Workplace violence and associations with health outcomes in public health administration agencies in Taiwan: a survey during the COVID-19 pandemic

Objectives: To investigate the prevalence of workplace violence in public health administration agencies and its effects on health outcomes. Methods: A survey was conducted in March 2022. Staff who had been working for at least one year in the Ministry of Health and Welfare or its subordinate agencies, the Department of Health, or in public health centers were recruited. Data were collected anonymously with a structured, online questionnaire. A total of 492 valid questionnaires were collected. Results: A total of 48.17% participants reported having experienced workplace violence (physical, psychological, verbal, or sexual). The most common type of violence was verbal (43.50%), followed by psychological (31.71%). Supervisors were the primary perpetrators of verbal and psychological violence, followed by clients and colleagues. Staff reported long working hours and high levels of psychological and physical stress. Furthermore, 22.97% of workers reported poor self-rated health, 60.57% had personal burnout levels higher than 50, and 63.41% reported poor mental health. Regression analyses showed that low workplace justice was most strongly associated with internal verbal and psychological violence, whereas routine work requiring interaction with the public was most strongly associated with external verbal violence. Staff who had experienced workplace violence in the past year had significantly higher risks of poor self-rated health, mental health, and personal burnout, and poor health was more strongly associated with workplace violence that originated inside the organization than with workplace violence that originated from outside the organization. Conclusions: This survey was conducted on-line anonymously, so the representativeness of our findings might be limited. However, heavy workloads and workplace violence in public health administration agencies during the COVID-19 pandemic are important issues deserving urgent attention. (Taiwan J Public Health. 2023;42(1) :42-61)

A three-timepoint network analysis of Covid-19's impact on schizotypal traits, paranoia and mental health through loneliness.

The 2019 coronavirus (Covid-19) pandemic has impacted people's mental wellbeing. Studies to date have examined the prevalence of mental health symptoms (anxiety and depression), yet fewer longitudinal studies have compared across background factors and other psychological variables to identify vulnerable subgroups in the general population. This study tests to what extent higher levels of schizotypal traits and paranoia are associated with mental health variables 6- and 12-months since April 2020. Over 2300 adult volunteers (18-89 years, female = 74.9%) with access to the study link online were recruited from the UK, the USA, Greece and Italy. Self-reported levels of schizotypy, paranoia, anxiety, depression, aggression, loneliness and stress from three timepoints (17 April to 13 July 2020, N1 = 1599; 17 October to 31 January 2021, N2 = 774; and 17 April to 31 July 2021, N3 = 586) were mapped using network analysis and compared across time and background variables (sex, age, income, country). Schizotypal traits and paranoia were positively associated with poorer mental health through loneliness, with no effect of age, sex, income levels, countries and timepoints. Loneliness was the most influential variable across all networks, despite overall reductions in levels of loneliness, schizotypy, paranoia and aggression during the easing of lockdown (time 3). Individuals with higher levels of schizotypal traits/paranoia reported poorer mental health outcomes than individuals in the low-trait groups. Schizotypal traits and paranoia are associated with poor mental health outcomes through self-perceived feelings of loneliness, suggesting that increasing social/community cohesion may improve individuals' mental wellbeing in the long run.

A Study of Reasons for Self-Disclosure on Social Media among Chinese COVID-19 Patients: Based on the Theory of Planned Behavior Model.

BACKGROUND: With a massive population of internet users, China has witnessed a shift in the behavior of social media users towards the COVID-19 pandemic, transitioning from reticence to frequent sharing of information in response to changing circumstances and policy adjustments of the disease. This study aims to explore how perceived benefits, perceived risks, subjective norms, and self-efficacy influence the intentions of Chinese COVID-19 patients to disclose their medical history on social media, and thus to examine their actual disclosure behaviors. METHODS: Based on the Theory of Planned Behavior (TPB) and Privacy Calculus Theory (PCT), a structural equation model was constructed to analyze the influence paths among perceived benefits, perceived risks, subjective norms, self-efficacy, and behavioral intentions to disclose medical history on social media among Chinese COVID-19 patients. A total of 593 valid surveys were collected via a randomized internet-based survey, which constituted a representative sample. Firstly, we used SPSS 26.0 to conduct reliability and validity analyses of the questionnaire, as well as the tests of demographic differences and correlations between variables. Next, Amos 26.0 was employed to construct and test the model fit degree, identify the relationships among latent variables, and conduct path tests. RESULTS: Our findings revealed the following: (1) There were significant gender differences in the self-disclosure behaviors of medical history on social media among Chinese COVID-19 patients. (2) Perceived benefits had a positive effect on self-disclosure behavioral intentions (ß = 0.412, p < 0.001); perceived risks had a positive effect on self-disclosure behavioral intentions (ß = 0.097, p < 0.05); subjective norms had a positive effect on self-disclosure behavioral intentions (ß = 0.218, p < 0.001); self-efficacy had a positive effect on self-disclosure behavioral intentions (ß = 0.136, p < 0.001). (3) Self-disclosure behavioral intentions had a positive effect on disclosure behaviors (ß = 0.356, p < 0.001). CONCLUSIONS: Our study, by integrating TPB and PCT to examine the influencing factors of the self-disclosure behaviors among Chinese COVID-19 patients on social media, found that perceived risks, perceived benefits, subjective norms, and self-efficacy had a positive influence on the self-disclosure intentions of Chinese COVID-19 patients. We also found that self-disclosure intentions, in turn, positively influenced disclosure behaviors. However, we did not observe a direct influence of self-efficacy on disclosure behaviors. Our study provides a sample of the application of TPB in the context of social media self-disclosure behavior among patients. It also introduces a novel perspective and potential approach for individuals to address the feelings of fear and shame related to illness, particularly within the context of collectivist cultural values.

Exposure to negative foreign COVID-19 news predicts lower support for immigration policy in China.

We present a framework for studying the spillover effect of negative foreign COVID-19 news on attitudes towards immigration. Our framework proposes that exposure to negative COVID-19 news from foreign countries can activate negative associations with foreigners, reduce positive attitudes towards them, and increase perceived threat, ultimately leading to decreased support for immigration. We conducted three studies to test this framework. Study 1 found that exposure to negative COVID-19 news about a foreign country increased negative valence associations with that country. Study 2 showed that exposure to more negative COVID-19 news about foreign countries was associated with lower acceptance of immigration policies in real life. Study 3 replicated the spillover effect of negative news exposure using a scenario manipulation. The effects of negative news exposure on immigration policy acceptance in both Studies 2 and 3 were mediated by changes in foreigner attitudes and intergroup threat. Our results demonstrate the important spillover effect of negative foreign COVID-19 news exposure on immigration attitudes and highlight the association perspective as a foundation for understanding attitude changes during the COVID-19 pandemic.

A CRISPR-Cas12a-based platform for ultrasensitive rapid highly specific detection of Mycobacterium tuberculosis in clinical application.

Tuberculosis, caused by Mycobacterium tuberculosis (MTB), is the second leading cause of death after COVID-19 pandemic. Here, we coupled multiple cross displacement amplification (MCDA) technique with CRISPR-Cas12a-based biosensing system to design a novel detection platform for tuberculosis diagnosis, termed MTB-MCDA-CRISPR. MTB-MCDA-CRISPR pre-amplified the specific sdaA gene of MTB by MCDA, and the MCDA results were then decoded by CRISPR-Cas12a-based detection, resulting in simple visual fluorescent signal readouts. A set of standard MCDA primers, an engineered CP1 primer, a quenched fluorescent ssDNA reporter, and a gRNA were designed targeting the sdaA gene of MTB. The optimal temperature for MCDA pre-amplification is 67°C. The whole experiment process can be completed within one hour, including sputum rapid genomic DNA extraction (15 minutes), MCDA reaction (40 minutes), and CRISPR-Cas12a-gRNA biosensing process (5 minutes). The limit of detection (LoD) of the MTB-MCDA-CRISPR assay is 40 fg per reaction. The MTB-MCDA-CRISPR assay does not cross reaction with non-tuberculosis mycobacterium (NTM) strains and other species, validating its specificity. The clinical performance of MTB-MCDA-CRISPR assay was higher than that of the sputum smear microscopy test and comparable to that of Xpert method. In summary, the MTB-MCDA-CRISPR assay is a promising and effective tool for tuberculosis infection diagnosis, surveillance and prevention, especially for point-of-care (POC) test and field deployment in source-limited regions.

Integrating local and neighboring area influences into vulnerability modeling of infectious diseases in Singapore

Infectious disease spreading is a spatial interaction process. Assessing community vulnerability to infectious diseases thus requires not only information on local demographic and built environmental conditions, but also insights into human activity interactions with neighboring areas that can lead to the transition of vulnerability from locations to locations. This study presented an analytical framework based on the Particle Swarm Optimization model to estimate the weights of the factors for vulnerability modeling, and a local proportional parameter for use in the integration of the local and neighboring area risks. A country model and five cross-region validation models were developed for the case study of Singapore to assess the vulnerability to COVID-19. The results showed that the identified weights for the factors were robust throughout the optimization process and across various models. The local proportional parameter could be set slightly higher in between 0.6 and 0.8 (out of 1), signifying that the local effect was higher than the neighboring effect. Computation of the weights from the optimal solutions for the integrated vulnerability index showed that the factors of human activity intensity and accessibility to amenities had much higher weights, at 0.5 and 0.3, respectively. Conversely, the weights of population density, elderly population, social economic status and land use diversity were much lower. These findings underscored the importance of considering non-equal weights for factors and incorporating spatial interactions between local and neighboring areas for vulnerability modeling, to provide to a more comprehensive assessment of vulnerability to infectious diseases.

Assessing the cost-effectiveness of COVID-19 vaccines in a low incidence and low mortality setting: the case of Thailand at start of the pandemic.

OBJECTIVE: This study aimed to assess the cost-effectiveness of COVID-19 vaccines, preferred COVID-19 vaccine profiles, and the preferred vaccination strategies in Thailand. METHODS: An age-structured transmission dynamic model was developed based on key local data to evaluate economic consequences, including cost and health outcome in terms of life-years (LYs) saved. We considered COVID-19 vaccines with different profiles and different vaccination strategies such as vaccinating elderly age groups (over 65s) or high-incidence groups, i.e. adults between 20 and 39 years old who have contributed to more than 60% of total COVID-19 cases in the country thus far. Analyses employed a societal perspective in a 1-year time horizon using a cost-effectiveness threshold of 160,000 THB per LY saved. Deterministic and probabilistic sensitivity analyses were performed to identify and characterize uncertainty in the model. RESULTS: COVID-19 vaccines that block infection combined with social distancing were cost-saving regardless of the target population compared to social distancing alone (with no vaccination). For vaccines that block infection, the preferred (cost-effective) strategy was to vaccinate the high incidence group. Meanwhile, COVID-19 vaccines that reduces severity (including hospitalization and mortality) were cost-effective when the elderly were vaccinated, while vaccinating the high-incidence group was not cost-effective with this vaccine type. Regardless of vaccine type, higher vaccination coverage, higher efficacy, and longer protection duration were always preferred. More so, vaccination with social distancing measures was always preferred to strategies without social distancing. Quarantine-related costs were a major cost component affecting the cost-effectiveness of COVID-19 vaccines. CONCLUSION: COVID-19 vaccines are good value for money even in a relatively low-incidence and low-mortality setting such as Thailand, if the appropriate groups are vaccinated. The preferred vaccination strategies depend on the type of vaccine efficacy. Social distancing measures should accompany a vaccination strategy.

Research on Affective Interaction in Mini Public Transport Based on IPA-FMEA

In the promotion of sustainable modes of transport, especially public transport, reasonable failure risk assessment at the critical moment in the process of service provider touch with users can improve the service quality to a certain extent. This study presents a product service touch point evaluation approach based on the importance–performance analysis (IPA) of user and failure mode and effect analysis (FMEA). Firstly, the authors capture service product service touch points in the process of user interaction with the product by observing the user behavior in a speculative design experiment, and perform the correlation analysis of the service product service touch point. Second, the authors use the IPA analysis method to evaluate and classify the product service touch points and identify the key product service touch points. Thirdly, the authors propose to analyze the failure of key product service touch points based on user-perceived affective interaction and clarify the priority of each key touch point. Finally, reluctant interpersonal communication, as the key failure caused by high risk, is derived according to the evaluation report, which leads to establishing new product service touch points and improving the overall user experience to promote sustainable transports with similar forms and characteristics.

Dynamics of CD4+ T-Cells and Neutralizing Antibody Responses to Three Consecutive Doses of Inactivated COVID-19 Vaccines in PLWH.

Background: Comprehensive characterization of safety and immune responses to vaccines is crucial for the prevention and treatment of COVID-19 among people living with HIV (PLWH). This study aimed to investigate the dynamic changes in SARS-CoV-2-specific CD4+ T-cell subsets and neutralizing antibody after three consecutive doses of inactivated COVID-19 vaccines (BBIBP-CorV) among PLWH. Methods: The blood samples were collected from 165 PLWH, including 66 PLWH in the 3-month interval between the second and third dose (cohort 1) and 99 PLWH in the 5-month interval (cohort 2). Blood collection for immunogenicity analysis was performed at 1-month post-2nd vaccination, pre-3rd vaccination, and within 2-month post-3rd vaccination. Wilcoxon matched-pairs signed-rank test was applied to compare the SARS-CoV-2-specific CD4+ T cell subsets and neutralizing antibody level at different time points. The relationship among CD4+ T-cells, Tregs subpopulations and SARS-CoV-2-specific neutralizing antibody level were evaluated with Spearman non-parametric correlation test. Results: No serious adverse reactions were found among PLWH. After two-dose or three-dose inactivated COVID-19 vaccination, the absolute counts of CD4+ T-cells and Tregs subpopulations (CD4+CD25HighCD127Low Tregs, CD45RA+ rTregs and CD45RO+ eTregs) increased in two cohorts. Satisfactory SARS-CoV-2-specific neutralizing antibody responses to the third-dose vaccination were found in two cohorts, including significantly enhanced neutralizing antibody level and high neutralizing antibody seroconversion rate. In addition, SARS-CoV-2-specific neutralizing antibody level were positively associated with the absolute counts of CD4+ T-cells and Tregs subpopulations as well as the frequency of CD45RO+ eTregs in PLWH after three doses of vaccinations. Conclusion: The three doses of inactivated COVID-19 vaccination were both safe and effective to increase SARS-CoV-2-specific CD4+ T-cells and neutralizing antibody in two PLWH cohorts with different inoculation intervals.

Severe/critical COVID-19 early warning system based on machine learning algorithms using novel imaging scores.

BACKGROUND: Early identification of severe/critical coronavirus disease 2019 (COVID-19) is crucial for timely treatment and intervention. Chest computed tomography (CT) score has been shown to be a significant factor in the diagnosis and treatment of pneumonia, however, there is currently a lack of effective early warning systems for severe/critical COVID-19 based on dynamic CT evolution. AIM: To develop a severe/critical COVID-19 prediction model using a combination of imaging scores, clinical features, and biomarker levels. METHODS: This study used an improved scoring system to extract and describe the chest CT characteristics of COVID-19 patients. The study also took into consideration the general clinical indicators such as dyspnea, oxygen saturation, alternative lengthening of telomeres (ALT), and androgen suppression treatment (AST), which are commonly associated with severe/critical COVID-19 cases. The study employed lasso regression to evaluate and rank the significance of different disease characteristics. RESULTS: The results showed that blood oxygen saturation, ALT, IL-6/IL-10, combined score, ground glass opacity score, age, crazy paving mode score, qsofa, AST, and overall lung involvement score were key factors in predicting severe/critical COVID-19 cases. The study established a COVID-19 severe/critical early warning system using various machine learning algorithms, including XGBClassifier, Logistic Regression, MLPClassifier, RandomForestClassifier, and AdaBoost Classifier. The study concluded that the prediction model based on the improved CT score and machine learning algorithms is a feasible method for early detection of severe/critical COVID-19 evolution. CONCLUSION: The findings of this study suggest that a prediction model based on improved CT scores and machine learning algorithms is effective in detecting the early warning signals of severe/critical COVID-19.

Subunit vaccines with a saponin-based adjuvant boost humoral and cellular immunity to MERS coronavirus.

Middle East respiratory syndrome coronavirus (MERS-CoV) outbreaks have constituted a public health issue with drastic mortality higher than 34%, necessitating the development of an effective vaccine. During MERS-CoV infection, the trimeric spike protein on the viral envelope is primarily responsible for attachment to host cellular receptor, dipeptidyl peptidase 4 (DPP4). With the goal of generating a protein-based prophylactic, we designed a subunit vaccine comprising the recombinant S1 protein with a trimerization motif (S1-Fd) and examined its immunogenicity and protective immune responses in combination with various adjuvants. We found that sera from immunized wild-type and human DPP4 transgenic mice contained S1-specific antibodies that can neutralize MERS-CoV infection in susceptible cells. Vaccination with S1-Fd protein in combination with a saponin-based QS-21 adjuvant provided long-term humoral as well as cellular immunity in mice. Our findings highlight the significance of the trimeric S1 protein in the development of MERS-CoV vaccines and offer a suitable adjuvant, QS-21, to induce robust and prolonged memory T cell response.

Extending the dosing interval of COVID-19 vaccination leads to higher rates of seroconversion in people living with HIV

Introduction Vaccination against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is an effective way of protecting individuals from severe coronavirus disease 2019 (COVID-19). However, immune responses to vaccination vary considerably. This study dynamically assessed the neutralizing antibody (NAb) responses to the third dose of the inactivated COVID-19 vaccine administered to people living with human immunodeficiency virus (HIV;PLWH) with different inoculation intervals. Methods A total of 171 participants were recruited: 63 PLWH were placed in cohort 1 (with 3-month interval between the second and third doses), while 95 PLWH were placed in cohort 2 (with 5-month interval between the second and third doses);13 individuals were enrolled as healthy controls (HCs). And risk factors associated with seroconversion failure after vaccination were identified via Cox regression analysis. Results At 6 months after the third vaccination, PLWH in cohort 2 had higher NAb levels (GMC: 64.59 vs 21.99, P < 0.0001) and seroconversion rate (68.42% vs 19.05%, P < 0.0001). A weaker neutralizing activity against the SARSCoV-2 Delta variant was observed (GMT: 3.38 and 3.63, P < 0.01) relative to the wildtype strain (GMT: 13.68 and 14.83) in both cohorts. None of the participants (including HCs or PLWH) could mount a NAb response against Omicron BA.5.2. In the risk model, independent risk factors for NAb seroconversion failure were the vaccination interval (hazed ration [HR]: 0.316, P < 0.001) and lymphocyte counts (HR: 0.409, P < 0.001). Additionally, PLWH who exhibited NAb seroconversion after vaccination had fewer initial COVID-19 symptoms when infected with Omicron. Discussion This study demonstrated that the third vaccination elicited better NAb responses in PLWH, when a longer interval was used between vaccinations. Since post-vaccination seroconversion reduced the number of symptoms induced by Omicron, efforts to protect PLWH with risk factors for NAb seroconversion failure may be needed during future Omicron surges. Clinical trial registration https://beta.clinicaltrials.gov/study/NCT05075070, identifier NCT05075070.

Innovative technology-enhanced social work service during COVID-19: How 'Garden on the Balcony' promoted resilience, community bonds and a green lifestyle

The ongoing COVID-19 pandemic has motivated social workers to reckon with and transform traditions in service delivery. The development, application, and evaluation of technology-enhanced practices have become more vital than ever. Garden on the Balcony (GOB) was an innovative internet-based social work service designed to respond rapidly to the COVID-19 outbreak in Beijing. This paper introduces the underlying perspectives and design of GOB and reports participants' reflections on the program to understand its mechanisms and implications. Interview data from GOB participants were collected 4 months after the program ended. Thematic analysis generated three major themes, suggesting that GOB had (a) promoted individual resilience and family cohesion;(b) built online and offline community bonds;and (c) cultivated a green lifestyle and spiritual reflection on life. This study demonstrates a practical example of the effective use of technology-enhanced practice.

Multimodal Identification by Transcriptomics and Multiscale Bioassays of Active Components in Xuanfeibaidu Formula to Suppress Macrophage-Mediated Immune Response.

Xuanfeibaidu Formula (XFBD) is a Chinese medicine used in the clinical treatment of coronavirus disease 2019 (COVID-19) patients. Although XFBD has exhibited significant therapeutic efficacy in clinical practice, its underlying pharmacological mechanism remains unclear. Here, we combine a comprehensive research approach that includes network pharmacology, transcriptomics, and bioassays in multiple model systems to investigate the pharmacological mechanism of XFBD and its bioactive substances. High-resolution mass spectrometry was combined with molecular networking to profile the major active substances in XFBD. A total of 154 compounds were identified or tentatively characterized, including flavonoids, terpenes, carboxylic acids, and other types of constituents. Based on the chemical composition of XFBD, a network pharmacology-based analysis identified inflammation-related pathways as primary targets. Thus, we examined the anti-inflammation activity of XFBD in a lipopolysaccharide-induced acute inflammation mice model. XFBD significantly alleviated pulmonary inflammation and decreased the level of serum proinflammatory cytokines. Transcriptomic profiling suggested that genes related to macrophage function were differently expressed after XFBD treatment. Consequently, the effects of XFBD on macrophage activation and mobilization were investigated in a macrophage cell line and a zebrafish wounding model. XFBD exerts strong inhibitory effects on both macrophage activation and migration. Moreover, through multimodal screening, we further identified the major components and compounds from the different herbs of XFBD that mediate its anti-inflammation function. Active components from XFBD, including Polygoni cuspidati Rhizoma, Phragmitis Rhizoma, and Citri grandis Exocarpium rubrum, were then found to strongly downregulate macrophage activation, and polydatin, isoliquiritin, and acteoside were identified as active compounds. Components of Artemisiae annuae Herba and Ephedrae Herba were found to substantially inhibit endogenous macrophage migration, while the presence of ephedrine, atractylenolide, and kaempferol was attributed to these effects. In summary, our study explores the pharmacological mechanism and effective components of XFBD in inflammation regulation via multimodal approaches, and thereby provides a biological illustration of the clinical efficacy of XFBD.

Extending the dosing interval of COVID-19 vaccination leads to higher rates of seroconversion in people living with HIV.

Introduction: Vaccination against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is an effective way of protecting individuals from severe coronavirus disease 2019 (COVID-19). However, immune responses to vaccination vary considerably. This study dynamically assessed the neutralizing antibody (NAb) responses to the third dose of the inactivated COVID-19 vaccine administered to people living with human immunodeficiency virus (HIV; PLWH) with different inoculation intervals. Methods: A total of 171 participants were recruited: 63 PLWH were placed in cohort 1 (with 3-month interval between the second and third doses), while 95 PLWH were placed in cohort 2 (with 5-month interval between the second and third doses); 13 individuals were enrolled as healthy controls (HCs). And risk factors associated with seroconversion failure after vaccination were identified via Cox regression analysis. Results: At 6 months after the third vaccination, PLWH in cohort 2 had higher NAb levels (GMC: 64.59 vs 21.99, P < 0.0001) and seroconversion rate (68.42% vs 19.05%, P < 0.0001). A weaker neutralizing activity against the SARSCoV-2 Delta variant was observed (GMT: 3.38 and 3.63, P < 0.01) relative to the wildtype strain (GMT: 13.68 and 14.83) in both cohorts. None of the participants (including HCs or PLWH) could mount a NAb response against Omicron BA.5.2. In the risk model, independent risk factors for NAb seroconversion failure were the vaccination interval (hazed ration [HR]: 0.316, P < 0.001) and lymphocyte counts (HR: 0.409, P < 0.001). Additionally, PLWH who exhibited NAb seroconversion after vaccination had fewer initial COVID-19 symptoms when infected with Omicron. Discussion: This study demonstrated that the third vaccination elicited better NAb responses in PLWH, when a longer interval was used between vaccinations. Since post-vaccination seroconversion reduced the number of symptoms induced by Omicron, efforts to protect PLWH with risk factors for NAb seroconversion failure may be needed during future Omicron surges. Clinical trial registration: https://beta.clinicaltrials.gov/study/NCT05075070, identifier NCT05075070.

Community-Level Social Support to Mitigate the Impact of Combined Frailty and Multimorbidity on Psychological Distress Among Rural Chinese Older Adults During the COVID-19 Pandemic: Multilevel Modeling Study.

BACKGROUND: Accumulating research provides evidence that the psychological health of older people deteriorated from before to during the COVID-19 pandemic. Unlike robust individuals, coexisting frailty and multimorbidity expose older adults to more complicated and wide-ranging stressors. Community-level social support (CSS) is also an important impetus for age-friendly interventions, and it is 1 of the components of social capital that is seen as an ecological-level property. To date, we have not found research that examines whether CSS buffered the adverse impacts of combined frailty and multimorbidity on psychological distress in a rural setting during COVID-19 in China. OBJECTIVE: This study explores the combined effect of frailty and multimorbidity on psychological distress in rural Chinese older adults during the COVID-19 pandemic and examines whether CSS would buffer the aforementioned association. METHODS: Data used in this study were extracted from 2 waves of the Shandong Rural Elderly Health Cohort (SREHC), and the final analytic sample included 2785 respondents who participated in both baseline and follow-up surveys. Multilevel linear mixed effects models were used to quantify the strength of the longitudinal association between frailty and multimorbidity combinations and psychological distress using 2 waves of data for each participant, and then, cross-level interactions between CSS and combined frailty and multimorbidity were included to test whether CSS would buffer the adverse impact of coexisting frailty and multimorbidity on psychological distress. RESULTS: Frail older adults with multimorbidity reported the most psychological distress compared to individuals with only 1 or none of the conditions (ß=.68, 95% CI 0.60-0.77, P<.001), and baseline coexisting frailty and multimorbidity predicted the most psychological distress during the COVID-19 pandemic (ß=.32, 95% CI 0.22-0.43, P<.001). Further, CSS moderated the aforementioned association (ß=-.16, 95% CI -0.23 to -0.09, P<.001), and increased CSS buffered the adverse effect of coexisting frailty and multimorbidity on psychological distress during the COVID-19 pandemic (ß=-.11, 95% CI -0.22 to -0.01, P=.035). CONCLUSIONS: Our findings suggest that more public health and clinical attention should be paid to psychological distress among multimorbid older adults with frailty when facing public health emergencies. This research also suggests that community-level interventions prioritizing social support mechanisms, specifically improving the average levels of social support within communities, may be an effective approach to alleviate psychological distress for rural older adults who concurrently manifest frailty and multimorbidity.

Green bonds' liquidity in COVID-19 and low carbon investments in China: A stochastic trend analysis.

Central banks and regulators increasingly consider climate-related financial risks (CRFR) relevant to their responsibilities for maintaining financial stability and using daily data from 2016 to 2021 for China. Specifically, we used the S&P Green Bond Price Index, the Solactive Global Solar Price Index, the Solactive Global Wind Price Index, and the S&P Global Clean Energy and Carbon Price Index as our data set. We use the TVP-VAR method to probe return spillovers and interconnectedness. We test several portfolio strategies, including the minimum variance portfolio, the minimum correlation portfolio, and the more recent minimum connectedness portfolio. However, the evolving policy structure for dealing with CRFR has generally focused on market-based solutions that attempt to address perceived data gaps that preclude the appropriate pricing of CRFR, even though CRFR is thought to have certain distinctive features. Disclosure and openness fall within this category. We propose limiting the approach's influence since CRFR is characterized by extreme attainability. A 'precautionary' financial policy option is presented as an alternative, providing a conceptual foundation for justifying more aggressive financial policy intervention in the present to better cope with these long-term dangers.

Association of laparoscopically-confirmed endometriosis with long COVID-19: a prospective cohort study.

BACKGROUND: Women are at greater risk than men of developing chronic inflammatory conditions and "long COVID." However, few gynecologic health risk factors for long COVID-19 have been identified. Endometriosis is a common gynecologic disorder associated with chronic inflammation, immune dysregulation, and comorbid presentation with autoimmune and clotting disorders, all of which are pathophysiological mechanisms proposed for long COVID-19. Therefore, we hypothesized that women with a history of endometriosis may be at greater risk of developing long COVID-19. OBJECTIVE: This study aimed to investigate the association between history of endometriosis before SARS-CoV-2 infection and risk of long COVID-19. STUDY DESIGN: We followed 46,579 women from 2 ongoing prospective cohort studies-the Nurses' Health Study II and the Nurses' Health Study 3-who participated in a series of COVID-19-related surveys administered from April 2020 to November 2022. Laparoscopic diagnosis of endometriosis was documented prospectively in main cohort questionnaires before the pandemic (1993-2020) with high validity. SARS-CoV-2 infection (confirmed by antigen, polymerase chain reaction, or antibody test) and long-term COVID-19 symptoms (≥4 weeks) defined by the Centers for Disease Control and Prevention were self-reported during follow-up. Among individuals with SARS-CoV-2 infection, we fit Poisson regression models to assess the associations between endometriosis and risk of long COVID-19 symptoms, with adjustment for potential confounding variables (demographics, body mass index, smoking status, history of infertility, and history of chronic diseases). RESULTS: Among 3650 women in our sample with self-reported SARS-CoV-2 infections during follow-up, 386 (10.6%) had a history of endometriosis with laparoscopic confirmation, and 1598 (43.8%) reported experiencing long COVID-19 symptoms. Most women were non-Hispanic White (95.4%), with a median age of 59 years (interquartile range, 44-65). Women with a history of laparoscopically-confirmed endometriosis had a 22% greater risk of developing long COVID-19 (adjusted risk ratio, 1.22; 95% confidence interval, 1.05-1.42) compared with those who had never been diagnosed with endometriosis. The association was stronger when we defined long COVID-19 as having symptoms for ≥8 weeks (risk ratio, 1.28; 95% confidence interval, 1.09-1.50). We observed no statistically significant differences in the relationship between endometriosis and long COVID-19 by age, infertility history, or comorbidity with uterine fibroids, although there was a suggestive trend indicating that the association may be stronger in women aged <50 years (<50 years: risk ratio, 1.37; 95% confidence interval, 1.00-1.88; ≥50 years: risk ratio, 1.19; 95% confidence interval, 1.01-1.41). Among persons who developed long COVID-19, women with endometriosis reported on average 1 additional long-term symptom compared with women without endometriosis. CONCLUSION: Our findings suggest that those with a history of endometriosis may be at modestly increased risk for long COVID-19. Healthcare providers should be aware of endometriosis history when treating patients for signs of persisting symptoms after SARS-CoV-2 infection. Future studies should investigate the potential biological pathways underlying these associations.