Search Results (855)

Early-career teachers (ECTs) entered the profession during the COVID-19 pandemic, a period that introduced unique stressors to an already-demanding career phase. This systematic review examines empirical studies published between 2020 and February 2025 to explore how the pandemic influenced ECT wellbeing, with particular attention to stressors and protective factors impacting long-term retention and professional sustainability. Guided by PRISMA protocols, databases including Web of Science, ERIC, Google Scholar, and Scopus were searched, screening 470 records and identifying 30 studies that met inclusion criteria: peer-reviewed, empirical, focused on early-career teachers (within the first five years), and situated in or explicitly addressing the pandemic and its ongoing impacts. The results of Braun and Clarke’s thematic analysis (2006) revealed that pandemic-related challenges such as increased workload, professional isolation, disrupted induction processes, and emotional strain have persisted into the post-pandemic era, contributing to sustained risks of burnout and attrition. Regardless, protective factors identified during the pandemic—including high-quality mentoring, structured induction programmes, collegial support, professional autonomy, and effective individual coping strategies—continue to offer essential support, enhancing resilience and professional wellbeing. These findings underscore the necessity of institutionalising targeted supports to address the enduring effects of pandemic-related stressors on ECT wellbeing. By prioritising sustained mental health initiatives and structural supports, education systems can effectively mitigate long-term impacts and improve retention outcomes for early-career teachers in a post-pandemic educational landscape. Full article

The COVID-19 pandemic triggered unprecedented economic disruptions, raising critical questions about the resilience and adaptability of macroeconomic productivity across countries. This study examines the impact of COVID-19 on macroeconomic efficiency and productivity dynamics in 37 OECD countries using quarterly data from 2018Q1 to 2024Q4. By employing a Slack-Based Measure Data Envelopment Analysis (SBM-DEA) and the Malmquist Productivity Index (MPI), we decompose total factor productivity (TFP) into efficiency change (EC) and technological change (TC) across three periods: pre-pandemic, during-pandemic, and post-pandemic. Our framework incorporates both desirable (GDP) and undesirable outputs (inflation, unemployment, housing price inflation, and interest rate distortions), offering a multidimensional view of macroeconomic efficiency. Results show broad but uneven productivity gains, with technological progress proving more resilient than efficiency during the pandemic. Post-COVID recovery trajectories diverged, reflecting differences in structural adaptability and innovation capacity. Regression analysis reveals that stringent lockdowns in 2020 were associated with lower productivity in 2023–2024, while more adaptive policies in 2021 supported long-term technological gains. These findings highlight the importance of aligning crisis response with forward-looking economic strategies and demonstrate the value of DEA-based methods for evaluating macroeconomic performance beyond GDP. Full article

Background and Objectives: Preterm birth and stillbirth are primary adverse pregnancy outcomes. Research during the COVID-19 pandemic revealed reductions in preterm birth in some countries, while stillbirth rates increased or remained unchanged. These findings suggest the presence of preventable risk factors associated with changes in physical activity and lower exposure to community-acquired infections due to lockdown measures, altered social interaction patterns or reduced access to antenatal care. Assessing seasonal variation may offer insights into whether lifestyle changes during the COVID-19 lockdown period influenced preterm birth rates. Materials and Methods: This retrospective cohort study used data from the electronic medical records of Bihor and Sibiu counties. Preterm deliveries (<37 weeks) and stillbirths during the COVID-19 pandemic (2020 and 2021) were compared with the corresponding pre-pandemic (2018 and 2019) and post-pandemic (2022 and 2023) period. Preterm birth rates during summer and winter in the pre-pandemic, pandemic, and post-pandemic years were analyzed. A comparison with rates during strict lockdown was made. Results: Out of 52,021 newborn infants, 4473 were born preterm. Preterm birth rates remained stable across all three periods (p = 0.13), and no significant seasonal pattern was identified (p = 0.65). In contrast, stillbirth rates increased notably during the strict lockdown period, with the median incidence almost doubling compared to other periods (0.87%, p = 0.05), while remaining unchanged during the rest of the pandemic (p = 0.52). Conclusions: Our study found that preterm birth rates remained unaffected by the pandemic and lockdown periods, while stillbirths increased significantly during the strict lockdown. These findings highlight the importance of maintaining access to timely antenatal care during public health emergencies to prevent adverse perinatal outcomes. Full article

With the development of information and communication technologies, analysing new risks of moral harassment at work is becoming increasingly pertinent, especially with the expansion of teleworking and hybrid working (a mix of remote and face-to-face work per week) in the wake of the COVID-19 pandemic. In an attempt to respond to the new issues of labour regulation, this study places special emphasis on new risks of moral harassment in hybrid work and teleworking contexts, considering both the international and European framework and the legal regime in Portugal, identifying its specificities. With the rise in teleworking in the post-pandemic period, the online monitoring of workers has accentuated the difficulty in drawing the line between managerial power and harassment. Moral harassment at work is a persistent challenge and organisations must recognise, prevent and respond to inappropriate behaviour in the organisation. The results of this study—based on the results of an online survey completed by employees (with employment contracts)—show that teleworking employees recognise that they have been pressured, above all, both to respond to messages quickly and pressure to work beyond hours and suggest possible gender differences in the way harassment in hybrid work and teleworking contexts is reported. Full article

Amid ongoing societal development, tourists’ travel behavior patterns have been undergoing substantial transformations, and understanding their evolution has emerged as a key area of scholarly interest. Taking Beijing as a case study, this research aims to uncover the spatiotemporal evolution patterns of tourist flows and their underlying driving mechanisms. Based on digital footprint relational data, a dual-perspective analytical framework—“tourist perception–tourist flow network”—is constructed. By integrating the center-of-gravity model, social network analysis, and regression models, the study systematically examines the dynamic spatial structure of tourist flows in Beijing from 2012 to 2024. The findings reveal that in the post-pandemic period, Beijing tourists place greater emphasis on the cultural connotation and experiential aspects of destinations. The gravitational center of tourist flows remains relatively stable, with core historical and cultural blocks retaining strong appeal, though a slight shift has occurred due to policy influences and emerging attractions. The evolution of the spatial network structure reveals that tourism flows have become more dispersed, while the influence of core scenic spots continues to intensify. Government policy orientation, tourism information retrieval, and the agglomeration of tourism resources significantly promote the structure of tourist flows, whereas the general level of tourism resources exerts no notable influence. These findings offer theoretical insights and practical guidance for the sustainable development and regional coordination of tourism in Beijing, and provide a valuable reference for the spatial restructuring of urban tourism in the post-COVID-19 era. Full article

We investigate how the factors influencing aircraft utilization have changed during and post-Pandemic depending on the business model before. We classify the Pandemic into three periods (pre-, during and post- Pandemic) and the business models into three types (Total, FSC and LCC). For each group, we analyze the importance of factors using the SHAP and Random Forest models. Through group-difference tests on factor importance, we examine whether there are significant differences across the three periods and business models. According to the findings of the ANOVA (Analysis of Variance) and the Kruskal–Wallis assay, the importance of factors influencing aircraft utilization has changed across all business models over the three periods. Pre-Pandemic, a coincident index and a consumer price index were the principal factors. However, the exchange rate (KRW/EUR) gained significant importance during the Pandemic. This suggests that the Pandemic’s impact on the aviation industry was not limited to reduced demand but was also associated with changes in the importance of exchange rates and key business indicators for airline operations. Pre-Pandemic, there were significant differences among the business model groups. However, no meaningful differences were observed during and post-Pandemic. In other words, it seems that the leading indexes were closely interconnected pre-Pandemic, whereas lagging indexes and exchange rate became closely interconnected afterward. A group-difference test confirmed that no differences were observed among the business models, but differences were evident when considering the groups in their entirety. We presented the implications for changes in airline decision-making to understand changes in the aviation industry caused by the Pandemic, by identifying how the factors influencing aircraft utilization were altered. Full article

This study examines the safety and cost-effectiveness of implementing shoulder rumble strips (SRS) and road lighting on Saudi Arabian freeways, providing insights into their roles in fostering sustainable transport systems. By leveraging the Highway Safety Manual (HSM) framework, this research develops localized Crash Modification Factors (CMFs) for these interventions, ensuring evidence-based and context-specific evaluations. Data were collected for two periods—pre-pandemic (2017–2019) and post-pandemic (2021–2022). For each period, we obtained traffic crash records from the Saudi Highway Patrol database, traffic volume data from the Ministry of Transport and Logistic Services’ automated count stations, and roadway characteristics and pavement-condition metrics from the National Road Safety Center. The findings reveal that SRS reduces fatal and injury run-off-road crashes by 52.7% (CMF = 0.473) with a benefit–cost ratio of 14.12, highlighting their high cost-effectiveness. Road lighting, focused on nighttime crash reduction, decreases such crashes by 24% (CMF = 0.760), with a benefit–cost ratio of 1.25, although the adoption of solar-powered lighting systems offers potential for greater sustainability gains and a higher benefit–cost ratio. These interventions align with global sustainability goals by enhancing road safety, reducing the socio-economic burden of crashes, and promoting the integration of green technologies. This study not only provides actionable insights for achieving KSA Vision 2030’s target of improved road safety but also demonstrates how engineering solutions can be harmonized with sustainability objectives to advance equitable, efficient, and environmentally responsible transportation systems. Full article

Ride-pooling, as a sustainable mode of ride-hailing services, enables different riders to share a vehicle while traveling along similar routes. The COVID-19 pandemic led to the suspension of this service, but Transportation Network Companies (TNCs) such as Uber and Lyft resumed it after a significant delay following the lockdown. This raises the question of what determinants shape ride-pooling in the post-pandemic era and how they spatially influence shared ride-hailing compared to the pre-pandemic period. To address this gap, this study employs geospatial analysis and machine learning to examine the factors affecting ride-pooling trips in pre- and post-pandemic periods. Using over 66 million trip records from 2019 and 43 million from 2023, we observe a significant decline in shared trip adoption, from 16% to 2.91%. The results of an extreme gradient boosting (XGBoost) model indicate a robust capture of non-linear relationships. The SHAP analysis reveals that the percentage of the non-white population is the dominant predictor in both years, although its influence weakened post-pandemic, with a breakpoint shift from 78% to 90%, suggesting reduced sharing in mid-range minority areas. Crime density and lower car ownership consistently correlate with higher sharing rates, while dense, transit-rich areas exhibit diminished reliance on shared trips. Our findings underscore the critical need to enhance transportation integration in underserved communities. Concurrently, they highlight the importance of encouraging shared ride adoption in well-served, high-demand areas where solo ride-hailing is prevalent. We believe these results can directly inform policies that foster more equitable, cost-effective, and sustainable shared mobility systems in the post-pandemic landscape. Full article

This research focuses on medium-term load forecasting in a tropical region post-pandemic. This study presents one of the first attempts to analyze medium-term forecasting using half-hourly resolution in the Java-Bali power system post-COVID-19 period. The dataset comprises load measurements recorded every 30 min (48 data points per day) from 2014 to 2022. Three distinct methods, namely polynomial regression, split polynomial regression, and Long Short-Term Memory (LSTM) networks, were employed and compared to predict the electricity load demand. The analysis found that LSTM outperformed the other methods, exhibiting the lowest error rates with Mean Absolute Percentage Error (MAPE) at 3.86% and Root Mean Squared Error (RMSE) at 1247.93. Additionally, a consistent observation emerged, showing that all methods performed better in predicting load demand during nighttime hours (6 p.m. to 6 a.m.). The hypothesis is that data stability during nighttime, with fewer significant fluctuations, contributed to the improved prediction accuracy. These findings provide valuable insights for improving load forecasting in the post-pandemic tropical region and offer opportunities for enhancing power grid efficiency and reliability. Full article

The COVID-19 pandemic significantly impacted the circulation, seasonality, and disease burden of viral respiratory infections. This study aimed to evaluate the impact of SARS-CoV-2 on the frequency of viral respiratory infections at a teaching hospital in Southern Italy by comparing data from before, during, and after the COVID-19 pandemic and by investigating how the emergence of SARS-CoV-2 affected the circulation and seasonality of other respiratory viruses. This retrospective and prospective study was performed on de-identified nasopharyngeal specimens classified as pre-COVID-19 (before 15 March 2020), during-COVID-19 (from 16 March 2020 to 5 May 2023), and post-COVID-19 (from 6 May 2023 to 31 December 2024). Overall, 790 out of 3930 (20%) patient samples tested positive for at least one respiratory virus. The mean age of patients was 60 ± 19 years, with significant positivity rates observed in the 65–98 age group (p ≤ 0.05) across all periods. In the pre-COVID-19 period, the most prevalent virus was influenza A (47.5%, 47/99), followed by the human rhinovirus (19.2%, 19/99). During the COVID-19 pandemic, SARS-CoV-2 was the most prevalent (64.9%, 290/447), before decreasing to 38% (92/244) after the pandemic, while influenza A’s positivity prevalence increased to 14.3% (35/244). Rhinovirus/enterovirus remained relatively stable throughout all periods. The pandemic notably altered viral co-infection dynamics, with its effects lasting into the post-COVID-19 period. Specifically, a marked decrease in influenza A circulation was observed, while respiratory syncytial virus (RSV) epidemiology remained stable and significant co-circulation of rhinovirus/enterovirus with SARS-CoV-2 persisted. Therefore, since COVID-19 and influenza affect the same high-risk groups, those individuals must be vaccinated against both viruses. Full article

(1) Background: Physical activity (PA) plays a crucial role in preserving and enhancing mental health, particularly in the aftermath of major health crises such as the COVID-19 pandemic. However, the specific levels and domains of physical activity that have the greatest impact on alleviating symptoms of anxiety, depression, and stress in the post-COVID-19 period remain unclear. The aim of this study was to examine the influence of different levels and domains of PA on mental health parameters, specifically symptoms of anxiety, depression, and stress, in individuals who had recovered from COVID-19. (2) Methods: The study included initial measurements (2–4 weeks post-recovery) and final measurements (14–16 weeks post-recovery). The sample comprised 288 participants aged 20 to 60 years (M = 47.06; SD = 12.41), with 95 men and 193 women. PA was assessed using the long version of the IPAQ questionnaire, while mental health was evaluated using the long version of the DASS scale. (3) Results: Stepwise regression analysis revealed that low- (p = 0.010) and moderate-intensity (p = 0.022) PA was significantly associated with reductions in anxiety symptoms as well as lower stress levels (low PA: p = 0.014; moderate PA: p = 0.042). Total PA (p < 0.001) and vigorous-intensity PA (p = 0.008) emerged as significant predictors of reduced depression levels. Among the domains of PA, home-based activities had a statistically significant impact on all three mental health components: anxiety (p = 0.005), depression (p = 0.002), and stress (p = 0.041). Transport-related PA was significantly associated with anxiety (p = 0.011) and stress (p = 0.022), but not with depression. (4) Conclusions: The results suggest that a combined model incorporating different levels and domains of PA may represent an effective approach to improving mental health in individuals recovering from COVID-19. Further longitudinal studies are needed to establish more precise causal relationships. Full article

Background: The long-term impact of SARS-CoV-2 infection on pulmonary function remains insufficiently characterised, particularly among individuals who have experienced mild or asymptomatic disease. This study aimed to assess spirometric changes over a three-year period and evaluate potential associations with demographic and clinical variables. Methods: We retrospectively analysed spirometry data from 103 healthcare workers (HCWs) who underwent pulmonary function tests at three time points: before the pandemic (Time 0), one year post-pandemic (Time 1), and two years post-pandemic (Time 2). Linear regression models were employed to evaluate the impact of various factors, including age, BMI, gender, smoking status, history of SARS-CoV-2 infection, vaccination status prior to infection, and the number of infections, on changes in FVC and FEV₁. Results: A statistically significant decrease in both FVC and FEV₁ were observed at Time 1 and Time 2 compared to baseline (p < 0.05). Smoking habits were significantly associated with a greater decline in both FVC and FEV₁. Multiple infections were associated with larger reductions in FVC at Time 1. No significant associations were found with age, gender, BMI, or vaccination status. Even in the absence of severe symptoms of the disease, healthcare workers exhibited a measurable decline in pulmonary function over time. Smoking and reinfection emerged as relevant factors associated with reduced lung capacity. Conclusions: These findings emphasise the need for ongoing respiratory monitoring in occupational settings and the importance of targeted preventive measures. Full article

Since the early 21st century, urban shrinkage has become a significant global phenomenon. Dongguan, in Guangdong Province, China, is known as a “world factory”. It experienced notable urban shrinkage following the 2008 financial crisis. However, the city demonstrated remarkable recovery and ongoing development in subsequent years. On that basis, this study focuses on the following three points: (1) identifying the spatiotemporal factors contributing to the growth and shrinkage of manufacturing cities, taking Dongguan as an example; (2) explaining the influencing factors of the growth and shrinkage of Dongguan City during three critical periods, 2008–2014 (post-crisis), 2015–2019 (as machinery replaced human work), and 2020–2023 (the COVID-19 pandemic and recovery); and (3) selecting representative towns and streets for on-site observation and investigation, analyzing the measures they have taken to cope with growth and shrinkage during different periods. The key findings include the following: (1) The spatial dynamics of growth and shrinkage in Dongguan show significant temporal patterns, with traditional manufacturing areas shrinking from 2008 to 2014, central urban areas recovering from 2015 to 2019, and renewed shrinkage from 2020 to 2023. However, some regions maintained stability through strategic innovations. (2) Various factors, particularly industrial upgrading and technological innovation, drove the urban dynamics, enhancing economic resilience. (3) The case study of Houjie Town revealed successful adaptive mechanisms supported by policy while facing challenges like labor mismatches and inadequate R&D investment. This research offers insights for improving urban resilience and promoting sustainable development in Dongguan. Full article

This paper investigates the impact of the transition from manufacturing to tourism on sectoral productivity, output prices, and labor costs. Using panel data econometric models for 15 selected EU countries from 2011 to 2023, the study confirms key dynamics predicted by Baumol’s cost disease (BCD) hypothesis. The findings reveal that higher productivity is positively associated with both implied prices and hourly labor costs across sectors, supporting the wage equalization mechanism central to BCD. However, the relationship between productivity and wages or prices is weaker in labor-intensive sectors like tourism, underscoring their structural vulnerability to wage-driven cost pressures. Additionally, the analysis captures the impact of major external shocks, including the COVID-19 pandemic and the Russo–Ukrainian war, treated as jointly sourced super-shocks. The regression results indicate significant price disruptions following these shocks, whereas no statistically significant trend in labor costs was detected in the post-treatment period. These results highlight the differential effects of external shocks on wages versus prices, emphasizing the challenges faced by low-productivity, labor-intensive sectors in managing cost dynamics. The findings provide valuable insights for policymakers addressing sectoral imbalances in the context of BCD and navigating the economic consequences of global disruptions. Full article

Background: Obesity during pregnancy is associated with an elevated risk of severe COVID-19, including higher rates of maternal complications, intensive care admission, and adverse neonatal outcomes. The impact of combination of SARS-CoV-2 infection and maternal obesity in placental pathology has not been properly investigated. Aim: To compare the histopathological changes in the placenta induced by active SARS-CoV-2 infection in obese and non-obese patients. Methods: This retrospective cohort study included human placentas from non-obese women and pre-gestationally obese women with active SARS-CoV-2 infection (SARS and OB+SARS, respectively), and placentas from non-obese women and pre-gestationally obese women without SARS-CoV-2 infection (control and OB, collected in the post- and pre-pandemic periods, respectively). Results: A higher (50%) occurrence of ischemic injury and subchorionic fibrin deposits and a 15× higher risk of occurrence of these lesions were found in the OB+SARS group, in relation to control. In contrast, a 10% lower risk of developing chorangiosis in the OB+SARS group than the OB group was observed. Conclusions: An increased risk of lesions related to both maternal and fetal malperfusion and ischemic injury and a lower risk for chorangiosis exist in placentas from obese women affected by SARS-CoV-2 infection. Importantly, these differences were not observed in placentas from non-obese women. Full article