The relationship between pangolin-CoV and SARS-CoV-2 has been a subject of debate. Further evidence of a special relationship between the two viruses can be found by the fact that all known COVID-19 viruses have an abnormally hard outer shell (low M disorder, i.e., low content of intrinsically disordered residues in the membrane (M) protein) that so far has been found in CoVs associated with burrowing animals, such as rabbits and pangolins, in which transmission involves virus remaining in buried feces for a long time. While a hard outer shell is necessary for viral survival, a harder inner shell could also help. For this reason, the N disorder range of pangolin-CoVs, not bat-CoVs, more closely matches that of SARS-CoV-2, especially when Omicron is included. The low N disorder (i.e., low content of intrinsically disordered residues in the nucleocapsid (N) protein), first observed in pangolin-CoV-2017 and later in Omicron, is associated with attenuation according to the Shell-Disorder Model. Our experimental study revealed that pangolin-CoV-2017 and SARS-CoV-2 Omicron (XBB.1.16 subvariant) show similar attenuations with respect to viral growth and plaque formation. Subtle differences have been observed that are consistent with disorder-centric computational analysis.

This prospective study in Hong Kong aimed at identifying prognostic metabolomic and immunologic biomarkers for Coronavirus Disease 2019 (COVID-19). We examined 327 patients, mean age 55 (19-89) years, in whom 33.6% were infected with Omicron and 66.4% were infected with earlier variants. The effect size of disease severity on metabolome outweighed others including age, gender, peak C-reactive protein (CRP), vitamin D and peak viral levels. Sixty-five metabolites demonstrated strong associations and the majority (54, 83.1%) were downregulated in severe disease (z score: -3.30 to -8.61). Ten cytokines/chemokines demonstrated strong associations (p < 0.001), and all were upregulated in severe disease. Multiple pairs of metabolomic/immunologic biomarkers showed significant correlations. Fourteen metabolites had the area under the receiver operating characteristic curve (AUC) > 0.8, suggesting a high predictive value. Three metabolites carried high sensitivity for severe disease: triglycerides in medium high-density lipoprotein (MHDL) (sensitivity: 0.94), free cholesterol-to-total lipids ratio in very small very-low-density lipoprotein (VLDL) (0.93), cholesteryl esters-to-total lipids ratio in chylomicrons and extremely large VLDL (0.92);whereas metabolites with the highest specificity were creatinine (specificity: 0.94), phospholipids in large VLDL (0.94) and triglycerides-to-total lipids ratio in large VLDL (0.93). Five cytokines/chemokines, namely, interleukin (IL)-6, IL-18, IL-10, macrophage inflammatory protein (MIP)-1b and tumour necrosis factor (TNF)-a, had AUC > 0.8. In conclusion, we demonstrated a tight interaction and prognostic potential of metabolomic and immunologic biomarkers enabling an outcome-based patient stratification.

UNASSIGNED: Social media platforms such as Twitter and Weibo facilitate both positive and negative communication, including cyberbullying. Empirical evidence has revealed that cyberbullying increases when public crises occur, that such behavior is gendered, and that social media user account verification may deter it. However, the association of gender and verification status with cyberbullying is underexplored. This study aims to address this gap by examining how Weibo users\' gender, verification status, and expression of affect and anger in posts influence cyberbullying attitudes. Specifically, it investigates how these factors differ between posts pro- and anti-cyberbullying of COVID-19 cases during the pandemic.
UNASSIGNED: This study utilized social role theory, the Barlett and Gentile Cyberbullying Model, and general strain theory as theoretical frameworks. We applied text classification techniques to identify pro-cyberbullying and anti-cyberbullying posts on Weibo. Subsequently, we used a standardized mean difference method to compare the emotional content of these posts. Our analysis focused on the prevalence of affective and anger-related expressions, particularly examining variations across gender and verification status of the users.
UNASSIGNED: Our text classification identified distinct pro-cyberbullying and anti-cyberbullying posts. The standardized mean difference analysis revealed that pro-cyberbullying posts contained significantly more emotional content compared to anti-cyberbullying posts. Further, within the pro-cyberbullying category, posts by verified female users exhibited a higher frequency of anger-related words than those by other users.
UNASSIGNED: The findings from this study can enhance researchers\' algorithms for identifying cyberbullying attitudes, refine the characterization of cyberbullying behavior using real-world social media data through the integration of the mentioned theories, and help government bodies improve their cyberbullying monitoring especially in the context of public health crises.

Amid the COVID-19 pandemic, education systems globally implemented protective measures, notably mandatory mask wearing. As the pandemic\'s dynamics changed, many municipalities lifted these mandates, warranting a critical examination of these policy changes\' implications. This study examines the effects of lifting mask mandates on COVID-19 transmission within Massachusetts school districts. We first replicated previous research that utilized a difference-in-difference (DID) model for COVID-19 incidence. We then repeated the DID analysis by replacing the outcome measurement with the reproductive number (Rt ), reflecting the transmissibility. Due to the data availability, the Rt we estimated only measures the within school transmission. We found a similar result in the replication using incidence with an average treatment effect on treated (ATT) of 39.1 (95% CI: 20.4 to 57.4) COVID-19 cases per 1,000 students associated with lifting masking mandates. However, when replacing the outcome measurement to Rt , our findings suggest that no significant association between lifting mask mandates and reduced Rt (ATT: 0.04, 95% CI: -0.09 to 0.18), except for the first 2 weeks postintervention. Moreover, we estimated Rt below 1 at 4 weeks before lifting mask mandates across all school types, suggesting nonsustainable transmission before the implementation. Our reanalysis suggested no evidence of lifting mask mandates in schools impacted the COVID-19 transmission in the long term. Our study highlights the importance of examining the transmissibility outcome when evaluating interventions against transmission.

In typical times, adolescents\' relationships with family members influence changing cognitive, social, and physical aspects of their development. The COVID-19 pandemic, however, impacted the full family system in ways that were unprecedented. Scholars of adolescence worldwide were driven to understand how adolescents\' relationships with family members changed due to these dramatic societal shifts and the influence these relationships had on adolescents\' well-being. This systematic review examined two research questions with 189 articles published from 2020-2022: (1) How has the COVID-19 pandemic impacted families with adolescents, including broader family functioning, family relationship qualities, and parenting? and (2) How has the pandemic or pandemic-related stressors interacted with family functioning, family relationships, and parenting of adolescents to impact adolescent well-being and adjustment? Additionally, examination of the relevant studies were divided into sub-themes of pandemic influence: (a) family environment and routines, (b) family difficulties, (c) parenting and parent-adolescent relationships, and (d) sibling relationships.

The integration of disparate emergency resources and the improvement of emergency response teamwork are the underlying trends and shared requirements for building resilience in an era of multiple global public health crises.
This study investigated the emergency response with emergency collaboration networks of each functional module and the overall Joint Epidemic Prevention and Control Mechanism (JPCM) network in China\'s COVID outbreak prevention and control.
The study employed a scholarly framework of \"the integration of JPCM coordination and emergency collaborative modularization\" to explore the attributes of JPCM using social network analysis. The data were obtained from administrative records from JPCM\'s official website, spanning January 2020 to December 2022.
The study examined the JPCM coordination and found several functional working modules of JPCM, such as Interrupt Spread, Manage Supply, Medical Rescue, Restore Work and Production, and Implement Responsibility modules. The network structure indicators showed that the Manage Supply module had the most extensive network connectivity, the shortest communication distance, and the most consistent collaboration. The E-I index of the overall JPCM network and the Manage Supply network were - 0.192 and - 0.452, respectively (at p < 0.001 and p < 0.05), indicating more internal relationships than external relationships. The E-I index of the Medical Rescue and Implement Responsibility collaboration networks were 0.122 and 0.147, respectively (at p < 0.001 and p < 0.05), indicating more external relationships than internal relationships. The QAP regression analysis showed that the most vital driver on the overall JPCM network was the Interrupt Spread module, followed by the Implement Responsibility and Medical Rescue modules.
The Interrupt Spread module initiated emergency coordination with most departments and agencies. The Manage Supply module ensured the flow of medical supplies and survival essentials, while the Medical Rescue module addressed the core aspects of the health emergency response. The Restore Work and Production module repaired the halt in production and livelihoods caused by the outbreak, strengthening and developing emergency coordination and roles across emergency organizations. The Implement Responsibility module provided more heterogeneous emergency response resources for the overall JPCM coordination, complementing the COVID cross-organizational emergency response coordination.
The study on the JPCM case in China improves public health emergency management and aids informed decision-making.

BACKGROUND: Most studies on the impact of the COVID-19 pandemic on depression burden focused on the earlier pandemic phase specific to lockdowns, but the longer-term impact of the pandemic is less well-studied. In this population-based cohort study, we examined the short-term and long-term impacts of COVID-19 on depression incidence and healthcare service use among patients with depression.
METHODS: Using the territory-wide electronic medical records in Hong Kong, we identified all patients aged ≥ 10 years with new diagnoses of depression from 2014 to 2022. We performed an interrupted time-series (ITS) analysis to examine changes in incidence of medically attended depression before and during the pandemic. We then divided all patients into nine cohorts based on year of depression incidence and studied their initial and ongoing service use patterns until the end of 2022. We applied generalized linear modeling to compare the rates of healthcare service use in the year of diagnosis between patients newly diagnosed before and during the pandemic. A separate ITS analysis explored the pandemic impact on the ongoing service use among prevalent patients with depression.
RESULTS: We found an immediate increase in depression incidence (RR = 1.21, 95% CI: 1.10-1.33, p < 0.001) in the population after the pandemic began with non-significant slope change, suggesting a sustained effect until the end of 2022. Subgroup analysis showed that the increases in incidence were significant among adults and the older population, but not adolescents. Depression patients newly diagnosed during the pandemic used 11% fewer resources than the pre-pandemic patients in the first diagnosis year. Pre-existing depression patients also had an immediate decrease of 16% in overall all-cause service use since the pandemic, with a positive slope change indicating a gradual rebound over a 3-year period.
CONCLUSIONS: During the pandemic, service provision for depression was suboptimal in the face of increased demand generated by the increasing depression incidence during the COVID-19 pandemic. Our findings indicate the need to improve mental health resource planning preparedness for future public health crises.

After the Chinese government announced the end of the dynamic zero-COVID policy on January 8, 2023, the COVID-19 pandemic peaked. Frontline nursing staff are at high risk of infection transmission due to their frequent contact with COVID-19 patients. In addition, due to the ending of China\'s dynamic zero-COVID policy, frontline nursing staff have grappled with increased workload, fatigue, and more. This study aimed to explore the prevalence of insomnia symptoms in frontline nursing staff and its influencing factors following the end of the policy.
Between January and February 2023, this study was conducted by the Wenjuanxing platform to survey frontline nursing staff in a hospital in Wuhu City, Anhui Province. All the nursing staff included in this study had a COVID-19 infection. The questionnaires included the Athens Insomnia Scale (AIS), PC-PTSD-5 Chinese Version Scale, the Fear of COVID-19 Scale, The 2-item Connor-Davidson Resilience Scale (CD-RISC-2) Scale, and the burden of COVID-19 Scale. Binary logistic regression methods were used to identify variables associated with insomnia symptoms.
Among the 694 frontline nursing staff, 74.5% (517/694) exhibited insomnia symptoms. Fear of COVID-19 (p < 0.001), the burden of COVID-19 (p < 0.05), PTSD (p < 0.001), and higher technical titles (p < 0.008) were highly correlated with insomnia symptoms in frontline nursing staff. Psychological resilience (p < 0.001) was a protective factor for insomnia symptoms among frontline nursing staff.
After ending China\'s dynamic zero-COVID policy, the prevalence of insomnia symptoms among frontline nursing staff is generally higher. This study highlights the association between insomnia symptoms and PTSD, fear of COVID-19, COVID-19 burden, and resilience. Psychological assistance is needed for frontline nursing staff to prevent insomnia symptoms and protect the mental health of frontline nursing staff after the end of China\'s dynamic zero-COVID policy.

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Sleep disturbances are highly prevalent during the COVID-19 pandemic, especially among older adults. We aimed to evaluate sleep heath during COVID-19 pandemic and assess the differences among geographical regions and pandemic periods. We searched three databases (PubMed, Embase, Web of Science) to find articles up to March 12, 2023. We included observational studies that reported the prevalence of sleep disturbances among adults aged 60 years or older in any setting. Two researchers independently reviewed the literature and retrieved the data. We used Der Simonian-Laird random effects meta-analyses to pool the data, followed by subgroup analysis, sensitivity analysis, and meta-regression. A total of 64 studies with 181,224 older adults during the pandemic were included. The prevalence of poor sleep quality, short sleep duration, long sleep duration, and insomnia symptoms were 47.12% (95% CI: 25.97%, 68.27%), 40.81% (95% CI: 18.49%, 63.12%), 31.61% (95% CI: 24.83%, 38.38%), and 21.15% (95% CI: 15.30%, 27.00%), respectively. The prevalence of sleep problems reported by self-constructed items was 26.97% (95% CI: 20.73%, 33.22%). When compared to America (64.13%), Europe (20.23%) and the Western Pacific (21.31%) showed a lower prevalence of sleep problems (all P < 0.0001). The prevalence of worsened sleep problems was 27.88% (95% CI: 11.94%, 43.82%). Compared to 2020 (15.14%), it increased to 47.42% in 2021 (P < 0.05). Eight studies on sleep disturbances among 672 older COVID-19 patients were included. The prevalence of sleep problems and insomnia symptoms among older COVID-19 patients were 41.58% (95% CI: 21.97%, 61.20%) and 41.56% (95% CI: 28.11%, 58.02%), respectively. A significant burden related to poor sleep has been observed among older adults worldwide over the past three years, with variations across different regions and time periods. It is important to make more efforts in prevention and intervention to identify the risk factors, treatment, and rehabilitation of sleep disturbances for healthy aging.