UNASSIGNED: The significant rebound of influenza A (H1N1) virus activity, particularly among children, with rapidly growing number of hospitalized cases is of major concern in the post-COVID-19 era. The present study was performed to establish a prediction model of severe case in pediatric patients hospitalized with H1N1 infection during the post-COVID-19 era.
UNASSIGNED: This is a multicenter retrospective study across nine public tertiary hospitals in Yunnan, China, recruiting pediatric H1N1 inpatients hospitalized at five of these centers between February 1 and July 1, 2023, into the development dataset. Screening of 40 variables including demographic information, clinical features, and laboratory parameters were performed utilizing Least Absolute Shrinkage and Selection Operator (LASSO) regression and logistic regression to determine independent risk factors of severe H1N1 infection, thus constructing a prediction nomogram. Receiver operating characteristic (ROC) curve, calibration curve, as well as decision curve analysis (DCA) were employed to evaluate the model\'s performance. Data from four independent cohorts comprised of pediatric H1N1 inpatients from another four hospitals between July 25 and October 31, 2023, were utilized to externally validate this nomogram.
UNASSIGNED: The development dataset included 527 subjects, 122 (23.1 %) of whom developed severe H1N1 infection. The external validation dataset included 352 subjects, 72 (20.5 %) of whom were eventually confirmed as severe H1N1 infection. The LASSO regression identified 19 candidate predictors, with logistic regression further narrowing down to 11 independent risk factors, including underlying conditions, prematurity, fever duration, wheezing, poor appetite, leukocyte count, neutrophil-lymphocyte ratio (NLR), erythrocyte sedimentation rate (ESR), lactate dehydrogenase (LDH), interleukin-10 (IL-10), and tumor necrosis factor-α (TNF-α). By integrating these 11 factors, a predictive nomogram was established. In terms of prediction of severe H1N1 infection, excellent discriminative capacity, favorable accuracy, and satisfactory clinical usefulness of this model were internally and externally validated via ROC curve, calibration curve, and DCA, respectively.
UNASSIGNED: Our study successfully established and validated a novel nomogram model integrating underlying conditions, prematurity, fever duration, wheezing, poor appetite, leukocyte count, NLR, ESR, LDH, IL-10, and TNF-α. This nomogram can effectively predict the occurrence of serious case in pediatric H1N1 inpatients during the post-COVID-19 era, facilitating the early recognition and more efficient clinical management of such patients.

Between March and October 2022, a peak of detection of Bordetella parapertussis by qPCR, real-time PCR was observed in France.Hypothesis/Gap Statement. Whether this peak was due to resurgence from previous circulating lineages or reintroduction into the country was unknown.Objective. The objective of this study is to understand B. parapertussis-transient increase observed in France in 2022 whereas it had virtually stopped being reported since the start of the COVID-19 pandemic in 2020.Methods. We analysed real-time PCR (qPCR) data from the two largest French outpatient laboratories performing whooping cough diagnosis and characterized all B. parapertussis isolates collected in the 2016-2022 period by the French National Reference Centre for Whooping Cough.Results. Microbiological analyses reveal that 13 of 18 bacterial isolates collected in 2022 produce the vaccine antigen pertactin, whereas none of the 22 isolates collected in the 2016-2021 period did.Conclusion. We hypothesize a re-introduction of B. parapertussis from regions of the world where whole-cell vaccines are still in use.

UNASSIGNED: Global centers of epidemic prevention and control have entered a new stage of normalization, namely, the \"post-COVID-19 era.\" During the post-COVID-19 era, which is characterized by the time period following that with the most serious medical consequences, the psychosocial consequences of the COVID-19 pandemic began to receive worldwide attention, especially the degree of psychological distress it caused.
UNASSIGNED: This study explored the differential impact of gender role conflict on Chinese university students\' engagement in nonsuicidal self-injury (NSSI) as a function of biological sex following the global COVID-19 pandemic.
UNASSIGNED: Participants were 1,600 university students in northwestern China (M age = 21.3 years; 50.8% women) who completed online measures of demographic variables (including biological sex, gender role conflict, and NSSI engagement).
UNASSIGNED: Women reported significantly more gender role conflicts than men did, while engagement in NSSI was significantly more prevalent among men than women. A total of 262 men reported engaging in at least one NSSI behavior, resulting in a prevalence rate of 33.25%. In comparison, a total of 106 individuals reported engaging in at least one NSSI behavior, resulting in a prevalence rate of 13.05% among women. Gender role conflict was found to significantly predict university students\' NSSI engagement, regardless of biological sex.
UNASSIGNED: This is the first empirical study to identify sex differences in both gender role conflict and engagement in NSSI among university students in Northwestern China during the post-COVID-19 era. In addition, the present study is the first to demonstrate how gender role conflict predicts engagement in NSSI across sexes. These findings will inform the literature on gender role conflict and NSSI, particularly the close relationship between gender role conflict and engagement in NSSI among Chinese university students, and they emphasize the need for continued efforts to explore NSSI cross-culturally.

BACKGROUND: A healthy lifestyle is one of the important global concepts in the post-COVID-19 era, which can lead to maintaining and improving the health of societies. This study aimed to identify the factors affecting a healthy lifestyle in the post-COVID-19 era.
METHODS: The current research is a qualitative study that was conducted in the field by theoretical sampling method. The qualitative method used in the current research was Strauss-Corbin\'s method. The data collection tool in the current research was a semi-structured interview. The researcher reached theoretical saturation by the end of the 13th interview, and for more certainty, the interviews continued until the 15th interview. The statistical population of the research was all professors and experts with specialized doctorate degrees in Mashhad University of Medical Sciences, and finally, 15 people were selected according to the entry and exit criteria for the study. Data analysis was done by summarizing and coding and analyzing the hidden content from expert interviews using MAXQDA software.
RESULTS: The factors affecting a healthy lifestyle in the post-COVID-19 era (cultural norms, social norms, biological norms, technological factors, and economic factors) emerged from the intuitive opinions of experts.
CONCLUSIONS: Providing and maintaining health is not a simple task, as it involves biological, individual, familial, cultural, societal, economic, political, and health factors. Promotion of healthy lifestyles is not merely the responsibility of health-related organizations and bodies; rather, they necessitate extensive coordination and empathy among educational, health, cultural, service, and even political institutions and bodies.

BACKGROUND: The COVID-19 pandemic has profoundly affected human social contact patterns, but there is limited understanding regarding the post-pandemic social contact patterns. Our objective is to quantitatively assess social contact patterns in Suzhou post-COVID-19.
METHODS: We employed a diary design and conducted social contact surveys from June to October 2023, utilizing paper questionnaires. A generalized linear model was utilized to analyze the relationship between individual contacts and covariates. We examined the proportions of contact type, location, duration, and frequency. Additionally, age-related mixed matrices were established.
RESULTS: The participants reported an average of 11.51 (SD 5.96) contact numbers and a total of 19.78 (SD 20.94) contact numbers per day, respectively. The number of contacts was significantly associated with age, household size, and the type of week. Compared to the 0-9 age group, those in the 10-19 age group reported a higher number of contacts (IRR = 1.12, CI: 1.01-1.24), while participants aged 20 and older reported fewer (IRR range: 0.54-0.67). Larger households (5 or more) reported more contacts (IRR = 1.09, CI: 1.01-1.18) and fewer contacts were reported on weekends (IRR = 0.95, CI: 0.90-0.99). School had the highest proportion of contact durations exceeding 4 h (49.5%) and daily frequencies (90.4%), followed by home and workplace. The contact patterns exhibited clear age-assortative mixing, with Q indices of 0.27 and 0.28.
CONCLUSIONS: We assessed the characteristics of social contact patterns in Suzhou, which are essential for parameterizing models of infectious disease transmission. The high frequency and intensity of contacts among school-aged children should be given special attention, making school intervention policies a crucial component in controlling infectious disease transmission.

Knowing how workers return to work is a key policymaking issue for economic recovery in the post-COVID-19 era. This paper uses country-wide time-series mobile phone big data (comparing monthly and annual figures), obtained between February 2019 and October 2019 and between February 2020 and October 2020, to discover the spatial patterns of rural migrant workers\' (RMWs\') return to work in China\'s three urban agglomerations (UAs): the Beijing-Tianjin-Hebei Region, the Yangtze River Delta and the Pearl River Delta. Spatial patterns of RMWs\' return to work and how these patterns vary with location, city level and human attribute were investigated using the fine-scale social sensing related to post-pandemic human mobility. The results confirmed the multidimensional spatiotemporal differentiations, interaction effects between variable pairs and effects of the actual situation on the changing patterns of RMWs\' return to work. The spatial patterns of RMWs\' return to work in China\'s major three UAs can be regarded as a comprehensive and complex interaction result accompanying the nationwide population redistribution, which was affected by various hidden factors. Our findings provide crucial implications and suggestions for data-informed policy decisions for a harmonious society in the post-COVID-19 era.

BACKGROUND: The rebound of influenza A (H1N1) infection in post-COVID-19 era recently attracted enormous attention due the rapidly increased number of pediatric hospitalizations and the changed characteristics compared to classical H1N1 infection in pre-COVID-19 era. This study aimed to evaluate the clinical characteristics and severity of children hospitalized with H1N1 infection during post-COVID-19 period, and to construct a novel prediction model for severe H1N1 infection.
METHODS: A total of 757 pediatric H1N1 inpatients from nine tertiary public hospitals in Yunnan and Shanghai, China, were retrospectively included, of which 431 patients diagnosed between February 2023 and July 2023 were divided into post-COVID-19 group, while the remaining 326 patients diagnosed between November 2018 and April 2019 were divided into pre-COVID-19 group. A 1:1 propensity-score matching (PSM) was adopted to balance demographic differences between pre- and post-COVID-19 groups, and then compared the severity across these two groups based on clinical and laboratory indicators. Additionally, a subgroup analysis in the original post-COVID-19 group (without PSM) was performed to investigate the independent risk factors for severe H1N1 infection in post-COIVD-19 era. Specifically, Least Absolute Shrinkage and Selection Operator (LASSO) regression was applied to select candidate predictors, and logistic regression was used to further identify independent risk factors, thus establishing a prediction model. Receiver operating characteristic (ROC) curve and calibration curve were utilized to assess discriminative capability and accuracy of the model, while decision curve analysis (DCA) was used to determine the clinical usefulness of the model.
RESULTS: After PSM, the post-COVID-19 group showed longer fever duration, higher fever peak, more frequent cough and seizures, as well as higher levels of C-reactive protein (CRP), interleukin 6 (IL-6), IL-10, creatine kinase-MB (CK-MB) and fibrinogen, higher mechanical ventilation rate, longer length of hospital stay (LOS), as well as higher proportion of severe H1N1 infection (all P < 0.05), compared to the pre-COVID-19 group. Moreover, age, BMI, fever duration, leucocyte count, lymphocyte proportion, proportion of CD3+ T cells, tumor necrosis factor α (TNF-α), and IL-10 were confirmed to be independently associated with severe H1N1 infection in post-COVID-19 era. A prediction model integrating these above eight variables was established, and this model had good discrimination, accuracy, and clinical practicability.
CONCLUSIONS: Pediatric H1N1 infection during post-COVID-19 era showed a higher overall disease severity than the classical H1N1 infection in pre-COVID-19 period. Meanwhile, cough and seizures were more prominent in children with H1N1 infection during post-COVID-19 era. Clinicians should be aware of these changes in such patients in clinical work. Furthermore, a simple and practical prediction model was constructed and internally validated here, which showed a good performance for predicting severe H1N1 infection in post-COVID-19 era.

Online learning has evolved as an attractive and viable option for education, yet there is a need for further research to investigate the factors contributing to students\' online learning anxiety regarding the college English course. Based on Keegan\'s distance education framework, this study examines the factors impacting online learning anxiety among English as foreign language (EFL) students in the Chinese context during the post-COVID-19 era. Data were collected from 899 EFL students across different regions of China through an online survey. Follow-up interviews with ten students provided additional insights into the association between online English learning and anxiety. The collected data underwent descriptive analysis, exploratory factor analysis, reliability analysis, and multiple linear regression analysis to examine the relationship between online learning anxiety and the identified factors. The results of our study indicate that many Chinese EFL students experienced different degrees of anxiety, ranging from mild to moderate or severe. Moreover, online learning anxiety among Chinese EFL students was positively predicted by a lack of learning motivation, separation from instructors, separation from peers, and technological challenges, while a lack of two-way communication negatively predicted it. The findings underscore the importance of taking effective measures and offering psychological guidance for Chinese EFL students to alleviate anxiety and facilitate their successful adaptation to the new normal of online learning.

In the quest to strengthen resilient and sustainable recovery in the post-COVID-19 era, there is a huge requirement for manufacturing firms to adopt green finance which is dominated by green bond issuance. Nevertheless, published studies that provide insights on factors that influence the issuance of green bonds within manufacturing firms in the post-COVID-19 era and the impact on sustainable outcomes are currently non-existent. Therefore, this study analyzed the interrelationships that exist between the influencing factors of green bond issuance within manufacturing firms using decision-making trial and evaluation laboratory (DEMATEL) and data from Nigerian manufacturing firms. Then, a structural model of their importance levels was illustrated using interpretive structural modeling (ISM) while their impact on manufacturing sustainability outcomes was estimated with the aid of evaluation based on distance from average solution (EDAS). The study results highlight the key influencing factors of green bond issuance as environmental competencies, policy framing, low corruption, public awareness, and government support thereby signifying the criticality of strong institutions in facilitating green finance in the post-pandemic era. Besides, the study results demonstrate that green finance can significantly strengthen manufacturing sustainability in the post-COVID-19 era via green bonds by enhancing sustainable waste management, technological growth, and quality improvement as well as reducing carbon emissions. The study findings can provide a reference to decision-makers in manufacturing enterprises to predict scenarios and enact policies that facilitate the success of green finance in the post-COVID-19 era to further develop a low-carbon economy and increase competitive edge.

OBJECTIVE: Coronavirus disease-2019 (COVID-19) pandemic-related psychological symptoms can lead to smartphone addiction (SPA) risk and other behavioral disorders, thus impacting individuals\' mental health and well-being. The present study aims to propose a mediation model to investigate the association between emotional intelligence (EI) and SPA, and the mediating role of future anxiety (FA) during the post-COVID-19 era.
METHODS: An online questionnaire including the Emotional Intelligence Scale, the Dark Future Scale, and the Smartphone Addiction Scale among university students from China, was conducted between September 14 and November 22, 2022. Finally, 1,154 valid questionnaires were collected. The reliability and confirmatory factor analysis results showed that all three scales had good reliability and validity.
RESULTS: Structural Equation Model demonstrated that EI significantly and negatively influenced SPA (β=0.211, p<0.001), university students\' FA significantly and positively effected SPA (β=0.315, p<0.001), EI significantly predicted SPA in university students, and FA partially mediated the association between EI and SPA. The mediation effect of FA was 0.110, which accounted for 34.27% of the total effect. Bootstrap results furthermore tested the rigor of the mediating effect.
CONCLUSIONS: These findings broaden our understanding regarding the relationship between EI and SPA and the mediating role of FA, providing new sights for educators on how to reduce the risk of SPA when confronting the ongoing and possible future pandemics.