Economic Growth and the Environment with Clean and Dirty Consumption

This paper aims to verify the existence of the Environmental Kuznets Curve (EKC) or inverted U-shaped relationship between economic growth and environmental degradation in the context of endogenous growth. An important feature of this study is that the EKC is examined in the presence of pollution as a by product of consumption activities; also, pollution is a stock variable rather than a flow and tends to accumulate over time. In order to highlight the role of consumption on the environment, consumers do not consider directly pollution in the maximization problem and are assumed to choose between two different consumption types, characterized by a different impact on the environment (i.e. dirty and clean consumption). We find that substitution of dirty consumption with clean consumption alone is not sufficient to reduce environmental pollution. The result depends on the product differentiation and the cost to achieve it. From a social welfare perspective, more environmental awareness is unambiguously desirable when it generates less pollution. However, it could be that more environmental awareness leads to a lower level of social welfare depending on the costs of product differentiation and social marginal damage of pollution.Environmental Kuznets Curve, Economic Growth, Pollution, Consumption, Consumption behaviour

Does employment generation really matter for poverty reduction ?

This paper analyzes how the employment/productivity profile of growth and its sectoral pattern are correlated with poverty reduction. The authors use a sample of 104 short-run growth spells in developing countries, between 1980 and 2001. They also identify some conditions of the labor market and the economic environment that are associated with employment-intensive growth or specific sectoral growth. The results show that, inthe short run, although the aggregate employment-rate intensity of growth does not matter for poverty reduction any more than the aggregate productivity intensity of growth, the sectoral pattern of employment growth and productivity growth is important. Employment-intensive growth in the secondary sector is associated with decreases in poverty, while employment-intensive growth in agriculture is correlated with poverty increases. Similarly, productivity-intensive growth in agriculture is associated with decreases in poverty. Although the study does not address causality, coincidence of these phenomena in this large sample of heterogeneous countries and periods suggests that, in the short run, the sectoral productivity and employment pattern of growth may have important implications for poverty alleviation. Therefore, policies for reducing poverty should not overlook the sectoral productivity and employment implications of different growth policies.Achieving Shared Growth,Labor Policies,Rural Poverty Reduction,Labor Markets,Population Policies

Quality assurance for automatically generated contours with additional deep learning

Objective: Deploying an automatic segmentation model in practice should require rigorous quality assurance (QA) and continuous monitoring of the model’s use and performance, particularly in high-stakes scenarios such as healthcare. Currently, however, tools to assist with QA for such models are not available to AI researchers. In this work, we build a deep learning model that estimates the quality of automatically generated contours. Methods: The model was trained to predict the segmentation quality by outputting an estimate of the Dice similarity coefficient given an image contour pair as input. Our dataset contained 60 axial T2-weighted MRI images of prostates with ground truth segmentations along with 80 automatically generated segmentation masks. The model we used was a 3D version of the EfficientDet architecture with a custom regression head. For validation, we used a fivefold cross-validation. To counteract the limitation of the small dataset, we used an extensive data augmentation scheme capable of producing virtually infinite training samples from a single ground truth label mask. In addition, we compared the results against a baseline model that only uses clinical variables for its predictions. Results: Our model achieved a mean absolute error of 0.020 ± 0.026 (2.2% mean percentage error) in estimating the Dice score, with a rank correlation of 0.42. Furthermore, the model managed to correctly identify incorrect segmentations (defined in terms of acceptable/unacceptable) 99.6% of the time. Conclusion: We believe that the trained model can be used alongside automatic segmentation tools to ensure quality and thus allow intervention to prevent undesired segmentation behavior

How future surgery will benefit from SARS-COV-2-related measures: a SPIGC survey conveying the perspective of Italian surgeons

COVID-19 negatively affected surgical activity, but the potential benefits resulting from adopted measures remain unclear. The aim of this study was to evaluate the change in surgical activity and potential benefit from COVID-19 measures in perspective of Italian surgeons on behalf of SPIGC. A nationwide online survey on surgical practice before, during, and after COVID-19 pandemic was conducted in March-April 2022 (NCT:05323851). Effects of COVID-19 hospital-related measures on surgical patients' management and personal professional development across surgical specialties were explored. Data on demographics, pre-operative/peri-operative/post-operative management, and professional development were collected. Outcomes were matched with the corresponding volume. Four hundred and seventy-three respondents were included in final analysis across 14 surgical specialties. Since SARS-CoV-2 pandemic, application of telematic consultations (4.1% vs. 21.6%; p < 0.0001) and diagnostic evaluations (16.4% vs. 42.2%; p < 0.0001) increased. Elective surgical activities significantly reduced and surgeons opted more frequently for conservative management with a possible indication for elective (26.3% vs. 35.7%; p < 0.0001) or urgent (20.4% vs. 38.5%; p < 0.0001) surgery. All new COVID-related measures are perceived to be maintained in the future. Surgeons' personal education online increased from 12.6% (pre-COVID) to 86.6% (post-COVID; p < 0.0001). Online educational activities are considered a beneficial effect from COVID pandemic (56.4%). COVID-19 had a great impact on surgical specialties, with significant reduction of operation volume. However, some forced changes turned out to be benefits. Isolation measures pushed the use of telemedicine and telemetric devices for outpatient practice and favored communication for educational purposes and surgeon-patient/family communication. From the Italian surgeons' perspective, COVID-related measures will continue to influence future surgical clinical practice

Time for a paradigm shift in shared decision-making in trauma and emergency surgery? Results from an international survey

Background: Shared decision-making (SDM) between clinicians and patients is one of the pillars of the modern patient-centric philosophy of care. This study aims to explore SDM in the discipline of trauma and emergency surgery, investigating its interpretation as well as the barriers and facilitators for its implementation among surgeons. Methods: Grounding on the literature on the topics of the understanding, barriers, and facilitators of SDM in trauma and emergency surgery, a survey was created by a multidisciplinary committee and endorsed by the World Society of Emergency Surgery (WSES). The survey was sent to all 917 WSES members, advertised through the society’s website, and shared on the society’s Twitter profile. Results: A total of 650 trauma and emergency surgeons from 71 countries in five continents participated in the initiative. Less than half of the surgeons understood SDM, and 30% still saw the value in exclusively engaging multidisciplinary provider teams without involving the patient. Several barriers to effectively partnering with the patient in the decision-making process were identified, such as the lack of time and the need to concentrate on making medical teams work smoothly. Discussion: Our investigation underlines how only a minority of trauma and emergency surgeons understand SDM, and perhaps, the value of SDM is not fully accepted in trauma and emergency situations. The inclusion of SDM practices in clinical guidelines may represent the most feasible and advocated solutions

Burnout among surgeons before and during the SARS-CoV-2 pandemic: an international survey

Background: SARS-CoV-2 pandemic has had many significant impacts within the surgical realm, and surgeons have been obligated to reconsider almost every aspect of daily clinical practice. Methods: This is a cross-sectional study reported in compliance with the CHERRIES guidelines and conducted through an online platform from June 14th to July 15th, 2020. The primary outcome was the burden of burnout during the pandemic indicated by the validated Shirom-Melamed Burnout Measure. Results: Nine hundred fifty-four surgeons completed the survey. The median length of practice was 10 years; 78.2% included were male with a median age of 37 years old, 39.5% were consultants, 68.9% were general surgeons, and 55.7% were affiliated with an academic institution. Overall, there was a significant increase in the mean burnout score during the pandemic; longer years of practice and older age were significantly associated with less burnout. There were significant reductions in the median number of outpatient visits, operated cases, on-call hours, emergency visits, and research work, so, 48.2% of respondents felt that the training resources were insufficient. The majority (81.3%) of respondents reported that their hospitals were included in the management of COVID-19, 66.5% felt their roles had been minimized; 41% were asked to assist in non-surgical medical practices, and 37.6% of respondents were included in COVID-19 management. Conclusions: There was a significant burnout among trainees. Almost all aspects of clinical and research activities were affected with a significant reduction in the volume of research, outpatient clinic visits, surgical procedures, on-call hours, and emergency cases hindering the training. Trial registration: The study was registered on clicaltrials.gov "NCT04433286" on 16/06/2020

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

The removal of fossil fuel subsidies in Italy and interactions with the 2030 EU climate and energy framework

The removal of environmentally harmful subsidies (EHS, henceforth) is at the centre of the international debate especially after the signature and entrance into force of the Paris Agreement. To evaluate the macroeconomic benefits stemming from the removal EHS we employed the global dynamic general equilibrium model ERMES (Economic Recursive-dynamic Model for Environmental Sustainability) based on the static model Gtap-E (McDougall et al., 2007) and on the Gtap 9 database (Aguiar et al., 2016) and includes representative firms and households and production factors. This type of models has been used extensively for the evaluation of fossil fuels subsidies removal (Burniaux and Chateau , 2011 and 2014, Bosello and Standardi, 2013; Jewell et al. 2018). The original structure of the Gtap-E model has been extensively modified and updated: the capital stock is not fixed but varies over time based on the so-called recursive dynamics; the energy system of the model has been carefully extended and considers the substitution (with CRESH functions, Hanoch 1975) between 11 different technologies; considers all GHGs: CO2 emissions, CH4, N2O and FGASS; the climate policy module is flexible enough to select the types of gas (CO2, CH4, N2O, FGAS), the sector (distinguishing between ETS and non-ETS) and the country

The removal of fossil fuel subsidies in Italy and interactions with the 2030 EU climate and energy framework

The removal of environmentally harmful subsidies (EHS, henceforth) is at the centre of the international debate especially after the signature and entrance into force of the Paris Agreement. To evaluate the macroeconomic benefits stemming from the removal EHS we employed the global dynamic general equilibrium model ERMES (Economic Recursive-dynamic Model for Environmental Sustainability) based on the static model Gtap-E (McDougall et al., 2007) and on the Gtap 9 database (Aguiar et al., 2016) and includes representative firms and households and production factors. This type of models has been used extensively for the evaluation of fossil fuels subsidies removal (Burniaux and Chateau , 2011 and 2014, Bosello and Standardi, 2013; Jewell et al. 2018). The original structure of the Gtap-E model has been extensively modified and updated: the capital stock is not fixed but varies over time based on the so-called recursive dynamics; the energy system of the model has been carefully extended and considers the substitution (with CRESH functions, Hanoch 1975) between 11 different technologies; considers all GHGs: CO2 emissions, CH4, N2O and FGASS; the climate policy module is flexible enough to select the types of gas (CO2, CH4, N2O, FGAS), the sector (distinguishing between ETS and non-ETS) and the country