Trees in the Andes:: Sustainable livelihood strategies for risk reduction

High mountain regions including the Andean region are very sensitive to climate change. Farmers in the central Andes of Peru are increasingly being exposed to the impacts of climate variability. This transdisciplinary research uses field laboratories, combining the farming system and the sustainable livelihood approaches, to carry out social, ecological, and financial assessments so as to identify sustainable and resilient livelihood strategies for small-scale Andean farmers. The first research step studies and characterizes farm household systems, influenced by their biophysical and socioeconomic contexts, for which two vulnerability indices were elaborated. Focused on the climate variability, the five livelihood assets and the three IPCC’s vulnerability components, these indices show the highly sensitive conditions of most communities with poor health conditions, access to infrastructure and public services. Farmers’ capacity of response is often limited by the low on-farm diversity and lack of organization. Thereafter, sustainable livelihood strategies were identified. These include on-farm intensification and non-farm labor intensification for lowland and better-access communities. In the middle-access and highland communities, where temporary migration is a common coping strategy, sustainable scenarios include an increment in diversification strategies through agrobiodiversity and a larger share of tree-based production systems. Furthermore, research step II explores local strategies to cope with agricultural droughts and evaluates, by means of natural resource assessment methods, agroforestry systems as an alternative to reduce their negative effects. Mainly affected by the increasing variation in precipitation events, farmers identify off-farm and on-farm diversification as adaptive strategies against agricultural droughts that reduce the weather dependence and covariance between livelihood activities. Among the introduction of more resistant crop and pasture varieties, the incorporation of trees in their system is desired because of their positive influence in soil moisture and crop yields. Soil moisture in agroforestry systems with eucalyptus trees is 10-20% higher than in agricultural systems during the beginning of the wet season. Differences in the soil moisture during the end of the dry season and in the potato yield are not evident between these systems, although an area without sowing reduced the agricultural output in 13-17% in agroforestry systems. Research step III seeks to maximize the efficiency of resource allocation in farm household systems by developing a linear programming optimization model. This financial assessment underpinned the need of additional off-farm activities for resource-scarcer farmers. In addition, under interest rates below 15% the model includes tree-based production systems as part of the optimal solution. However, with increasing interest rates, a higher share of land is used to cover household’s basic needs and fewer resources are available for capital accumulation activities such as forestry. Variations introduced in the model show that pasture systems are more sensitive to changes in the production outputs, whereas variation in farm worker wages and tree prices affected less the optimal solutions, making farming systems less sensitive to these market changes. Finally, the incorporation of tree-based systems have proved to be a sustainable and resilient livelihood strategy against climate variability available for particular farm household systems of the study area.:1 Introduction - 1 - 1.1 Introduction and justification - 1 - 1.2 Objectives and thesis statements - 2 - 1.3 Outline - 3 - 1.4 Definition of terms - 5 - 1.4.1 Vulnerability - 5 - 1.4.2 Resilience - 7 - 1.4.3 Agroforestry systems - 8 - 1.4.4 Farming system approach - 9 - 1.4.5 Farm household system - 10 - 1.4.6 Sustainable livelihood approach - 10 - 2 Framework and study site - 14 - 2.1 Theoretical framework - 14 - 2.2 Methodological framework - 18 - 2.2.1 Field laboratories - 18 - 2.2.2 Methods - 19 - 2.2.3 Methodology applied in research step I: Vulnerability in Achamayo - 21 - 2.2.4 Methodology applied in research step II: Agroforestry systems and agricultural droughts - 29 - 2.2.5 Methodology applied in research step III: Modeling small farm production systems - 33 - 2.2.6 Selection of case studies - 34 - 2.3 Study area - 35 - 2.3.1 Soils and topography - 35 - 2.3.2 Weather - 37 - 2.3.3 Agro-ecological zones and vegetation - 38 - 2.3.4 Climate change - 40 - 2.3.5 Socioeconomic characteristics - 42 - 2.3.6 Population - 43 - 2.3.7 External determinants - 71 - 2.4 Case studies - 47 - 2.4.1 Lowland communities (L) - 49 - 2.4.2 Middle access communities (M) - 50 - 2.4.3 Highland communities (H) - 51 - 3 Vulnerability in Achamayo - 53 - 3.1 Results - 53 - 3.1.1 Sustainable Livelihood Vulnerability Index (S-LVI) - 53 - 3.1.2 IPCC Livelihood Vulnerability Index (LVI-IPCC) - 68 - 3.2 Discussion - 71 - 3.2.1 Climate variability and extreme events - 71 - 3.2.2 Human capital - 71 - 3.2.3 Social capital - 71 - 3.2.4 Natural capital - 71 - 3.2.5 Physical capital - 71 - 3.2.6 Financial capital - 71 - 3.2.7 Livelihood strategies following the S-LVI and LVI-IPCC indices - 86 - 3.3 Conclusion - 92 - 4 Agroforestry systems and agricultural droughts - 95 - 4.1 Results - 96 - 4.1.1 Farmers’ experience and perception on climate variability and agricultural droughts - 96 - 4.1.2 Agricultural droughts in the farm household systems - 97 - 4.1.3 Farming forestry systems and land-use decision-making - 102 - 4.1.4 Influence of trees in the soil moisture and yield - 104 - 4.2 Discussion - 110 - 4.2.1 Climate change and agricultural droughts - 110 - 4.2.2 Farm forestry systems and land-use decision-making - 115 - 4.2.3 Influence of trees in the soil moisture and yield - 117 - 4.3 Conclusion - 121 - 5 Modeling small farm production systems: optimization of resource allocation - 123 - 5.1 Methodology - 124 - 5.1.1 Optimization Model - 126 - 5.1.2 Plan of optimization - 128 - 5.1.3 Production systems - 131 - 5.1.4 Constraints - 134 - 5.2 Results - 138 - 5.2.1 Model - 138 - 5.2.2 Interest rates - 142 - 5.2.3 Sensitivity analyses - 146 - 5.3 Discussion - 151 - 5.3.1 Cash flows - 151 - 5.3.2 Model outcomes - 152 - 5.3.3 Interest rates - 155 - 5.3.4 Sensitivity analyses - 159 - 5.4 Conclusion - 169 - 6 Synthesis - 171 - 6.1 Lessons learned - 171 - 6.1.1 Research step I - 172 - 6.1.2 Research step II - 175 - 6.1.3 Research step III - 176 - 6.2 Conclusions & outlook - 179 - 6.2.1 General conclusions - 179 - 6.2.2 Outlook - 181 - References - 185 - Appendix - 199 -Las zonas montañosas, incluyendo la región andina son muy sensibles al cambio climático. Los agricultores de los Andes centrales del Perú están cada vez más expuestos a los efectos de la variabilidad climática. Esta investigación transdisciplinaria utiliza laboratorios de campo (field laboratories), combinando los enfoques de sistemas agrícolas y de medios de vida sostenibles, para llevar a cabo evaluaciones sociales, ecológicas y financieras con el fin de identificar estrategias sostenibles y resilientes para los agricultores andinos de pequeña escala. La primera fase de la investigación caracteriza a los sistemas agrícolas familiares, influenciados por sus contextos biofísicos y socioeconómicos, para lo cual se elaboraron dos índices de vulnerabilidad centrados en la variabilidad del clima, los cinco activos de los medios de vida y los tres componentes de la vulnerabilidad del IPCC. Estos índices muestran las condiciones de alta sensibilidad de la mayoría de las comunidades, con malas condiciones de salud y poco acceso a la infraestructura y a los servicios públicos. La capacidad de respuesta de los agricultores es a menudo limitada por la baja diversidad en las actividades agrícolas y la falta de organización. Posteriormente se identificaron las estrategias de medios de vida sostenibles. Estas incluyen la intensificación en las actividades agrícolas y la intensificación del trabajo no agrícola en las comunidades de zonas bajas y con mejor acceso. En las comunidades con menor acceso y zonas altas la migración temporal es una estrategia de afrontamiento común. Los escenarios sostenibles en estas comunidades incluyen un incremento en las estrategias de diversificación p. ej. a través de un aumento de la biodiversidad agrícola y una mayor proporción de sistemas de producción asociados con árboles. Por otra parte, la segunda fase de la investigación explora las estrategias locales para hacer frente a las sequías agrícolas y evalúa, por medio de métodos de evaluación de recursos naturales, los sistemas agroforestales como alternativa para reducir sus efectos negativos. Afectados principalmente por el aumento en la variación de las precipitaciones, los pequeños agricultores identifican a la diversificación de actividades dentro y fuera de sus parcelas agrícolas como una estrategia de adaptación frente a las sequías agrícolas que reduce la dependencia climática y la covarianza entre las actividades de subsistencia. Dentro de la introducción de variedades de cultivos y pastos más resistentes, como parte de la solución, los agricultores desean la incorporación de árboles en su sistema debido a su influencia positiva en la humedad del suelo y en los rendimientos de los cultivos. La humedad del suelo en sistemas agroforestales con árboles de eucalipto es un 10-20% mayor que en los sistemas agrícolas durante el comienzo de la estación húmeda. Las diferencias en la humedad del suelo durante el final de la estación seca y en el rendimiento de los cultivos de papa no son evidentes entre estos dos sistemas. A pesar de esto, el espacio sin siembra dejado en los sistemas agroforestales redujo la producción agrícola en un 13-17%. La tercera fase de la investigación busca maximizar la eficiencia en la asignación de recursos en los sistemas agrícolas familiares mediante el desarrollo de un modelo de optimización de programación lineal. Esta evaluación financiera respalda la necesidad de actividades adicionales no-agrícolas para agricultores con recursos más escasos. Además, con tasas de interés por debajo del 15%, el modelo siempre incluye a los sistemas de producción forestales y/o agroforestales como parte de las soluciones óptimas. Sin embargo, con el aumento de las tasas de interés, una mayor proporción de tierra se utiliza para cubrir las necesidades básicas del hogar y menos recursos están disponibles para las actividades de acumulación de capital como la silvicultura. Las variaciones introducidas en el modelo muestran que los sistemas de pastoreo son más sensibles a los cambios en los condiciones de producción. Por otro lado, la variación en los salarios de los trabajadores agrícolas y en los precios de los árboles afectan en un menor grado las soluciones óptimas, proporcionando sistemas agrícolas menos sensibles a estos cambios en el mercado. Finalmente, la incorporación de árboles en los sistemas agrícolas ha demostrado ser una estrategia de vida sostenible y resiliente a la variabilidad climática disponible para determinados sistemas agrícolas familiares de la zona de estudio.:1 Introduction - 1 - 1.1 Introduction and justification - 1 - 1.2 Objectives and thesis statements - 2 - 1.3 Outline - 3 - 1.4 Definition of terms - 5 - 1.4.1 Vulnerability - 5 - 1.4.2 Resilience - 7 - 1.4.3 Agroforestry systems - 8 - 1.4.4 Farming system approach - 9 - 1.4.5 Farm household system - 10 - 1.4.6 Sustainable livelihood approach - 10 - 2 Framework and study site - 14 - 2.1 Theoretical framework - 14 - 2.2 Methodological framework - 18 - 2.2.1 Field laboratories - 18 - 2.2.2 Methods - 19 - 2.2.3 Methodology applied in research step I: Vulnerability in Achamayo - 21 - 2.2.4 Methodology applied in research step II: Agroforestry systems and agricultural droughts - 29 - 2.2.5 Methodology applied in research step III: Modeling small farm production systems - 33 - 2.2.6 Selection of case studies - 34 - 2.3 Study area - 35 - 2.3.1 Soils and topography - 35 - 2.3.2 Weather - 37 - 2.3.3 Agro-ecological zones and vegetation - 38 - 2.3.4 Climate change - 40 - 2.3.5 Socioeconomic characteristics - 42 - 2.3.6 Population - 43 - 2.3.7 External determinants - 71 - 2.4 Case studies - 47 - 2.4.1 Lowland communities (L) - 49 - 2.4.2 Middle access communities (M) - 50 - 2.4.3 Highland communities (H) - 51 - 3 Vulnerability in Achamayo - 53 - 3.1 Results - 53 - 3.1.1 Sustainable Livelihood Vulnerability Index (S-LVI) - 53 - 3.1.2 IPCC Livelihood Vulnerability Index (LVI-IPCC) - 68 - 3.2 Discussion - 71 - 3.2.1 Climate variability and extreme events - 71 - 3.2.2 Human capital - 71 - 3.2.3 Social capital - 71 - 3.2.4 Natural capital - 71 - 3.2.5 Physical capital - 71 - 3.2.6 Financial capital - 71 - 3.2.7 Livelihood strategies following the S-LVI and LVI-IPCC indices - 86 - 3.3 Conclusion - 92 - 4 Agroforestry systems and agricultural droughts - 95 - 4.1 Results - 96 - 4.1.1 Farmers’ experience and perception on climate variability and agricultural droughts - 96 - 4.1.2 Agricultural droughts in the farm household systems - 97 - 4.1.3 Farming forestry systems and land-use decision-making - 102 - 4.1.4 Influence of trees in the soil moisture and yield - 104 - 4.2 Discussion - 110 - 4.2.1 Climate change and agricultural droughts - 110 - 4.2.2 Farm forestry systems and land-use decision-making - 115 - 4.2.3 Influence of trees in the soil moisture and yield - 117 - 4.3 Conclusion - 121 - 5 Modeling small farm production systems: optimization of resource allocation - 123 - 5.1 Methodology - 124 - 5.1.1 Optimization Model - 126 - 5.1.2 Plan of optimization - 128 - 5.1.3 Production systems - 131 - 5.1.4 Constraints - 134 - 5.2 Results - 138 - 5.2.1 Model - 138 - 5.2.2 Interest rates - 142 - 5.2.3 Sensitivity analyses - 146 - 5.3 Discussion - 151 - 5.3.1 Cash flows - 151 - 5.3.2 Model outcomes - 152 - 5.3.3 Interest rates - 155 - 5.3.4 Sensitivity analyses - 159 - 5.4 Conclusion - 169 - 6 Synthesis - 171 - 6.1 Lessons learned - 171 - 6.1.1 Research step I - 172 - 6.1.2 Research step II - 175 - 6.1.3 Research step III - 176 - 6.2 Conclusions & outlook - 179 - 6.2.1 General conclusions - 179 - 6.2.2 Outlook - 181 - References - 185 - Appendix - 199 -Hochgebirgsregionen einschließlich der Andenregion sind gegenüber dem Klimawandel sehr empfindlich. Die in den zentralen Anden von Peru lebenden Bauern sind mehr und mehr den Auswirkungen durch Klimaschwankungen ausgesetzt. Diese transdisziplinäre Forschung nutzt Feldlabore, die das System der landwirtschaftlichen Bewirtschaftung und Ansätze zur nachhaltigen Lebensunterhaltssicherung kombinieren, um soziale, ökologische und ökonomische Erhebungen durchzuführen, so dass nachhaltige Livelihood-Strategien für die Kleinbauern in den Anden aufgezeigt werden können. Der erste Forschungsschritt untersucht und charakterisiert die bäuerlichen Haushaltssysteme, die durch ihre biophysikalischen und sozioökonomischen Kontexte beeinflusst sind. Hierfür wurden zwei Vulnerabilitätsindizes herausgearbeitet, die Klimavariabilität und die fünf Güter des Sustainable Livelihood-Konzepts im Fokus haben, sowie die drei Vulnerabilitätskomponenten des Intergovernmental Panel on Climate Change (IPCC). Diese Indizes decken die hochgradige Sensitivität für die meisten Gemeinden auf, aufgrund des schlechten Gesundheitszustandes sowie dem Mangel an Infrastruktur und öffentlichen Dienstleistungen. Die Fähigkeit der Bauern damit umzugehen, ist zumeist begrenzt durch eine geringe Diversität und fehlende Organisation auf den Farmen. Anschließend werden nachhaltige Livelihood-Strategien aufgezeigt. Diese umfassen die Intensivierung der Arbeit in der Landwirtschaft und der Arbeitskraft außerhalb der Landwirtschaft für Gemeinden im Flachland sowie besser erreichbare Gemeinden. In Hochlandgemeinden und Gemeinden die schwer zugänglich sind, ist temporäre Migration eine geläufige Bewältigungsstrategie. Nachhaltige Szenarien in diesen Gemeinden beinhalten eine höhere Anzahl an Diversifizierungsstrategien wie die Steigerung von Agro-Biodiversität und dem Anteil an baumbasierten Produktionssystemen. Forschungsschritt II untersucht lokale Strategien, um die landwirtschaftliche Dürre zu bewältigen und bewertet – mit Hilfe von Naturressourcenbewertungsverfahren – Agroforstsysteme als eine Alternative, um die negativen Auswirkungen der Trockenzeiten zu verringern. Beeinträchtigt durch zunehmende Niederschlagsschwankungen, identifizieren Bauern die Diversifizierung von landwirtschaftlichen und nicht-landwirtschaftlichen Aktivitäten als Anpassungsstrategie bei landwirtschaftliche Dürre, wodurch die Abhängigkeit vom Wetter und die Kovarianz zwischen den Aktivitäten für den Lebensunterhalt reduziert werden kann. Neben der Einführung resistenterer Kultur- und Weidepflanzen, ist die Einbeziehung von Bäumen in das System wünschenswert, aufgrund ihres positiven Einflusses auf die Bodenfeuchte und Erträge. Die Bodenfeuchte in agroforstwirtschaftlichen Systemen mit Eukalyptusbäumen ist während der beginnenden Feuchtperiode 20% höher als in landwirtschaftlichen Systemen. Die Unterschiede der Bodenfeuchte am Ende der Trockenzeit und bezüglich des Kartoffelertrags sind zwischen diesen Systemen nicht markant, obwohl eine Fläche, auf der keine Saat ausgebracht wurde, den landwirtschaftlichen Ertrag in Agroforstsystemen um 13 bis 17% mindert. Forschungsschritt III versucht die Effizienz der Ressourcenzuordnung in Farmhaushaltssystemen zu maximieren, indem ein Optimierungsmodell mit Hilfe der linearen Programmierung entwickelt wird. Diese ökonomische Erhebung unterstreicht die Notwendigkeit zusätzlicher nichtlandwirtschaftlicher Aktivitäten für ressourcenärmere Bauern. Bei Zinsraten unter 15% umfasst das Model baumbasierte Produktionssysteme als einen Teil der optimalen Lösung. Mit steigenden Zinsraten wird jedoch eine größere Bodenfläche dazu verwendet, um die Grundbedürfnisse der Haushalte zu decken und es stehen weniger Ressourcen für Aktivitäten zur Kapitalanhäufung wie Forstwirtschaft zur Verfügung. Die in das Modell involvierten Variationen zeigen, dass Weidesysteme sensibler auf Veränderungen des Produktionsausstoßes reagieren. Schwankungen bei den Löhnen der Farmer und Veränderungen der Baumpreise beeinträchtigen hingegen die optimalen Lösungen weniger. Dadurch sind die landwirtschaftlichen Systeme gegenüber Marktschwankungen weniger anfällig. Abschließend erweist sich, dass – für bestimmte Farmhaushaltssysteme im Untersuchungsgebiet – die Einbeziehung baumbasierter Systeme als nachhaltige und resiliente Livelihood-Strategie angesichts von Klimaschwankungen nützlich ist.:1 Introduction - 1 - 1.1 Introduction and justification - 1 - 1.2 Objectives and thesis statements - 2 - 1.3 Outline - 3 - 1.4 Definition of terms - 5 - 1.4.1 Vulnerability - 5 - 1.4.2 Resilience - 7 - 1.4.3 Agroforestry systems - 8 - 1.4.4 Farming system approach - 9 - 1.4.5 Farm household system - 10 - 1.4.6 Sustainable livelihood approach - 10 - 2 Framework and study site - 14 - 2.1 Theoretical framework - 14 - 2.2 Methodological framework - 18 - 2.2.1 Field laboratories - 18 - 2.2.2 Methods - 19 - 2.2.3 Methodology applied in research step I: Vulnerability in Achamayo - 21 - 2.2.4 Methodology applied in research step II: Agroforestry systems and agricultural droughts - 29 - 2.2.5 Methodology applied in research step III: Modeling small farm production systems - 33 - 2.2.6 Selection of case studies - 34 - 2.3 Study area - 35 - 2.3.1 Soils and topography - 35 - 2.3.2 Weather - 37 - 2.3.3 Agro-ecological zones and vegetation - 38 - 2.3.4 Climate change - 40 - 2.3.5 Socioeconomic characteristics - 42 - 2.3.6 Population - 43 - 2.3.7 External determinants - 71 - 2.4 Case studies - 47 - 2.4.1 Lowland communities (L) - 49 - 2.4.2 Middle access communities (M) - 50 - 2.4.3 Highland communities (H) - 51 - 3 Vulnerability in Achamayo - 53 - 3.1 Results - 53 - 3.1.1 Sustainable Livelihood Vulnerability Index (S-LVI) - 53 - 3.1.2 IPCC Livelihood Vulnerability Index (LVI-IPCC) - 68 - 3.2 Discussion - 71 - 3.2.1 Climate variability and extreme events - 71 - 3.2.2 Human capital - 71 - 3.2.3 Social capital - 71 - 3.2.4 Natural capital - 71 - 3.2.5 Physical capital - 71 - 3.2.6 Financial capital - 71 - 3.2.7 Livelihood strategies following the S-LVI and LVI-IPCC indices - 86 - 3.3 Conclusion - 92 - 4 Agroforestry systems and agricultural droughts - 95 - 4.1 Results - 96 - 4.1.1 Farmers’ experience and perception on climate variability and agricultural droughts - 96 - 4.1.2 Agricultural droughts in the farm household systems - 97 - 4.1.3 Farming forestry systems and land-use decision-making - 102 - 4.1.4 Influence of trees in the soil moisture and yield - 104 - 4.2 Discussion - 110 - 4.2.1 Climate change and agricultural droughts - 110 - 4.2.2 Farm forestry systems and land-use decision-making - 115 - 4.2.3 Influence of trees in the soil moisture and yield - 117 - 4.3 Conclusion - 121 - 5 Modeling small farm production systems: optimization of resource allocation - 123 - 5.1 Methodology - 124 - 5.1.1 Optimization Model - 126 - 5.1.2 Plan of optimization - 128 - 5.1.3 Production systems - 131 - 5.1.4 Constraints - 134 - 5.2 Results - 138 - 5.2.1 Model - 138 - 5.2.2 Interest rates - 142 - 5.2.3 Sensitivity analyses - 146 - 5.3 Discussion - 151 - 5.3.1 Cash flows - 151 - 5.3.2 Model outcomes - 152 - 5.3.3 Interest rates - 155 - 5.3.4 Sensitivity analyses - 159 - 5.4 Conclusion - 169 - 6 Synthesis - 171 - 6.1 Lessons learned - 171 - 6.1.1 Research step I - 172 - 6.1.2 Research step II - 175 - 6.1.3 Research step III - 176 - 6.2 Conclusions & outlook - 179 - 6.2.1 General conclusions - 179 - 6.2.2 Outlook - 181 - References - 18

Peri-operative red blood cell transfusion in neonates and infants: NEonate and Children audiT of Anaesthesia pRactice IN Europe: A prospective European multicentre observational study

BACKGROUND: Little is known about current clinical practice concerning peri-operative red blood cell transfusion in neonates and small infants. Guidelines suggest transfusions based on haemoglobin thresholds ranging from 8.5 to 12 g dl-1, distinguishing between children from birth to day 7 (week 1), from day 8 to day 14 (week 2) or from day 15 (≥week 3) onwards. OBJECTIVE: To observe peri-operative red blood cell transfusion practice according to guidelines in relation to patient outcome. DESIGN: A multicentre observational study. SETTING: The NEonate-Children sTudy of Anaesthesia pRactice IN Europe (NECTARINE) trial recruited patients up to 60 weeks' postmenstrual age undergoing anaesthesia for surgical or diagnostic procedures from 165 centres in 31 European countries between March 2016 and January 2017. PATIENTS: The data included 5609 patients undergoing 6542 procedures. Inclusion criteria was a peri-operative red blood cell transfusion. MAIN OUTCOME MEASURES: The primary endpoint was the haemoglobin level triggering a transfusion for neonates in week 1, week 2 and week 3. Secondary endpoints were transfusion volumes, 'delta haemoglobin' (preprocedure - transfusion-triggering) and 30-day and 90-day morbidity and mortality. RESULTS: Peri-operative red blood cell transfusions were recorded during 447 procedures (6.9%). The median haemoglobin levels triggering a transfusion were 9.6 [IQR 8.7 to 10.9] g dl-1 for neonates in week 1, 9.6 [7.7 to 10.4] g dl-1 in week 2 and 8.0 [7.3 to 9.0] g dl-1 in week 3. The median transfusion volume was 17.1 [11.1 to 26.4] ml kg-1 with a median delta haemoglobin of 1.8 [0.0 to 3.6] g dl-1. Thirty-day morbidity was 47.8% with an overall mortality of 11.3%. CONCLUSIONS: Results indicate lower transfusion-triggering haemoglobin thresholds in clinical practice than suggested by current guidelines. The high morbidity and mortality of this NECTARINE sub-cohort calls for investigative action and evidence-based guidelines addressing peri-operative red blood cell transfusions strategies. TRIAL REGISTRATION: ClinicalTrials.gov, identifier: NCT02350348

Les droits disciplinaires des fonctions publiques : « unification », « harmonisation » ou « distanciation ». A propos de la loi du 26 avril 2016 relative à la déontologie et aux droits et obligations des fonctionnaires

The production of tt‾ , W+bb‾ and W+cc‾ is studied in the forward region of proton–proton collisions collected at a centre-of-mass energy of 8 TeV by the LHCb experiment, corresponding to an integrated luminosity of 1.98±0.02 fb−1 . The W bosons are reconstructed in the decays W→ℓν , where ℓ denotes muon or electron, while the b and c quarks are reconstructed as jets. All measured cross-sections are in agreement with next-to-leading-order Standard Model predictions.The production of $t\overline{t}$, $W+b\overline{b}$ and $W+c\overline{c}$ is studied in the forward region of proton-proton collisions collected at a centre-of-mass energy of 8 TeV by the LHCb experiment, corresponding to an integrated luminosity of 1.98 $\pm$ 0.02 \mbox{fb}^{-1}. The $W$ bosons are reconstructed in the decays $W\rightarrow\ell\nu$, where $\ell$ denotes muon or electron, while the $b$ and $c$ quarks are reconstructed as jets. All measured cross-sections are in agreement with next-to-leading-order Standard Model predictions

Measuring progress and projecting attainment on the basis of past trends of the health-related Sustainable Development Goals in 188 countries: an analysis from the Global Burden of Disease Study 2016

The UN’s Sustainable Development Goals (SDGs) are grounded in the global ambition of “leaving no one behind”. Understanding today’s gains and gaps for the health-related SDGs is essential for decision makers as they aim to improve the health of populations. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016), we measured 37 of the 50 health-related SDG indicators over the period 1990–2016 for 188 countries, and then on the basis of these past trends, we projected indicators to 2030

Global, regional, and national under-5 mortality, adult mortality, age-specific mortality, and life expectancy, 1970–2016: a systematic analysis for the Global Burden of Disease Study 2016

BACKGROUND: Detailed assessments of mortality patterns, particularly age-specific mortality, represent a crucial input that enables health systems to target interventions to specific populations. Understanding how all-cause mortality has changed with respect to development status can identify exemplars for best practice. To accomplish this, the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) estimated age-specific and sex-specific all-cause mortality between 1970 and 2016 for 195 countries and territories and at the subnational level for the five countries with a population greater than 200 million in 2016. METHODS: We have evaluated how well civil registration systems captured deaths using a set of demographic methods called death distribution methods for adults and from consideration of survey and census data for children younger than 5 years. We generated an overall assessment of completeness of registration of deaths by dividing registered deaths in each location-year by our estimate of all-age deaths generated from our overall estimation process. For 163 locations, including subnational units in countries with a population greater than 200 million with complete vital registration (VR) systems, our estimates were largely driven by the observed data, with corrections for small fluctuations in numbers and estimation for recent years where there were lags in data reporting (lags were variable by location, generally between 1 year and 6 years). For other locations, we took advantage of different data sources available to measure under-5 mortality rates (U5MR) using complete birth histories, summary birth histories, and incomplete VR with adjustments; we measured adult mortality rate (the probability of death in individuals aged 15-60 years) using adjusted incomplete VR, sibling histories, and household death recall. We used the U5MR and adult mortality rate, together with crude death rate due to HIV in the GBD model life table system, to estimate age-specific and sex-specific death rates for each location-year. Using various international databases, we identified fatal discontinuities, which we defined as increases in the death rate of more than one death per million, resulting from conflict and terrorism, natural disasters, major transport or technological accidents, and a subset of epidemic infectious diseases; these were added to estimates in the relevant years. In 47 countries with an identified peak adult prevalence for HIV/AIDS of more than 0·5% and where VR systems were less than 65% complete, we informed our estimates of age-sex-specific mortality using the Estimation and Projection Package (EPP)-Spectrum model fitted to national HIV/AIDS prevalence surveys and antenatal clinic serosurveillance systems. We estimated stillbirths, early neonatal, late neonatal, and childhood mortality using both survey and VR data in spatiotemporal Gaussian process regression models. We estimated abridged life tables for all location-years using age-specific death rates. We grouped locations into development quintiles based on the Socio-demographic Index (SDI) and analysed mortality trends by quintile. Using spline regression, we estimated the expected mortality rate for each age-sex group as a function of SDI. We identified countries with higher life expectancy than expected by comparing observed life expectancy to anticipated life expectancy on the basis of development status alone. FINDINGS: Completeness in the registration of deaths increased from 28% in 1970 to a peak of 45% in 2013; completeness was lower after 2013 because of lags in reporting. Total deaths in children younger than 5 years decreased from 1970 to 2016, and slower decreases occurred at ages 5-24 years. By contrast, numbers of adult deaths increased in each 5-year age bracket above the age of 25 years. The distribution of annualised rates of change in age-specific mortality rate differed over the period 2000 to 2016 compared with earlier decades: increasing annualised rates of change were less frequent, although rising annualised rates of change still occurred in some locations, particularly for adolescent and younger adult age groups. Rates of stillbirths and under-5 mortality both decreased globally from 1970. Evidence for global convergence of death rates was mixed; although the absolute difference between age-standardised death rates narrowed between countries at the lowest and highest levels of SDI, the ratio of these death rates-a measure of relative inequality-increased slightly. There was a strong shift between 1970 and 2016 toward higher life expectancy, most noticeably at higher levels of SDI. Among countries with populations greater than 1 million in 2016, life expectancy at birth was highest for women in Japan, at 86·9 years (95% UI 86·7-87·2), and for men in Singapore, at 81·3 years (78·8-83·7) in 2016. Male life expectancy was generally lower than female life expectancy between 1970 and 2016, an

Population and fertility by age and sex for 195 countries and territories, 1950–2017: a systematic analysis for the Global Burden of Disease Study 2017

Background: Population estimates underpin demographic and epidemiological research and are used to track progress on numerous international indicators of health and development. To date, internationally available estimates of population and fertility, although useful, have not been produced with transparent and replicable methods and do not use standardised estimates of mortality. We present single-calendar year and single-year of age estimates of fertility and population by sex with standardised and replicable methods. Methods: We estimated population in 195 locations by single year of age and single calendar year from 1950 to 2017 with standardised and replicable methods. We based the estimates on the demographic balancing equation, with inputs of fertility, mortality, population, and migration data. Fertility data came from 7817 location-years of vital registration data, 429 surveys reporting complete birth histories, and 977 surveys and censuses reporting summary birth histories. We estimated age-specific fertility rates (ASFRs; the annual number of livebirths to women of a specified age group per 1000 women in that age group) by use of spatiotemporal Gaussian process regression and used the ASFRs to estimate total fertility rates (TFRs; the average number of children a woman would bear if she survived through the end of the reproductive age span [age 10–54 years] and experienced at each age a particular set of ASFRs observed in the year of interest). Because of sparse data, fertility at ages 10–14 years and 50–54 years was estimated from data on fertility in women aged 15–19 years and 45–49 years, through use of linear regression. Age-specific mortality data came from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 estimates. Data on population came from 1257 censuses and 761 population registry location-years and were adjusted for underenumeration and age misreporting with standard demographic methods. Migration was estimated with the GBD Bayesian demographic balancing model, after incorporating information about refugee migration into the model prior. Final population estimates used the cohort-component method of population projection, with inputs of fertility, mortality, and migration data. Population uncertainty was estimated by use of out-of-sample predictive validity testing. With these data, we estimated the trends in population by age and sex and in fertility by age between 1950 and 2017 in 195 countries and territories. Findings: From 1950 to 2017, TFRs decreased by 49·4% (95% uncertainty interval [UI] 46·4–52·0). The TFR decreased from 4·7 livebirths (4·5–4·9) to 2·4 livebirths (2·2–2·5), and the ASFR of mothers aged 10–19 years decreased from 37 livebirths (34–40) to 22 livebirths (19–24) per 1000 women. Despite reductions in the TFR, the global population has been increasing by an average of 83·8 million people per year since 1985. The global population increased by 197·2% (193·3–200·8) since 1950, from 2·6 billion (2·5–2·6) to 7·6 billion (7·4–7·9) people in 2017; much of this increase was in the proportion of the global population in south Asia and sub-Saharan Africa. The global annual rate of population growth increased between 1950 and 1964, when it peaked at 2·0%; this rate then remained nearly constant until 1970 and then decreased to 1·1% in 2017. Population growth rates in the southeast Asia, east Asia, and Oceania GBD super-region decreased from 2·5% in 1963 to 0·7% in 2017, whereas in sub-Saharan Africa, population growth rates were almost at the highest reported levels ever in 2017, when they were at 2·7%. The global average age increased from 26·6 years in 1950 to 32·1 years in 2017, and the proportion of the population that is of working age (age 15–64 years) increased from 59·9% to 65·3%. At the national level, the TFR decreased in all countries and territories between 1950 and 2017; in 2017, TFRs ranged from a low of 1·0 livebirths (95% UI 0·9–1·2) in Cyprus to a high of 7·1 livebirths (6·8–7·4) in Niger. The TFR under age 25 years (TFU25; number of livebirths expected by age 25 years for a hypothetical woman who survived the age group and was exposed to current ASFRs) in 2017 ranged from 0·08 livebirths (0·07–0·09) in South Korea to 2·4 livebirths (2·2–2·6) in Niger, and the TFR over age 30 years (TFO30; number of livebirths expected for a hypothetical woman ageing from 30 to 54 years who survived the age group and was exposed to current ASFRs) ranged from a low of 0·3 livebirths (0·3–0·4) in Puerto Rico to a high of 3·1 livebirths (3·0–3·2) in Niger. TFO30 was higher than TFU25 in 145 countries and territories in 2017. 33 countries had a negative population growth rate from 2010 to 2017, most of which were located in central, eastern, and western Europe, whereas population growth rates of more than 2·0% were seen in 33 of 46 countries in sub-Saharan Africa. In 2017, less than 65% of the national population was of working age in 12 of 34 high-income countries, and less than 50% of the national population was of working age in Mali, Chad, and Niger. Interpretation: Population trends create demographic dividends and headwinds (ie, economic benefits and detriments) that affect national economies and determine national planning needs. Although TFRs are decreasing, the global population continues to grow as mortality declines, with diverse patterns at the national level and across age groups. To our knowledge, this is the first study to provide transparent and replicable estimates of population and fertility, which can be used to inform decision making and to monitor progress

Measuring universal health coverage based on an index of effective coverage of health services in 204 countries and territories, 1990–2019 : A systematic analysis for the Global Burden of Disease Study 2019

Background Achieving universal health coverage (UHC) involves all people receiving the health services they need, of high quality, without experiencing financial hardship. Making progress towards UHC is a policy priority for both countries and global institutions, as highlighted by the agenda of the UN Sustainable Development Goals (SDGs) and WHO's Thirteenth General Programme of Work (GPW13). Measuring effective coverage at the health-system level is important for understanding whether health services are aligned with countries' health profiles and are of sufficient quality to produce health gains for populations of all ages. Methods Based on the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, we assessed UHC effective coverage for 204 countries and territories from 1990 to 2019. Drawing from a measurement framework developed through WHO's GPW13 consultation, we mapped 23 effective coverage indicators to a matrix representing health service types (eg, promotion, prevention, and treatment) and five population-age groups spanning from reproductive and newborn to older adults (≥65 years). Effective coverage indicators were based on intervention coverage or outcome-based measures such as mortality-to-incidence ratios to approximate access to quality care; outcome-based measures were transformed to values on a scale of 0–100 based on the 2·5th and 97·5th percentile of location-year values. We constructed the UHC effective coverage index by weighting each effective coverage indicator relative to its associated potential health gains, as measured by disability-adjusted life-years for each location-year and population-age group. For three tests of validity (content, known-groups, and convergent), UHC effective coverage index performance was generally better than that of other UHC service coverage indices from WHO (ie, the current metric for SDG indicator 3.8.1 on UHC service coverage), the World Bank, and GBD 2017. We quantified frontiers of UHC effective coverage performance on the basis of pooled health spending per capita, representing UHC effective coverage index levels achieved in 2019 relative to country-level government health spending, prepaid private expenditures, and development assistance for health. To assess current trajectories towards the GPW13 UHC billion target—1 billion more people benefiting from UHC by 2023—we estimated additional population equivalents with UHC effective coverage from 2018 to 2023. Findings Globally, performance on the UHC effective coverage index improved from 45·8 (95% uncertainty interval 44·2–47·5) in 1990 to 60·3 (58·7–61·9) in 2019, yet country-level UHC effective coverage in 2019 still spanned from 95 or higher in Japan and Iceland to lower than 25 in Somalia and the Central African Republic. Since 2010, sub-Saharan Africa showed accelerated gains on the UHC effective coverage index (at an average increase of 2·6% [1·9–3·3] per year up to 2019); by contrast, most other GBD super-regions had slowed rates of progress in 2010–2019 relative to 1990–2010. Many countries showed lagging performance on effective coverage indicators for non-communicable diseases relative to those for communicable diseases and maternal and child health, despite non-communicable diseases accounting for a greater proportion of potential health gains in 2019, suggesting that many health systems are not keeping pace with the rising non-communicable disease burden and associated population health needs. In 2019, the UHC effective coverage index was associated with pooled health spending per capita (r=0·79), although countries across the development spectrum had much lower UHC effective coverage than is potentially achievable relative to their health spending. Under maximum efficiency of translating health spending into UHC effective coverage performance, countries would need to reach $1398 pooled health spending per capita (US$ adjusted for purchasing power parity) in order to achieve 80 on the UHC effective coverage index. From 2018 to 2023, an estimated 388·9 million (358·6–421·3) more population equivalents would have UHC effective coverage, falling well short of the GPW13 target of 1 billion more people benefiting from UHC during this time. Current projections point to an estimated 3·1 billion (3·0–3·2) population equivalents still lacking UHC effective coverage in 2023, with nearly a third (968·1 million [903·5–1040·3]) residing in south Asia. Interpretation The present study demonstrates the utility of measuring effective coverage and its role in supporting improved health outcomes for all people—the ultimate goal of UHC and its achievement. Global ambitions to accelerate progress on UHC service coverage are increasingly unlikely unless concerted action on non-communicable diseases occurs and countries can better translate health spending into improved performance. Focusing on effective coverage and accounting for the world's evolving health needs lays the groundwork for better understanding how close—or how far—all populations are in benefiting from UHC

Global, regional, and national incidence, prevalence, and years lived with disability for 328 diseases and injuries for 195 countries, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016

As mortality rates decline, life expectancy increases, and populations age, non-fatal outcomes of diseases and injuries are becoming a larger component of the global burden of disease. The Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) provides a comprehensive assessment of prevalence, incidence, and years lived with disability (YLDs) for 328 causes in 195 countries and territories from 1990 to 2016

Global, regional, and national disability-adjusted life-years (DALYs) for 333 diseases and injuries and healthy life expectancy (HALE) for 195 countries and territories, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016

BACKGROUND: Measurement of changes in health across locations is useful to compare and contrast changing epidemiological patterns against health system performance and identify specific needs for resource allocation in research, policy development, and programme decision making. Using the Global Burden of Diseases, Injuries, and Risk Factors Study 2016, we drew from two widely used summary measures to monitor such changes in population health: disability-adjusted life-years (DALYs) and healthy life expectancy (HALE). We used these measures to track trends and benchmark progress compared with expected trends on the basis of the Socio-demographic Index (SDI). METHODS: We used results from the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 for all-cause mortality, cause-specific mortality, and non-fatal disease burden to derive HALE and DALYs by sex for 195 countries and territories from 1990 to 2016. We calculated DALYs by summing years of life lost and years of life lived with disability for each location, age group, sex, and year. We estimated HALE using age-specific death rates and years of life lived with disability per capita. We explored how DALYs and HALE differed from expected trends when compared with the SDI: the geometric mean of income per person, educational attainment in the population older than age 15 years, and total fertility rate. FINDINGS: The highest globally observed HALE at birth for both women and men was in Singapore, at 75·2 years (95% uncertainty interval 71·9-78·6) for females and 72·0 years (68·8-75·1) for males. The lowest for females was in the Central African Republic (45·6 years [42·0-49·5]) and for males was in Lesotho (41·5 years [39·0-44·0]). From 1990 to 2016, global HALE increased by an average of 6·24 years (5·97-6·48) for both sexes combined. Global HALE increased by 6·04 years (5·74-6·27) for males and 6·49 years (6·08-6·77) for females, whereas HALE at age 65 years increased by 1·78 years (1·61-1·93) for males and 1·96 years (1·69-2·13) for females. Total global DALYs remained largely unchanged from 1990 to 2016 (-2·3% [-5·9 to 0·9]), with decreases in communicable, maternal, neonatal, and nutritional (CMNN) disease DALYs offset by increased DALYs due to non-communicable diseases (NCDs). The exemplars, calculated as the five lowest ratios of observed to expected age-standardised DALY rates in 2016, were Nicaragua, Costa Rica, the Maldives, Peru, and Israel. The leading three causes of DALYs globally were ischaemic heart disease, cerebrovascular disease, and lower respiratory infections, comprising 16·1% of all DALYs. Total DALYs and age-standardised DALY rates due to most CMNN causes decreased from 1990 to 2016. Conversely, the total DALY burden rose for most NCDs; however, age-standardised DALY rates due to NCDs declined globally. INTERPRETATION: At a global level, DALYs and HALE continue to show improvements. At the same time, we observe that many populations are facing growing functional health loss. Rising SDI was associated with increases in cumulative years of life lived with disability and decreases in CMNN DALYs offset by increased NCD DALYs. Relative compression of morbidity highlights the importance of continued health interventions, which has changed in most locations in pace with the gross domestic product per person, education, and family planning. The analysis of DALYs and HALE and their relationship to SDI represents a robust framework with which to benchmark location-specific health performance. Country-specific drivers of disease burden, particularly for causes with higher-than-expected DALYs, should inform health policies, health system improvement initiatives, targeted prevention efforts, and development assistance for health, including financial and research investments for all countries, regardless of their level of sociodemographic development. The presence of countries that substantially outperform others suggests the need for increased scrutiny for proven examples of best practices, which can help to extend gains, whereas the presence of underperforming countries suggests the need for devotion of extra attention to health systems that need more robust support. FUNDING: Bill & Melinda Gates Foundation