Mortality from gastrointestinal congenital anomalies at 264 hospitals in 74 low-income, middle-income, and high-income countries: a multicentre, international, prospective cohort study

Summary Background Congenital anomalies are the fifth leading cause of mortality in children younger than 5 years globally. Many gastrointestinal congenital anomalies are fatal without timely access to neonatal surgical care, but few studies have been done on these conditions in low-income and middle-income countries (LMICs). We compared outcomes of the seven most common gastrointestinal congenital anomalies in low-income, middle-income, and high-income countries globally, and identified factors associated with mortality. Methods We did a multicentre, international prospective cohort study of patients younger than 16 years, presenting to hospital for the first time with oesophageal atresia, congenital diaphragmatic hernia, intestinal atresia, gastroschisis, exomphalos, anorectal malformation, and Hirschsprung’s disease. Recruitment was of consecutive patients for a minimum of 1 month between October, 2018, and April, 2019. We collected data on patient demographics, clinical status, interventions, and outcomes using the REDCap platform. Patients were followed up for 30 days after primary intervention, or 30 days after admission if they did not receive an intervention. The primary outcome was all-cause, in-hospital mortality for all conditions combined and each condition individually, stratified by country income status. We did a complete case analysis. Findings We included 3849 patients with 3975 study conditions (560 with oesophageal atresia, 448 with congenital diaphragmatic hernia, 681 with intestinal atresia, 453 with gastroschisis, 325 with exomphalos, 991 with anorectal malformation, and 517 with Hirschsprung’s disease) from 264 hospitals (89 in high-income countries, 166 in middleincome countries, and nine in low-income countries) in 74 countries. Of the 3849 patients, 2231 (58·0%) were male. Median gestational age at birth was 38 weeks (IQR 36–39) and median bodyweight at presentation was 2·8 kg (2·3–3·3). Mortality among all patients was 37 (39·8%) of 93 in low-income countries, 583 (20·4%) of 2860 in middle-income countries, and 50 (5·6%) of 896 in high-income countries (p<0·0001 between all country income groups). Gastroschisis had the greatest difference in mortality between country income strata (nine [90·0%] of ten in lowincome countries, 97 [31·9%] of 304 in middle-income countries, and two [1·4%] of 139 in high-income countries; p≤0·0001 between all country income groups). Factors significantly associated with higher mortality for all patients combined included country income status (low-income vs high-income countries, risk ratio 2·78 [95% CI 1·88–4·11], p<0·0001; middle-income vs high-income countries, 2·11 [1·59–2·79], p<0·0001), sepsis at presentation (1·20 [1·04–1·40], p=0·016), higher American Society of Anesthesiologists (ASA) score at primary intervention (ASA 4–5 vs ASA 1–2, 1·82 [1·40–2·35], p<0·0001; ASA 3 vs ASA 1–2, 1·58, [1·30–1·92], p<0·0001]), surgical safety checklist not used (1·39 [1·02–1·90], p=0·035), and ventilation or parenteral nutrition unavailable when needed (ventilation 1·96, [1·41–2·71], p=0·0001; parenteral nutrition 1·35, [1·05–1·74], p=0·018). Administration of parenteral nutrition (0·61, [0·47–0·79], p=0·0002) and use of a peripherally inserted central catheter (0·65 [0·50–0·86], p=0·0024) or percutaneous central line (0·69 [0·48–1·00], p=0·049) were associated with lower mortality. Interpretation Unacceptable differences in mortality exist for gastrointestinal congenital anomalies between lowincome, middle-income, and high-income countries. Improving access to quality neonatal surgical care in LMICs will be vital to achieve Sustainable Development Goal 3.2 of ending preventable deaths in neonates and children younger than 5 years by 2030

Revealing the spatio-temporal energy consumption of a mediterranean city : the case of beirut

Pour réduire les émissions de gaz à effet de serre et la consommation d'énergie dans les zones urbaines, il est essentiel de comprendre les performances énergétiques et les modes de consommation des bâtiments pour pouvoir mettre en œuvre des stratégies efficaces de gestion de l'énergie et d'efficacité énergétique à l'échelle de la ville. La mise en œuvre à grande échelle de tels plans nécessite des informations sur la manière dont les demandes en énergie peuvent changer dans le cadre d'interventions spécifiques. Les modèles énergétiques de bâtiments à l'échelle urbaine (UBEM) sont des outils proposés pour estimer la demande énergétique actuelle et future des bâtiments. Ces modèles reposent sur une approche ascendante (bottom-up approach) combinant à la fois des techniques statistiques et des méthodes basées sur la physique thermodynamique. Cette étude vise à fournir une approche de modélisation améliorée simulant la demande énergétique des bâtiments à haute résolution spatiale et temporelle, ce qui peut aider à évaluer les stratégies de gestion de l'énergie et les politiques énergétiques décisionnelles. La méthodologie est appliquée pour la ville de Beyrouth, représentative de la région méditerranéenne, où la similarité des technologies de construction et des préoccupations climatiques de ses villes est prononcée. Les objectifs principaux de la thèse sont de développer, étudier et calibrer un outil de modélisation énergétique ascendante à l'échelle urbaine ; fournir des preuves de la pertinence de l'outil pour soutenir les directives pour les interventions futures ; et enfin, étudier l'impact de la compacité de la ville sur la disponibilité de la lumière du jour et donc sur le bien-être des citoyens. Dans cette étude de cas basée sur deux quartiers différents de la ville, un modèle énergétique de bâtiment à échelle urbaine approximativement, applé BEirut Energy Model BEEM, est généré pour estimer la consommation d'électricité du stock de bâtiment. Afin de réduire le temps de modélisation et de calcul, une classification archétypale des bâtiments basée sur leurs types et leurs périodes de construction est adoptée. Les informations supplémentaires requises pour générer le modle 3D des bâtiments sont le nombre d'étages, la superficie des bâtiments et une carte topographique des zones d'étude. En couplant les modèles aux conditions météorologiques horaires, le modèle thermodynamique de 3,630 bâtiments est simulé dans EnergyPlus. L'adaptation du modèle à l'occupation de Beyrouth et aux comportements des utilisateurs est cruciale pour renforcer la fiabilité de BEEM. La disponibilité des données d'électricité actuelles permet la calibration du modèle, qui repose sur le regroupement des bâtiments et la recherche des coefficients des regroupements représentatifs de modèles d'énergie spécifiques.To reduce greenhouse gas emissions and energy consumption in urban areas, understanding buildings' energy performance and consumption patterns is essential for implanting effective energy management and efficiency strategies at a city scale. Such plans' implementation at large scale requires information on how the energy demands may change under specific interventions. Urban Building Energy Models (UBEM) are proposed tools to estimate current and future building's energy demand. These models rely on a bottom-up approach, combining both statistical techniques and physics-based methods. This study aims at providing an enhanced modeling approach that simulates buildings' energy demand at high spatial and temporal resolution, which can help in evaluating energy management strategies and decision-making energy policies. The methodology is applied for the city of Beirut, representative of the Mediterranean region where the similarity of buildings technologies and climatic concerns among its cities is pronounced. The main objectives of the thesis are to develop, investigate and adjust a bottom-up energy modeling tool at urban scale; to provide evidence of the tool's suitability to support guidelines for future interventions; and finally to investigate the impact of the city's compactness on daylight availability and thus citizens' well-being. In this case study based on two different districts within the city, a near-city-scale building energy model, BEirut Energy Model BEEM, is generated to estimate the building's stock electricity consumption. To reduce the modeling and computation time, an archetypal classification of the buildings based on their types and periods of construction is adopted. The additional information required to generate the 3D model of the buildings are the number of floors, buildings' areas and a topographic map of the study areas. By coupling the models to the hourly weather conditions, the thermodynamic model of 3,630 buildings is simulated in EnergyPlus. Adapting the model to Beirut's occupancy and users' behaviors is crucial to enhance the reliability of BEEM. The availability of metered electricity data allows the model calibration, which is based on buildings' clustering and finding the clusters' coefficients representative of specific energy patterns. After the training phase, the model's accuracy in predicting electricity consumption is improved. Comparing the actual consumption and the calibrated results, the averaged absolute percentage error of the electricity consumption was reduced from 310% to 41% in district A and from 326% to 39% in district B. The calibrated model is combined with Geographic Information System (GIS) for a spatiotemporal distribution of energy demand patterns, which can help in assessing the most suitable intervention technologies

Révéler l'utilisation énergétique spatio-temporelle d'une ville côtière méditerranéenne : le cas de Beyrouth

To reduce greenhouse gas emissions and energy consumption in urban areas, understanding buildings' energy performance and consumption patterns is essential for implanting effective energy management and efficiency strategies at a city scale. Such plans' implementation at large scale requires information on how the energy demands may change under specific interventions. Urban Building Energy Models (UBEM) are proposed tools to estimate current and future building's energy demand. These models rely on a bottom-up approach, combining both statistical techniques and physics-based methods. This study aims at providing an enhanced modeling approach that simulates buildings' energy demand at high spatial and temporal resolution, which can help in evaluating energy management strategies and decision-making energy policies. The methodology is applied for the city of Beirut, representative of the Mediterranean region where the similarity of buildings technologies and climatic concerns among its cities is pronounced. The main objectives of the thesis are to develop, investigate and adjust a bottom-up energy modeling tool at urban scale; to provide evidence of the tool's suitability to support guidelines for future interventions; and finally to investigate the impact of the city's compactness on daylight availability and thus citizens' well-being. In this case study based on two different districts within the city, a near-city-scale building energy model, BEirut Energy Model BEEM, is generated to estimate the building's stock electricity consumption. To reduce the modeling and computation time, an archetypal classification of the buildings based on their types and periods of construction is adopted. The additional information required to generate the 3D model of the buildings are the number of floors, buildings' areas and a topographic map of the study areas. By coupling the models to the hourly weather conditions, the thermodynamic model of 3,630 buildings is simulated in EnergyPlus. Adapting the model to Beirut's occupancy and users' behaviors is crucial to enhance the reliability of BEEM. The availability of metered electricity data allows the model calibration, which is based on buildings' clustering and finding the clusters' coefficients representative of specific energy patterns. After the training phase, the model's accuracy in predicting electricity consumption is improved. Comparing the actual consumption and the calibrated results, the averaged absolute percentage error of the electricity consumption was reduced from 310% to 41% in district A and from 326% to 39% in district B. The calibrated model is combined with Geographic Information System (GIS) for a spatiotemporal distribution of energy demand patterns, which can help in assessing the most suitable intervention technologies.Pour réduire les émissions de gaz à effet de serre et la consommation d'énergie dans les zones urbaines, il est essentiel de comprendre les performances énergétiques et les modes de consommation des bâtiments pour pouvoir mettre en œuvre des stratégies efficaces de gestion de l'énergie et d'efficacité énergétique à l'échelle de la ville. La mise en œuvre à grande échelle de tels plans nécessite des informations sur la manière dont les demandes en énergie peuvent changer dans le cadre d'interventions spécifiques. Les modèles énergétiques de bâtiments à l'échelle urbaine (UBEM) sont des outils proposés pour estimer la demande énergétique actuelle et future des bâtiments. Ces modèles reposent sur une approche ascendante (bottom-up approach) combinant à la fois des techniques statistiques et des méthodes basées sur la physique thermodynamique. Cette étude vise à fournir une approche de modélisation améliorée simulant la demande énergétique des bâtiments à haute résolution spatiale et temporelle, ce qui peut aider à évaluer les stratégies de gestion de l'énergie et les politiques énergétiques décisionnelles. La méthodologie est appliquée pour la ville de Beyrouth, représentative de la région méditerranéenne, où la similarité des technologies de construction et des préoccupations climatiques de ses villes est prononcée. Les objectifs principaux de la thèse sont de développer, étudier et calibrer un outil de modélisation énergétique ascendante à l'échelle urbaine ; fournir des preuves de la pertinence de l'outil pour soutenir les directives pour les interventions futures ; et enfin, étudier l'impact de la compacité de la ville sur la disponibilité de la lumière du jour et donc sur le bien-être des citoyens. Dans cette étude de cas basée sur deux quartiers différents de la ville, un modèle énergétique de bâtiment à échelle urbaine approximativement, applé BEirut Energy Model BEEM, est généré pour estimer la consommation d'électricité du stock de bâtiment. Afin de réduire le temps de modélisation et de calcul, une classification archétypale des bâtiments basée sur leurs types et leurs périodes de construction est adoptée. Les informations supplémentaires requises pour générer le modle 3D des bâtiments sont le nombre d'étages, la superficie des bâtiments et une carte topographique des zones d'étude. En couplant les modèles aux conditions météorologiques horaires, le modèle thermodynamique de 3,630 bâtiments est simulé dans EnergyPlus. L'adaptation du modèle à l'occupation de Beyrouth et aux comportements des utilisateurs est cruciale pour renforcer la fiabilité de BEEM. La disponibilité des données d'électricité actuelles permet la calibration du modèle, qui repose sur le regroupement des bâtiments et la recherche des coefficients des regroupements représentatifs de modèles d'énergie spécifiques

Kinetic roughening of the urban skyline

We analyze the morphology of the modern urban skyline in terms of its roughness properties. This is facilitated by a database of 107 building heights in cities throughout the Netherlands which allows us to compute the asymptotic height difference correlation function in each city. We find that in cities for which the height correlations display power-law scaling as a function of distance between the buildings, the corresponding roughness exponents are commensurate to the Edwards-Wilkinson and Kardar-Parisi-Zhang equations for kinetic roughening. Based on analogy to discrete deposition models, we argue that these two limiting classes emerge because of possible height restriction rules for buildings in some cities.Peer reviewe

BEIRUT AS A SMART CITY: REDEFINING URBAN ENERGY

Global efforts are exerted to improve energy supply-demand balance in urban environments which are characterized byhigher population density and levels of energy consumption. Beirut, Lebanon’s capital, is no exception in facing suchurban challenges, which are compounded by the regular power outages. As such, developing an urban scale energymodel for energy management is essential to achieve this goal. This policy brief presents a model developed for theBachoura area to determine its buildings energy performance. The results are integrated to report the hourly energyuse profile spatially distributed over the city, which leads to identifying hotspots and peak hours of energy demands.The model can be used to estimate the potential savings from rooftop solar energy production and recommendtargeted energy-use policies to alleviate peaks and ensure an optimal and efficient distribution of resources

BEIRUT AS A SMART CITY: REDEFINING URBAN ENERGY

Global efforts are exerted to improve energy supply-demand balance in urban environments which are characterized byhigher population density and levels of energy consumption. Beirut, Lebanon’s capital, is no exception in facing suchurban challenges, which are compounded by the regular power outages. As such, developing an urban scale energymodel for energy management is essential to achieve this goal. This policy brief presents a model developed for theBachoura area to determine its buildings energy performance. The results are integrated to report the hourly energyuse profile spatially distributed over the city, which leads to identifying hotspots and peak hours of energy demands.The model can be used to estimate the potential savings from rooftop solar energy production and recommendtargeted energy-use policies to alleviate peaks and ensure an optimal and efficient distribution of resources

Urban energy modeling and calibration of a coastal Mediterranean city: The case of Beirut

International audienc