses, the factors related to anxiety included female sex, unemployment, no confirmed cardiovascular disease, and the online consultation mode, while smokers and those who underwent COVID-19 quarantine were less likely to present with anxiety. The factors related to depression included female sex, divorced or separated individuals, and the online consultation mode. COVID-19 quarantine was related with a lower likelihood of depression. BMI was negatively correlated with depression. In multiple ordered logistic regression analysis, women were more likely than men to present with anxiety (odds ratio [OR] 2.181, 95% CI 1.365-3.486; P=.001). Women (OR 1.664, 95% CI 1.082-2.559; P=.02) and online patients (OR 2.631, 95% CI 1.305-5.304; P=.007) were more likely to have depression., Conclusions: Online patients had more anxiety or depression than offline patients. Anxiety was more prevalent in women, the unemployed, and those without confirmed cardiovascular disease. Women and divorced or separated individuals were more prone to depression. Increasing the frequency of doctor-patient communication and participating in video interactions can help improve patient cooperation., (©Yongguang Li, Jue Cen, Junxia Wu, Min Tang, Jingyi Guo, Jingyu Hang, Qing Zhao, Gang Zhao, Xiaoli Huang, Beibei Han. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 04.10.2023.)

Background: The coronavirus disease 2019 (COVID-19) pandemic has exerted a profound influence on humans. Increasing evidence shows that immune response is crucial in influencing the risk of infection and disease severity. Observational studies suggest an association between COVID-19 and immunoglobulin G (IgG) N-glycosylation traits, but the causal relevance of these traits in COVID-19 susceptibility and severity remains controversial., Methods: We conducted a two-sample Mendelian randomization (MR) analysis to explore the causal association between 77 IgG N-glycosylation traits and COVID-19 susceptibility, hospitalization, and severity using summary-level data from genome-wide association studies (GWAS) and applying multiple methods including inverse-variance weighting (IVW), MR Egger, and weighted median. We also used Cochran's Q statistic and leave-one-out analysis to detect heterogeneity across each single nucleotide polymorphism (SNP). Additionally, we used the MR-Egger intercept test, MR-PRESSO global test, and PhenoScanner tool to detect and remove SNPs with horizontal pleiotropy and to ensure the reliability of our results., Results: We found significant causal associations between genetically predicted IgG N-glycosylation traits and COVID-19 susceptibility, hospitalization, and severity. Specifically, we observed reduced risk of COVID-19 with the genetically predicted increased IgG N-glycan trait IGP45 (OR = 0.95, 95% CI = 0.92-0.98; FDR = 0.019). IGP22 and IGP30 were associated with a higher risk of COVID-19 hospitalization and severity. Two (IGP2 and IGP77) and five (IGP10, IGP14, IGP34, IGP36, and IGP50) IgG N-glycosylation traits were causally associated with a decreased risk of COVID-19 hospitalization and severity, respectively. Sensitivity analyses did not identify any horizontal pleiotropy., Conclusions: Our study provides evidence that genetically elevated IgG N-glycosylation traits may have a causal effect on diverse COVID-19 outcomes. Our findings have potential implications for developing targeted interventions to improve COVID-19 outcomes by modulating IgG N-glycosylation levels., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Long, Xiao, Cui, Wang, Jiang, Tang, Zhang, Liu, Xiang, Zhang, Zhao, Yang, Yan, Wu, Wang, Zhou, Lu, Chen, Li, Jiang, Fan and Zhang.)

Background: Advanced age increases the risk for severe COVID-19. However, the risk factors for mortality from COVID-19 in very elderly patients (≥80-years-old) are unknown., Objective: Investigate the relationship of mortality with the clinical characteristics of very elderly COVID-19 patients., Materials and Methods: Very elderly patients who were hospitalized with COVID-19 from December 3, 2022 to January 1, 2023 were retrospectively examined. Sociodemographic and clinical variables were recorded and survival was recorded after 30 days., Results: We examined 181 patients (median age: 90.84 years; 114 older than 90 years). The median Barthel index was 30.69, and 55.8% of patients had severe or critical COVID-19 pneumonia. Forty-two patients (33.2%) received a high-flow nasal cannula or non-invasive ventilation, and only 4.4% received mechanical ventilation. The overall mortality was 35.9%, and there was no significant difference in mortality for the 80 to 90-year-old group and the over 90-year-old group (37.7% vs 32.8%, P =0.508). A multivariate analysis showed that the Barthel index (OR, 0.975; 95% CI, 0.962-0.989), serum creatinine (SCr) level (OR, 1.003; 95% CI, 1.000-1.006), white blood cell (WBC) count (OR, 1.160; 95% CI, 1.056-1.276), D-dimer level (OR, 1.060; 95% CI, 1.009-1.113), and corticosteroid use (OR, 0.268; 95% CI, 0.124-0.582) were significantly and independently related to 30-day mortality. A binary classification model based on the multivariate analysis had good predictive value (area under the curve, 0.794)., Conclusion: Very elderly COVID-19 patients have a high risk for mortality. The Barthel index, SCr, WBC count, D-dimer level, and corticosteroid use were independently associated with mortality., Competing Interests: No potential conflict of interest relevant to this article was reported., (© 2023 Xing et al.)

Thrombosis has been emerging as a major global life-threatening issue with high mortality and serious complications, especially in the post-COVID-19 era. Compared with the commonly used plasminogen activators thrombolytic drugs, fibrinolytic drugs are no longer heavily dependent on the patients' own plasminogen, which are poorly expressed in most patients. As a novel "direct acting" thrombolytic agent, fibrinolytic drugs are considered to have stronger thrombolytic efficacy and safety than the widely used plasminogen activators. However, the risk of their hemorrhage remains a major concern. Herein, the molecular mechanisms and solutions were summarized for the first time based on the systematic review of the latest developments, which could shed new light on the development of novel safety fibrinolytic drugs in the future., (Copyright © 2023 Wolters Kluwer Health, Inc. All rights reserved.)

The classical manifestation of COVID-19 is pulmonary infection. After host cell entry via human angiotensin-converting enzyme II (hACE2), the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus can infect pulmonary epithelial cells, especially the AT2 (alveolar type II) cells that are crucial for maintaining normal lung function. However, previous hACE2 transgenic models have failed to specifically and efficiently target the cell types that express hACE2 in humans, especially AT2 cells. In this study, we report an inducible, transgenic hACE2 mouse line and showcase three examples for specifically expressing hACE2 in three different lung epithelial cells, including AT2 cells, club cells, and ciliated cells. Moreover, all these mice models develop severe pneumonia after SARS-CoV-2 infection. This study demonstrates that the hACE2 model can be used to precisely study any cell type of interest with regard to COVID-19-related pathologies.

Background: Two years have passed since the 2019 novel coronavirus disease (COVID-19) was first reported. The persistent pandemic might lead to severe psychosomatic problems and fatigue. In addition, the recent rapid rising COVID-19 cases in China have become a trending issue. Therefore, this study aimed to investigate the dynamic changes in psychosomatic problems at the initial and current stages of the pandemic., Methods: Three waves of cross-sectional online survey were conducted during the initial COVID outbreak in China. The psychosomatic symptom scale (PSSS), perceived stress scale (PSS), and pandemic fatigue scale (PFS) were used to assess the psychosomatic problems, stress, and fatigue., Results: 4317, 1096, and 2172 participants completed the first, second, and third surveys. The prevalence of psychosomatic disorder was 22 %, 28 %, and 39 %, respectively. The network structure of PSSS symptoms has not significantly changed as the pandemic progresses. However, the global strength of the PSSS networks, indicating the overall connectivity, in the third wave was significantly higher than in the first wave (s = 0.54, P = 0.007). The most central symptoms in the first and third wave networks were depressed mood and tiredness. The PFS score was higher in the people concerned with indirect impact than those concerned with health (P < 0.001). PFS has positive relationships with PSSS and PSS score (R = 0.41, P < 0.001 and R = 0.35, P < 0.001, respectively)., Conclusions: The persistence of the pandemic caused critical psychosomatic issues, stress, and indirect burden over time, leading to inevitable fatigue. People endured needing immediate attention to prevent or reduce psychosomatic disorders., Competing Interests: Conflict of interest None of the authors have any conflicts of interest to declare., (Copyright © 2023. Published by Elsevier B.V.)

Background and Objective: 'Hearing loss' has been reported as a clinical atypical symptom in some COVID-19 patients. We searched and collated the existing literature for a systematic review and meta-analysis to assess the prevalence of hearing loss during the COVID-19 epidemic., Methods: An exhaustive search of the PubMed, Embase, Web of Science, China National Knowledge Infrastructure and other sources from the inception of the database until 31st December 2022. The Search terms were set to: 'COVID-19', 'SARS-CoV-2', '2019-nCoV', 'hearing impairment', 'hearing loss', 'auditory dysfunction'. The literature data meeting the inclusion criteria were extracted and analyzed. Prevalence was pooled from individual studies using a randomized effects meta-analysis., Results: A total of 22 studies were included in the final analysis, involving 14281 patients with COVID-19 infection, of which 482 patients had varying degrees of hearing loss. Our final meta-analysis demonstrated that the prevalence of hearing loss in COVID-19-positive patients was 8.2% (95%CI 5.0-12.1). Subgroup analysis of age showed that the prevalence of middle-aged and older patients aged 50-60 and over 60 years was 20.6% and 14.8%, respectively, which was significantly higher than that of patients aged 30-40 (4.9%) and 40-50 years (6.0%)., Conclusion: Hearing loss is one of the clinical symptoms of COVID-19 infection, compared with other diseases, it is less likely to attract the attention of clinical experts or researchers. Raising awareness of this disease can not only enable early diagnosis and treatment of hearing loss, and improve the quality of life of patients, but also enhance our vigilance against virus transmission, which has important clinical and practical significance.

Mask wearing and bleach disinfectants became commonplace during the COVID-19 pandemic. Bleach generates toxic species including hypochlorous acid (HOCl), chlorine (Cl 2 ), and chloramines. Their reaction with organic species can generate additional toxic compounds. To understand interactions between masks and bleach disinfection, bleach was injected into a ventilated chamber containing a manikin with a breathing system and wearing a surgical or KN95 mask. Concentrations inside the chamber and behind the mask were measured by a chemical ionization mass spectrometer (CIMS) and a Vocus proton transfer reaction mass spectrometer (Vocus PTRMS). HOCl, Cl 2 , and chloramines were observed during disinfection and concentrations inside the chamber are 2-20 times greater than those behind the mask, driven by losses to the mask surface. After bleach injection, many species decay more slowly behind the mask by a factor of 0.5-0.7 as they desorb or form on the mask. Mass transfer modeling confirms the transition of the mask from a sink during disinfection to a source persisting >4 h after disinfection. Humidifying the mask increases reactive formation of chloramines, likely related to uptake of ammonia and HOCl. These experiments indicate that masks are a source of chemical exposure after cleaning events occur.

Background: Coronavirus disease 2019 (COVID-19) has brought great challenges to the global public health system and huge economic burdens to society, the causal effect of COVID-19 and intraocular pressure was blank., Objective: This study aimed to explore the causal association between coronavirus disease (COVID-19) susceptibility, severity and criticality and intraocular pressure (IOP) by bidirectional Mendelian randomization (MR) analysis., Materials and Methods: Genetic associations with COVID-19 susceptibility, severity and criticality were obtained from the COVID-19 Host Genetics Initiative. Genetic associations with IOP were obtained from GWAS summary data. The standard inverse variance weighted (IVW) method was used in the primary assessment of this causality. Other methods were also implemented in supplementary analyses. Finally, sensitivity analysis was performed to evaluate the reliability and stability of the results., Results: The results showed that COVID-19 susceptibility had null effect on IOP (β = 0.131; Se = 0.211; P = 0.533) as assessed by the IVW method. Moreover, the results revealed that COVID-19 severity, specifically, hospitalization due to COVID-19, had a positive effect on IOP with nominal significance (β = 0.228; Se = 0.116; P = 0.049). However, there were null effect of COVID-19 criticality on IOP (β = 0.078; Se = 0.065; P = 0.227). Sensitivity analysis showed that all the results were reliable and stable. The reverse MR analysis revealed that there was null effect of IOP on COVID-19., Conclusions: We demonstrated that hospitalization due to COVID-19 might increase IOP; therefore, greater attention should be given to monitoring IOP in inpatients with COVID-19., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Lin, Jiang, Cai, Luo, Zheng, Zhu, Lin, Tang, Li and Xie.)

Aim: To examine effects of holistic sleep improvement strategies on frontline nurses who served in Wuhan, China, during a public health emergency (COVID-19)., Design: A pre-post-test design with single group was conducted with a convenience sample applied the Transparent Reporting of Evaluations with Non-randomized Designs statement., Methods: Fifty-two nurses were recruited from a COVID-19 designated hospital, receiving holistic sleep improvement intervention, which concentrated on scientific human resource management, comfortable sleep environment establishment, self-relaxation and self-adjustment training and humanistic care. Data was collected at baseline and 4-week follow-up post intervention using self-reported questionnaires., Results: The total score of Pittsburgh Sleep Quality Index scale was 8.69 ± 4.346 at baseline. After 4 weeks of follow-up, the score statistically significantly decreased to 7.48 ± 3.691. Subjective sleep quality (p = .016), sleep efficiency (p = .015), sleep disturbances (p = .007) were statistically significantly improved after the intervention, while there were no statistically significant differences in sleep latency (p = .205), sleep duration (p = .375), sleep medication (p = .723) or daytime dysfunction (p = .747)., (© 2022 The Authors. Nursing Open published by John Wiley & Sons Ltd.)

The COVID-19 pandemic has provided stiff challenges for planning and resourcing in health services in the UK and worldwide. Epidemiological models can provide simulations of how infectious disease might progress in a population given certain parameters. We adapted an agent-based model of COVID-19 to inform planning and decision-making within a healthcare setting, and created a software framework that automates processes for calibrating the model parameters to health data and allows the model to be run at national population scale on National Health Service (NHS) infrastructure. We developed a method for calibrating the model to three daily data streams (hospital admissions, intensive care occupancy, and deaths), and demonstrate that on cross-validation the model fits acceptably to unseen data streams including official estimates of COVID-19 incidence. Once calibrated, we use the model to simulate future scenarios of the spread of COVID-19 in England and show that the simulations provide useful projections of future COVID-19 clinical demand. These simulations were used to support operational planning in the NHS in England, and we present the example of the use of these simulations in projecting future clinical demand during the rollout of the national COVID-19 vaccination programme. Being able to investigate uncertainty and test sensitivities was particularly important to the operational planning team. This epidemiological model operates within an ecosystem of data technologies, drawing on a range of NHS, government and academic data sources, and provides results to strategists, planners and downstream data systems. We discuss the data resources that enabled this work and the data challenges that were faced., Competing Interests: Conflict of interest statement The authors declare no conflict of interest., (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)

Background: Coronavirus disease-2019 (COVID-19) has become a worldwide emergency and has had a severe impact on human health. Inflammatory factors have the potential to either enhance the efficiency of host immune responses or damage the host organs with immune overreaction in COVID-19. Therefore, there is an urgent need to investigate the functions of inflammatory factors and serum markers that participate in disease progression., Methods: In total, 54 COVID-19 patients were enrolled in this study. Disease severity was evaluated by clinical evaluation, laboratory tests, and computed tomography (CT) scans. Data were collected at: admission, 3-5 days after admission, when severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA detection became negative, and composite endpoint., Results: We found that the positive rate in sputum was three times higher than that in throat swabs. Higher levels of C-reactive protein (CRP), lactate dehydrogenase (LDH), D-dimer (D-D), interleukin-6 (IL-6) and neutrophil-to-lymphocyte ratio (NLR) or lower lymphocyte counts suggested more severe disease, and the levels of cytokines and serum markers were intrinsically correlated with disease progression. When SARS-CoV-2 RNA detection became negative, the receiver operating characteristic (ROC) curve demonstrated that LDH had the highest sensitivity independently, and four indicators (NLR, CRP, LDH, and D-D) when combined had the highest sensitivity in distinguishing critically ill patients from mild ones., Conclusions: Monitoring dynamic changes in NLR, CRP, LDH, IL-6, and D-D levels, combined with CT imaging and viral RNA detection in sputum, could aid in severity evaluation and prognosis prediction and facilitate COVID-19 treatment., (© 2023 The Authors. Journal of Clinical Laboratory Analysis published by Wiley Periodicals LLC.)

Background: COVID-19 data have been generated across the United Kingdom as a by-product of clinical care and public health provision, as well as numerous bespoke and repurposed research endeavors. Analysis of these data has underpinned the United Kingdom's response to the pandemic, and informed public health policies and clinical guidelines. However, these data are held by different organizations, and this fragmented landscape has presented challenges for public health agencies and researchers as they struggle to find relevant data to access and interrogate the data they need to inform the pandemic response at pace., Objective: We aimed to transform UK COVID-19 diagnostic data sets to be findable, accessible, interoperable, and reusable (FAIR)., Methods: A federated infrastructure model (COVID - Curated and Open Analysis and Research Platform [CO-CONNECT]) was rapidly built to enable the automated and reproducible mapping of health data partners' pseudonymized data to the Observational Medical Outcomes Partnership Common Data Model without the need for any data to leave the data controllers' secure environments, and to support federated cohort discovery queries and meta-analysis., Results: A total of 56 data sets from 19 organizations are being connected to the federated network. The data include research cohorts and COVID-19 data collected through routine health care provision linked to longitudinal health care records and demographics. The infrastructure is live, supporting aggregate-level querying of data across the United Kingdom., Conclusions: CO-CONNECT was developed by a multidisciplinary team. It enables rapid COVID-19 data discovery and instantaneous meta-analysis across data sources, and it is researching streamlined data extraction for use in a Trusted Research Environment for research and public health analysis. CO-CONNECT has the potential to make UK health data more interconnected and better able to answer national-level research questions while maintaining patient confidentiality and local governance procedures., (©Emily Jefferson, Christian Cole, Shahzad Mumtaz, Samuel Cox, Thomas Charles Giles, Sam Adejumo, Esmond Urwin, Daniel Lea, Calum Macdonald, Joseph Best, Erum Masood, Gordon Milligan, Jenny Johnston, Scott Horban, Ipek Birced, Christopher Hall, Aaron S Jackson, Clare Collins, Sam Rising, Charlotte Dodsley, Jill Hampton, Andrew Hadfield, Roberto Santos, Simon Tarr, Vasiliki Panagi, Joseph Lavagna, Tracy Jackson, Antony Chuter, Jillian Beggs, Magdalena Martinez-Queipo, Helen Ward, Julie von Ziegenweidt, Frances Burns, Joanne Martin, Neil Sebire, Carole Morris, Declan Bradley, Rob Baxter, Anni Ahonen-Bishopp, Paul Smith, Amelia Shoemark, Ana M Valdes, Benjamin Ollivere, Charlotte Manisty, David Eyre, Stephanie Gallant, George Joy, Andrew McAuley, David Connell, Kate Northstone, Katie Jeffery, Emanuele Di Angelantonio, Amy McMahon, Mat Walker, Malcolm Gracie Semple, Jessica Mai Sims, Emma Lawrence, Bethan Davies, John Kenneth Baillie, Ming Tang, Gary Leeming, Linda Power, Thomas Breeze, Duncan Murray, Chris Orton, Iain Pierce, Ian Hall, Shamez Ladhani, Natalie Gillson, Matthew Whitaker, Laura Shallcross, David Seymour, Susheel Varma, Gerry Reilly, Andrew Morris, Susan Hopkins, Aziz Sheikh, Philip Quinlan. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 27.12.2022.)

Objectives: To investigate the impact of the current coronavirus disease 2019 (COVID-19) pandemic on the quality of life (QoL) and status of COVID-19 vaccination in heart transplant recipients (HTRs)., Methods: Patients who underwent allogeneic heart transplants between June 2006 and December 2019, who survived were selected from a follow-up registration form at our center. Data were collected using questionnaires in 2021, the QoL survey was conducted using the MOS 36-item Short-Form Health Survey (SF-36) and compared to the same time frame in 2019. The patients were divided into two groups: post-epidemic (A) and pre-epidemic (B) groups. We also recorded whether the participants had been vaccinated against COVID-19 (Beijing Sinovac COVID-19 vaccine). All the data obtained were analyzed., Results: There were 88 patients who participated in the study. Only 12 (13.6%) were vaccinated. In terms of SF-36 scale assessments, after the outbreak of the COVID-19 pandemic, Group A scored lower in vitality [52.5(49.0, 58.0) vs. 75.0(69.0, 79.0), p < .001], social functioning [54.0(50.5, 58.0) vs. 74.0(67.5, 78.0), p < .001], role emotional [58.5(55.0, 62.0) vs. 67.0(63.0, 71.0), p < .001], and mental health [58.5(55.0, 62.0) vs. 76.0(72.0, 79.0), p < .001]. In Group A the mental component summary (MCS) significantly decreased [222.0(214.5, 230.0) vs. 289.0(277.5, 299.5), p < .001]. The PCS and MCS of HTRs who had been vaccinated against COVID-19 were significantly higher than those who had not [PCS: 283.5(280.0, 287.0) vs. 276.0(271.0, 279.0), p < .001; MCS: 245.0(141.5, 254.0) vs. 220.0(213.5, 226.5), p < .001]., Conclusion: Low acceptance levels of COVID-19 vaccination were observed in the HTRs. The QoL of the HTRs decreased after the COVID-19 pandemic., (© 2022 Wiley Periodicals LLC.)

Background: In addition to physical symptom burden, psychological suffering at end of life (EOL) is quite pervasive. As such, the interdisciplinary team in our Palliative and Supportive Care Unit strives to provide quality care sensitive to the physical and psychosocial needs of patients. Involving and allowing for the presence of family members is one way in which we afford our patients some additional comfort. Unfortunately, the current pandemic has placed limitations on this rather fundamental need for both patients and their family members. Here, we present a case illustrating the effects of visitor restrictions/isolation due to COVID-19 on the suffering of a patient at the EOL., Case Description: A male in his 20s with a refractory hematologic malignancy decided to pursue a comfort-based approach to care after a rapid clinical deterioration. Due to visitor restrictions, he had to face this decision with limited support at the bedside, which caused significant distress. He was forced to choose among several immediate family members who would be at his side through his hospitalization, to be his advocate, at times his voice, his confidant, and the person to relay all information to those on the outside. He expressed a wish to be married before he died, which occurred in our palliative care unit. This life goal was one we would normally encourage those he loved to gather around him, but this was not possible. He passed peacefully two days after he was married., Conclusion: Although social limitations are necessary to help provide safety to the patients and staff in a hospital, they can have a direct impact on the suffering of patients and families at the EOL. Helping to maintain dignity, reflect on their life, and resolve any conflicts in the presence of family members is a benchmark for providing quality palliative care. Being barred from visitation due to isolation, threatens this care and lays the foundation for complicated grief among family members. Further research is needed to help balance the needs of those at the EOL with public safety. One such measure to help ease distress is to allow for more virtual visitation through electronic measures.

Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) leads to coronavirus disease 2019 (COVID-19) and is a public health problem. This meta-analysis reviewed the clinical features of SARS-CoV-2 infection among infants., Methods: PubMed, Scopus, Web of Science, and the Cochrane Library were searched for studies on clinical features of infants with SARS-CoV-2 published before May 1, 2022. Two authors screened and extracted data on the number of infants with SARS-CoV-2 infection, clinical features, and number of clinical features. The proportion of asymptomatic infection, mild symptoms, moderate symptoms, severe symptoms, and the clinical features were analyzed., Results: Forty-four studies with 6,304 infants with SARS-CoV-2 infections were included in this study. The proportion of asymptomatic infection was 20% (95% CI: 11-28%, I2=97%, P<0.01) in infants with SARS-CoV-2 infections. The proportion of infants with mild, moderate, and severe symptoms was 48% (95% CI: 30-65%, I2=96%, P<0.01), 27% (95% CI: 10-44%, I2=93%, P<0.01), and 8% (95% CI: 0-16%, I2=90%, P<0.01), respectively. Notably, the most common clinical features of infants with SARS-CoV-2 infection were fever (64%), cough (34%), and nasal symptoms (31%)., Conclusions: This meta-analysis found that 20% of infants with SARS-CoV-2 infections were asymptomatic, while most infants with COVID-19 presented with mild symptoms.

Summary: The ongoing pandemic caused by SARS-CoV-2 emphasizes the importance of genomic surveillance to understand the evolution of the virus, to monitor the viral population, and plan epidemiological responses. Detailed analysis, easy visualization and intuitive filtering of the latest viral sequences are powerful for this purpose. We present CovRadar, a tool for genomic surveillance of the SARS-CoV-2 Spike protein. CovRadar consists of an analytical pipeline and a web application that enable the analysis and visualization of hundreds of thousand sequences. First, CovRadar extracts the regions of interest using local alignment, then builds a multiple sequence alignment, infers variants and consensus and finally presents the results in an interactive app, making accessing and reporting simple, flexible and fast., Availability and Implementation: CovRadar is freely accessible at https://covradar.net, its open-source code is available at https://gitlab.com/dacs-hpi/covradar., Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author(s) 2022. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Growing enthusiasm for remote patient monitoring has been motivated by the hope that it can improve care for patients with poorly controlled chronic illness. In a national commercially insured population in the US, we found that billing for remote patient monitoring increased more than fourfold during the first year of the COVID-19 pandemic. Most of this growth was driven by a small number of primary care providers. Among the patients of these providers with a high volume of remote patient monitoring, we did not observe substantial targeting of remote patient monitoring to people with greater disease burden or worse disease control. Further research is needed to identify which patients benefit from remote patient monitoring, to inform evidence-based use and coverage decisions. In the meantime, payers and policy makers should closely monitor remote patient monitoring use and spending.

Background: Polyethylene glycol (PEG) and polysorbate reactions were initially implicated as a likely risk factor for reacting to coronavirus disease 2019 (COVID-19) vaccines and remain a source of vaccine hesitancy despite increasing evidence that they do not pose an increased risk for COVID-19 vaccine reactions., Objective: To investigate COVID-19 vaccine safety outcomes in patients with reported reactions to PEG- and polysorbate-containing medications and vaccines., Methods: COVID-19 vaccine safety was reviewed in patients with PEG or polysorbate reactions documented in their electronic medical records at a tertiary academic medical center (cohort 1) and patients referred to Allergy and Immunology with reported PEG or polysorbate reactions (cohort 2). COVID-19 vaccine safety was also reviewed following reported symptoms (onset ≤ 12 hours) to first-dose PEG-containing messenger RNA (mRNA) COVID-19 vaccine (cohort 3)., Results: Of 252 patients in cohort 1 (n = 202) and cohort 2 (n = 50), 236 (94%) received mRNA COVID-19 vaccines (106 Pfizer, 130 Moderna); 235 received both doses. Only 3 patients from cohort 2 developed mild rash following vaccination. None of the 44 patients in cohort 3 with acute symptoms following first-dose mRNA COVID-19 vaccine (27 Pfizer, 17 Moderna) had previously reported PEG or polysorbate reactions. Of these 44 patients, 43 received the second dose and all 3 who developed symptoms following the second dose (1 required epinephrine) had negative PEG skin testing., Conclusion: Patients with reported reactions to PEG and polysorbate safely received COVID-19 vaccines. PEG and polysorbate skin testing did not identify patients at risk for first dose or recurrent reactions to COVID-19 vaccines. Screening for PEG and polysorbate allergy may only increase vaccine hesitancy without identifying patients at risk for COVID-19 vaccine reactions., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

Existing models about the dynamics of COVID-19 transmission often assume the mechanism of virus transmission and the form of the differential equations. These assumptions are hard to verify. Due to the biases of country-level data, it is inaccurate to construct the global dynamic of COVID-19. This research aims to provide a robust data-driven global model of the transmission dynamics. We apply sparse identification of nonlinear dynamics (SINDy) to model the dynamics of COVID-19 global transmission. One advantage is that we can discover the nonlinear dynamics from data without assumptions in the form of the governing equations. To overcome the problem of biased country-level data on the number of reported cases, we propose a robust global model of the dynamics by using maximin aggregation. Real data analysis shows the efficiency of our model., (© 2021 Wiley-VCH GmbH.)

In the past 10-15 years, the government of China has made various efforts in tackling excessive antibiotics use. Yet, little is known about their effects at rural primary care settings. This study aimed to determine the impact of government policies and the COVID-19 pandemic on antibiotic prescribing practices at such settings utilizing data from separate studies carried out pre- and during the pandemic, in 2016 and 2021 in Anhui province, China, using identical sampling and survey approaches. Data on antibiotics prescribed, diagnosis, socio-demographic, etc., were obtained through non-participative observation and a structured exit survey. Data analysis comprised mainly descriptive comparisons of 1153 and 762 patients with respiratory infections recruited in 2016 and 2021, respectively. The overall antibiotics prescription rate decreased from 89.6% in 2016 to 69.1% in 2021, and the proportion of prescriptions for two or more classes of antibiotics was estimated as 35.9% in 2016 and 11.0% in 2021. There was a statistically significant decrease in the number of days from symptom onset to clinic visits between the year groups. In conclusion, measures to constrain excessive prescription of antibiotics have led to some improvements at the rural primary care level, and the COVID-19 pandemic has had varying effects on antibiotic use.

Background: The COVID-19 pandemic has highlighted the importance of whole genome sequencing (WGS) of SARS-CoV-2 to inform public health policy. By enabling definition of lineages it facilitates tracking of the global spread of the virus. The evolution of new variants can be monitored and knowledge of specific mutations provides insights into the mechanisms through which the virus increases transmissibility or evades immunity. To date almost 1 million SARS-CoV-2 genomes have been sequenced by members of the COVID-19 Genomics UK (COG-UK) Consortium. To achieve similar feats in a more cost-effective and sustainable manner in future, improved high throughput virus sequencing protocols are required. We have therefore developed a miniaturized library preparation protocol with drastically reduced consumable use and costs., Results: We present the 'Mini-XT' miniaturized tagmentation-based library preparation protocol available on protocols.io ( https://doi.org/10.17504/protocols.io.bvntn5en ). SARS-CoV-2 RNA was amplified using the ARTIC nCov-2019 multiplex RT-PCR protocol and purified using a conventional liquid handling system. Acoustic liquid transfer (Echo 525) was employed to reduce reaction volumes and the number of tips required for a Nextera XT library preparation. Sequencing was performed on an Illumina MiSeq. The final version of Mini-XT has been used to sequence 4384 SARS-CoV-2 samples from N. Ireland with a COG-UK QC pass rate of 97.4%. Sequencing quality was comparable and lineage calling consistent for replicate samples processed with full volume Nextera DNA Flex (333 samples) or using nanopore technology (20 samples). SNP calling between Mini-XT and these technologies was consistent and sequences from replicate samples paired together in maximum likelihood phylogenetic trees., Conclusions: The Mini-XT protocol maintains sequence quality while reducing library preparation reagent volumes eightfold and halving overall tip usage from sample to sequence to provide concomitant cost savings relative to standard protocols. This will enable more efficient high-throughput sequencing of SARS-CoV-2 isolates and future pathogen WGS., (© 2022. The Author(s).)

Background: Data on the safety and efficacy of coronavirus disease 2019 (COVID-19) vaccination in people with a range of primary immunodeficiencies (PIDs) are lacking because these patients were excluded from COVID-19 vaccine trials. This information may help in clinical management of this vulnerable patient group., Objective: We assessed humoral and T-cell immune responses after 2 doses of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) messenger RNA (mRNA) vaccines in patients with PID and functional B-cell defects., Methods: A double-center retrospective review was performed of patients with PID who completed COVID-19 mRNA vaccination and who had humoral responses assessed through SARS-CoV-2 spike protein receptor binding domain (RBD) IgG antibody levels with reflex assessment of the antibody to block RBD binding to angiotensin-converting enzyme 2 (ACE2; hereafter referred to as ACE2 receptor blocking activity, as a surrogate test for neutralization) and T-cell response evaluated by an IFN-γ release assay. Immunization reactogenicity was also reviewed., Results: A total of 33 patients with humoral defect were evaluated; 69.6% received BNT162b2 vaccine (Pfizer-BioNTech) and 30.3% received mRNA-1273 (Moderna). The mRNA vaccines were generally well tolerated without severe reactions. The IFN-γ release assay result was positive in 24 (77.4%) of 31 patients. Sixteen of 33 subjects had detectable RBD-specific IgG responses, but only 2 of these 16 subjects had an ACE2 receptor blocking activity level of ≥50%., Conclusion: Vaccination of this cohort of patients with PID with COVID-19 mRNA vaccines was safe, and cellular immunity was stimulated in most subjects. However, antibody responses to the spike protein RBD were less consistent, and, when detected, were not effective at ACE2 blocking., (Copyright © 2021 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.)

Objective: The COVID-19 pandemic changed clinician electronic health record (EHR) work in a multitude of ways. To evaluate how, we measure ambulatory clinician EHR use in the United States throughout the COVID-19 pandemic., Materials and Methods: We use EHR meta-data from ambulatory care clinicians in 366 health systems using the Epic EHR system in the United States from December 2019 to December 2020. We used descriptive statistics for clinician EHR use including active-use time across clinical activities, time after-hours, and messages received. Multivariable regression to evaluate total and after-hours EHR work adjusting for daily volume and organizational characteristics, and to evaluate the association between messages and EHR time., Results: Clinician time spent in the EHR per day dropped at the onset of the pandemic but had recovered to higher than prepandemic levels by July 2020. Time spent actively working in the EHR after-hours showed similar trends. These differences persisted in multivariable models. In-Basket messages received increased compared with prepandemic levels, with the largest increase coming from messages from patients, which increased to 157% of the prepandemic average. Each additional patient message was associated with a 2.32-min increase in EHR time per day (P < .001)., Discussion: Clinicians spent more total and after-hours time in the EHR in the latter half of 2020 compared with the prepandemic period. This was partially driven by increased time in Clinical Review and In-Basket messaging., Conclusions: Reimbursement models and workflows for the post-COVID era should account for these demands on clinician time that occur outside the traditional visit., (© The Author(s) 2021. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

The current coronavirus disease 2019 (COVID-19) vaccines are used to prevent viral infection by inducing neutralizing antibody in the body, but according to the existing experience of severe acute respiratory syndrome coronavirus (SARS) infection, T-cell immunity could provide a longer durable protection period than antibody. The research on SARS-CoV-2-specific T-cell epitope can provide target antigen for the development and evaluation of COVID-19 vaccines, which is conducive to obtain COVID-19 vaccine that can provide long-term protection. For screening specific T-cell epitopes, a SARS-CoV-2 S protein peptide library with a peptide length of 15 amino acids was synthesized. Through flow cytometry to detect percentage of IFN-γ + T cells after mixed COVID-19 convalescent patients' peripheral blood mononuclear cell with peptide library, seven peptides (P77, P14, P24, P38, P48, P74, and P84) that can be recognized by the T cells of COVID-19 convalescent patients were found. After excluding the nonspecific cross-reactions with unexposed population, three SARS-CoV-2-specific T-cell potential epitopes (P38, P48, and P84) were finally screened with the positive reaction rates between 15.4% and 48.0% in COVID-19 convalescent patients. This study also provided the HLA allele information of peptide-positive-response COVID-19 convalescent patients, thus predicting the population coverage of these three potential epitopes. Some HLA alleles showed higher frequency of occurrence in COVID-19 patients than in total Chinese population but no HLA alleles related to the T-cell peptide response and the severity of COVID-19. This research provides three potential T-cell epitopes that are helpful for the design and efficacy evaluation of COVID-19 vaccines. The HLA information provided by this research supplies reference significance for subsequent research such as finding the relation of HLA genotype with disease susceptibility., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Zhang, Yang, Tang, Li, Tang, Li, Zhong, Zhang, Wang and Wang.)

Background: Long-term exposure to ambient air pollution was linked to depression incidence, although the results were limited and inconsistent., Objectives: To investigate the effects of long-term air pollution exposure on depression risk prospectively in China., Methods: The present study used data from Yinzhou Cohort on adults without depression at baseline, and followed up until April 2020. Two-year moving average concentrations of particulate matter with a diameter ≤ 2.5 μm (PM 2.5 ), ≤10 μm (PM 10 ) and nitrogen dioxide (NO 2 ) were measured using land-use regression (LUR) models for each participant. Depression cases were ascertained using the Health Information System (HIS) of the local health administration by linking the unique identifiers. We conducted Cox regression models with time-varying exposures to estimate the hazard ratios (HRs) and 95% confidence intervals (95% CIs) of depression with each pollutant, after adjusting for a sequence of individual covariates as demographic characteristics, lifestyles, and comorbidity. Besides, physical activity, baseline potential depressive symptoms, cancer status, COVID-19 pandemic, different outcome definitions and air pollution exposure windows were considered in sensitivity analyses., Results: Among the 30,712 adults with a mean age of 62.22 ± 11.25, 1024 incident depression cases were identified over totaling 98,619 person-years of observation. Interquartile range increments of the air pollutants were associated with increased risks of depression, and the corresponding HRs were 1.59 (95%CI: 1.46, 1.72) for PM 2.5 , 1.49 (95%CI: 1.35, 1.64) for PM 10 and 1.58 (95%CI: 1.42, 1.77) for NO 2 . Subgroup analyses suggested that participants without taking any protective measures towards air pollution were more susceptible. The results remained robust in all sensitivity analyses., Conclusions: Long-term exposure to ambient air pollution was identified as a risk factor for depression onset. Strategies to reduce air pollution are necessary to decrease the disease burden of depression., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021. Published by Elsevier B.V.)

COVID-19 is a serious respiratory disease. The ever-increasing number of cases is causing heavier loads on the health service system. Using 38 blood test indicators on the first day of admission for the 422 patients diagnosed with COVID-19 (from January 2020 to June 2021) to construct different machine learning (ML) models to classify patients into either mild or severe cases of COVID-19. All models show good performance in the classification between COVID-19 patients into mild and severe disease. The area under the curve (AUC) of the random forest model is 0.89, the AUC of the naive Bayes model is 0.90, the AUC of the support vector machine model is 0.86, and the AUC of the KNN model is 0.78, the AUC of the Logistic regression model is 0.84, and the AUC of the artificial neural network model is 0.87, among which the naive Bayes model has the best performance. Different ML models can classify patients into mild and severe cases based on 38 blood test indicators taken on the first day of admission for patients diagnosed with COVID-19., (© 2021 Wiley Periodicals LLC.)

The outbreak of COVID-19 pandemic has caused profound consequences on world economy. In order to explore the long-term impact of the pandemic on economic growth and the effects of different policy responses, this paper combines economic theory with epidemiological model to construct an interdisciplinary model, in which labor supply is dynamically constrained by pandemic conditions. Analysis of model equilibrium suggests that outbreaks of infectious disease reduce labor supply and negatively affect economic output. The accumulation of health capital can suppress the spread of disease and improve the recovery rate of infected individuals, which will alleviate the labor supply constraint caused by the pandemic and lead to an increase in output and consumption. The model is then calibrated to Chinese economy. The simulation results imply that government's public health policy can enhance the role of health capital in promoting economic growth. But the marginal effect of certain policies is diminishing. Therefore, the government needs to balance pandemic prevention and control costs and marginal benefits when formulating public health policies. When the pandemic is under control, the resumption of production is feasible and the economic stimulus package could lead to economic recovery., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Xiang, Tang, Yin, Zheng and Lu.)