Early Experiences in the Integration of Non-communicable Diseases into Emergency Primary Health Care, Beni Region, Democratic Republic of the Congo.

Background: Health services in humanitarian crises increasingly integrate the management of non-communicable diseases into primary care. As there is little description of such programs, this case study aims to describe the initial implementation of non-communicable disease management within emergency primary care in the conflict-affected Beni Region of Democratic Republic of the Congo (DRC). Objectives: We implemented and evaluated a primary care approach to hypertension and diabetes management to assess the feasibility of patient monitoring, early clinical and programmatic outcomes, and costs, after seven months of care. Methods: We designed clinical and programmatic modules for diabetes and hypertension management for clinical officers and the use of patient cards and community health workers to improve adherence. We used cohort analysis (April to October 2018), time-trend analysis, semi-structured interviews, and costing to evaluate the program. Findings: Increases in consultations for hypertension (incidence rate ratio [IRR] 13.5, 95% CI 5.8-31.5, p < 0.00) and diabetes (IRR 3.6, 95% CI 1-12.9, p < 0.05) were demonstrated up to the onset of violence and an Ebola epidemic in August 2018. Of 833 patients, 67% were women of median age 56. Nearly all were hypertensives (88.7%) and newly diagnosed (95.9%). Treatment adherence, defined as attending ≥2 visits in the seven month period, was demonstrated by 45.4% of hypertension patients. Community health workers had contact with 3.2-3.8 patients per month. Respondents stated that diabetes care remained fragmented with insulin and laboratory testing located outside of primary care. Program and management costs were 115 USD per person per treatment course. Conclusions: In an active conflict setting, we demonstrated that non-communicable disease care can be well-organized through clinical training and cohort analysis, and adherence can be addressed using patient-held cards and monitoring by community health workers. Nearly all diagnoses were new, emphasizing the need to establish self-management. Insecurity reduced access for patients but care continued for a subset of patients during the Ebola epidemic

DIAGNOSTIC ET PRESCRIPTION MEDICALE EN CAS DES FIEVRES INDIFERENCIEES DANS DES INSTITUTIONS SANITAIRES DE KINSHASA AVEC EMPHASE SUR LE VIRUS DE LA DENGUE

Lorsque les patients se présentent à la clinique pour le cas des fièvres, les cliniciens ont tendances à demandés un lot des examens para cliniques dont certains ne servent pas et font des prescriptions médicales hors les lignes budgétaires du patient et les normes de l’économie de la santé qui exigent  de l’efficience, l’efficacité et l’économie dans les prescriptions qui se résument par l’attention accordée au patient. Avec la réduction de la charge du paludisme parmi les causes de la fièvre, il est indispensable d'identifier les autres étiologies afin d'améliorer la prise en charge des patients. Pour ce diagnostic, il faut des outils simples utilisables dans les milieux endémiques surtout pour les pays en développement. Parmi les causes des fièvres d'origine indéterminées figurent les causes virales notamment la dengue. Au total 600 patients ont été inclus. Les résultats de notre recherche témoignent que la  prévalence de la dengue a été estimée à 6.1% en considérant les résultats de la PCR. La sensibilité et la spécificité de NS1 ont été estimées respectivement à 90.0% et à 100.0% en considérant la PCR comme le Gold standard. La Valeur Prédictive Positive et la Valeur Prédictive Négative ont été estimées respectivement à 100.0% et 99.4%. Le virus de la dengue est en circulation à Kinshasa en RDC. Le test de diagnostic rapide NS1 devra être introduit dans les structures sanitaires de la RDC afin d'accroître le plateau technique pour élucider les causes de fièvre et mettre le clinicien en confiance. Cette confiance permettra d'éviter une prescription inutile des antipaludiques et des antibiotiques.Lorsque les patients se présentent à la clinique pour le cas des fièvres, les cliniciens ont tendances à demandés un lot des examens para cliniques dont certains ne servent pas et font des prescriptions médicales hors les lignes budgétaires du patient et les normes de l’économie de la santé qui exigent &nbsp;de l’efficience, l’efficacité et l’économie dans les prescriptions qui se résument par l’attention accordée au patient. Avec la réduction de la charge du paludisme parmi les causes de la fièvre, il est indispensable d'identifier les autres étiologies afin d'améliorer la prise en charge des patients. Pour ce diagnostic, il faut des outils simples utilisables dans les milieux endémiques surtout pour les pays en développement. Parmi les causes des fièvres d'origine indéterminées figurent les causes virales notamment la dengue. Au total 600 patients ont été inclus. Les résultats de notre recherche témoignent que la &nbsp;prévalence de la dengue a été estimée à 6.1% en considérant les résultats de la PCR. La sensibilité et la spécificité de NS1 ont été estimées respectivement à 90.0% et à 100.0% en considérant la PCR comme le Gold standard. La Valeur Prédictive Positive et la Valeur Prédictive Négative ont été estimées respectivement à 100.0% et 99.4%. Le virus de la dengue est en circulation à Kinshasa en RDC. Le test de diagnostic rapide NS1 devra être introduit dans les structures sanitaires de la RDC afin d'accroître le plateau technique pour élucider les causes de fièvre et mettre le clinicien en confiance. Cette confiance permettra d'éviter une prescription inutile des antipaludiques et des antibiotiques

Closing a gap in tropical forest biomass estimation: taking crown mass variation into account in pantropical allometries

Accurately monitoring tropical forest carbon stocks is a challenge that remains outstanding. Allometric models that consider tree diameter, height and wood density as predictors are currently used in most tropical forest carbon studies. In particular, a pantropical biomass model has been widely used for approximately a decade, and its most recent version will certainly constitute a reference model in the coming years. However, this reference model shows a systematic bias towards the largest trees. Because large trees are key drivers of forest carbon stocks and dynamics, understanding the origin and the consequences of this bias is of utmost concern. In this study, we compiled a unique tree mass data set of 673 trees destructively sampled in five tropical countries (101 trees > 100 cm in diameter) and an original data set of 130 forest plots (1 ha) from central Africa to quantify the prediction error of biomass allometric models at the individual and plot levels when explicitly taking crown mass variations into account or not doing so. We first showed that the proportion of crown to total tree aboveground biomass is highly variable among trees, ranging from 3 to 88 %. This proportion was constant on average for trees  1 Mg) and reduced the range of plot-level error (in %) from [−23; 16] to [0; 10]. The disproportionally higher allocation of large trees to crown mass may thus explain the bias observed recently in the reference pantropical model. This bias leads to far-from-negligible, but often overlooked, systematic errors at the plot level and may be easily corrected by taking a crown mass proxy for the largest trees in a stand into account, thus suggesting that the accuracy of forest carbon estimates can be significantly improved at a minimal cost.This is the publisher’s final pdf. The published article is copyrighted by the author(s) and published by Copernicus Publications on behalf of the European Geosciences Union. The published article can be found at: http://www.biogeosciences.net

Consistent patterns of common species across tropical tree communities

Trees structure the Earth’s most biodiverse ecosystem, tropical forests. The vast number of tree species presents a formidable challenge to understanding these forests, including their response to environmental change, as very little is known about most tropical tree species. A focus on the common species may circumvent this challenge. Here we investigate abundance patterns of common tree species using inventory data on 1,003,805 trees with trunk diameters of at least 10 cm across 1,568 locations1,2,3,4,5,6 in closed-canopy, structurally intact old-growth tropical forests in Africa, Amazonia and Southeast Asia. We estimate that 2.2%, 2.2% and 2.3% of species comprise 50% of the tropical trees in these regions, respectively. Extrapolating across all closed-canopy tropical forests, we estimate that just 1,053 species comprise half of Earth’s 800 billion tropical trees with trunk diameters of at least 10 cm. Despite differing biogeographic, climatic and anthropogenic histories7, we find notably consistent patterns of common species and species abundance distributions across the continents. This suggests that fundamental mechanisms of tree community assembly may apply to all tropical forests. Resampling analyses show that the most common species are likely to belong to a manageable list of known species, enabling targeted efforts to understand their ecology. Although they do not detract from the importance of rare species, our results open new opportunities to understand the world’s most diverse forests, including modelling their response to environmental change, by focusing on the common species that constitute the majority of their trees.Publisher PDFPeer reviewe

Co-limitation towards lower latitudes shapes global forest diversity gradients

The latitudinal diversity gradient (LDG) is one of the most recognized global patterns of species richness exhibited across a wide range of taxa. Numerous hypotheses have been proposed in the past two centuries to explain LDG, but rigorous tests of the drivers of LDGs have been limited by a lack of high-quality global species richness data. Here we produce a high-resolution (0.025° × 0.025°) map of local tree species richness using a global forest inventory database with individual tree information and local biophysical characteristics from ~1.3 million sample plots. We then quantify drivers of local tree species richness patterns across latitudes. Generally, annual mean temperature was a dominant predictor of tree species richness, which is most consistent with the metabolic theory of biodiversity (MTB). However, MTB underestimated LDG in the tropics, where high species richness was also moderated by topographic, soil and anthropogenic factors operating at local scales. Given that local landscape variables operate synergistically with bioclimatic factors in shaping the global LDG pattern, we suggest that MTB be extended to account for co-limitation by subordinate drivers

Déterminants de la composition floristique et estimations des stocks de carbone des peuplements forestiers matures de Uma (Tshopo, RDC)

The study of tree assemblages in tropical forests is gaining new impetus with the need to assess carbon emissions at high precision and resolution, while limiting the erosion of diversity and promoting sustainable forest management. The objective of this study was to (i) investigate the respective roles of topographic / soil gradients and endogenous dynamics in shaping local variations in dominance; (ii) demonstrate the feasibility of studying canopy texture by harmonizing Fourier-based Textural Ordination (FOTO) indices of two GeoEye - 50 cm images, acquired from different phenologic seasons, to calibrate AGB inversion model using inventory plots. The study was conducted in Uma forest, East of Kisangani, Democratic Republic of Congo. Dataset of 30 1-ha plots, in which all trees above 10 cm diameter at 1.30 m height (DBH) were measured and identified. Standard physical and chemical properties of soil samples were determined (macro-nutrients, textural classes and pH) and a digital elevation model (SRTM 30 m) was used to infer relevant topographical features (altitude and hydromorphy). The forest in the study area is characterized by variations in the abundance of three dominant species: Petersianthus macrocarpus (P. BEAUV.) LIBEN, Gilbertiodendron dewevrei (De Wild.) J. Léonard and Julbernardia seretii (DE WILD.) TROUPIN, one non-pioneer, light demanding species and two late successional, shade tolerant species respectively. These variations occur nearly independently of variations in the substratum or topography, despite important gradients of the range of considered variables. Analyzing differential relative abundance of the three dominant species in the lower strata and in the canopy, did not provide evidence of shifts in dominance, in which a species would obviously tend to replace another through time in any of the three floristic groups. This suggests that in this study area the states of dominance in the vegetation are stable across generations, that successional dynamics are very slow or that they are localized to peculiar locations. Using FOTO method, this study documents a strong relation between observed and predicted AGBs, without cross validation (R² of the linear regression reached 0.82 (mean square error = 27.24 T/ha). This correlation was still present, although weaker, with cross validation (R² of the linear regression between observed and predicted AGBs = 0.64). The mean square error increases to 46.68 T/ha after cross validation for a mean of 450 T/ha. This result confirms the potential of FOTO indices of optical very high resolution satellite images to quantify aboveground biomass without no signal saturation in high AGB tropical forests.Les études des déterminants des groupements végétaux ont pris un nouvel élan avec la nécessité de quantifier avec précision les stocks de carbone à partir des données satellitaires de résolution métrique, tout en limitant l'érosion de la biodiversité et en promouvant une gestion durable des forêts. La présente étude se déroule dans la forêt de Uma, située à l’Est de Kisangani, en République Démocratique du Congo, entre les points kilométriques 65 et 90 sur la route nationale numéro 4. L’objectif de cette étude était (i) d’identifier les déterminants (sol, topographie, structure et / ou succession) des groupements végétaux qui dominent dans la forêt de Uma et (ii) estimer leurs stocks de carbone. Les données étaient collectées dans 30 parcelles de 1 ha chacune, dans lesquelles tous les arbres ≥ 10 cm de diamètre ont été mesurés et identifiés. Les échantillons de sol ont été analysés pour les variables pédologiques standard (macronutriments, classes de texture, pH) et un modèle numérique de terrain a été utilisé pour déduire les caractéristiques topographiques (altitude et hydromorphie). Deux images GeoEye – 50 cm aux géométries d’acquisition (angles soleil-capteur) très semblables, ont servi dans un modèle d’estimation de la biomasse des arbres sur 260 km² de superficie sur base de 30 parcelles de 1 ha chacune. Les résultats obtenus indiquent que, trois groupements végétaux dominent dans la forêt de Uma. Les espèces dominantes de chacun de ces groupements sont : Petersianthus macrocarpus (P. BEAUV.) LIBEN, Gilbertiodendron dewevrei (De Wild.) J. Léonard et Julbernardia seretii (DE WILD.) TROUPIN, respectivement une espèce non pionnière, exigeante en lumière et deux espèces tardives dans la succession forestière, tolérantes à l'ombrage. Ces groupements végétaux ne sont liés à aucune variable de l’environnement. La succession des espèces dominantes est au point mort. Ce résultat est évocateur soit, d'un modèle émergent, soit de multiples états stables induits par des rétroactions biologiques. La bonne relation entre la biomasse des parcelles et celle prédite sur les images de texture, a permis de produire la carte de biomasse de la forêt de Uma. A l’échelle de la parcelle, l’erreur quadratique moyenne est de 27,24 T/ha hors validation croisée (R²=0,82) et remonte à 46,68 T/ha (R²=0,61), après validation croisée pour une moyenne de 450 T/ha. Ce résultat démontre le potentiel des estimateurs de texture des images métriques dans la généralisation des biomasses de forêt sur les espaces non couverts par les données de terrain dans les forêts denses où la plupart des autres signaux de télédection saturen

Multiple Stable Dominance States in the Congo Basin Forests

Understanding the dynamics of dominant tree species in tropical forests is important both for biodiversity and carbon-related issues. We focus on the Congo Basin (East of Kisangani) to investigate the respective roles of topographic/soil gradients and endogenous dynamics in shaping local variations in dominance. We used a dataset of 30 1-ha plots, in which all trees above 10 cm diameter at breast height (DBH) were censused. Soil samples were analyzed for standard pedologic variables and a digital elevation model permitted to infer topography and hydromorphy. We found that this forest is characterized by variations in the abundance of three dominant species: Petersianthus macrocarpus (P.Beauv.) Liben (PM), Gilbertiodendron dewevrei (De Wild.) J.Leonard (GD) and Julbernardia seretii (De Wild.) Troupin (JS). These variations occur independently of substratum or topography variations. At plot level, the local relative abundance never reached 50%, the threshold for monodominance proposed in the literature, but rather progressively increased to reach higher values for canopy trees (&gt;60 cm DBH), where this threshold could be exceeded. We found no sign of shifting compositional dynamics, whereby the dominant species would switch between the canopy and the undergrowth. Our results, therefore, support the possibility of the existence of stable dominance states, induced by endogenous processes, such as biological positive feedbacks fostering monodominance. We also document a strong relation between monodominance level and alpha diversity, when giving more weight to abundant species which is expected (R&sup2; = 0.79) but also when giving more weight to rare species (R&sup2; = 0.37), showing that monodominance influences tree species richness patterns. Structural differences existed between groups, with the PM group having more (and on average smaller) stems and lighter wood on average, but paradoxically also higher biomass and basal area

Multiple Stable Dominance States in the Congo Basin Forests

International audienceUnderstanding the dynamics of dominant tree species in tropical forests is important both for biodiversity and carbon-related issues. We focus on the Congo Basin (East of Kisangani) to investigate the respective roles of topographic/soil gradients and endogenous dynamics in shaping local variations in dominance. We used a dataset of 30 1-ha plots, in which all trees above 10 cm diameter at breast height (DBH) were censused. Soil samples were analyzed for standard pedologic variables and a digital elevation model permitted to infer topography and hydromorphy. We found that this forest is characterized by variations in the abundance of three dominant species: Petersianthus macrocarpus (P.Beauv.) Liben (PM), Gilbertiodendron dewevrei (De Wild.) J.Leonard (GD) and Julbernardia seretii (De Wild.) Troupin (JS). These variations occur independently of substratum or topography variations. At plot level, the local relative abundance never reached 50%, the threshold for monodominance proposed in the literature, but rather progressively increased to reach higher values for canopy trees (>60 cm DBH), where this threshold could be exceeded. We found no sign of shifting compositional dynamics, whereby the dominant species would switch between the canopy and the undergrowth. Our results, therefore, support the possibility of the existence of stable dominance states, induced by endogenous processes, such as biological positive feedbacks fostering monodominance. We also document a strong relation between monodominance level and alpha diversity, when giving more weight to abundant species which is expected (R 2 = 0.79) but also when giving more weight to rare species (R 2 = 0.37), showing that monodominance influences tree species richness patterns. Structural differences existed between groups, with the PM group having more (and on average smaller) stems and lighter wood on average, but paradoxically also higher biomass and basal area

Pistes pour l'étude de la distribution des peuplements de Gilbertiodedron dewevrei comme signature des impacts climatiques ou anthropiques anciens

International audienc

Allometric options for predicting tropical tree height and crown area from stem diameter

publié sur la plateforme de prerpints : Research SquareTree height and crown area are important predictors of aboveground biomass but difficult to measure on the ground. Numerous allometric models have been established to predict tree height from diameter (H–D) and crown area from diameter (CA–D). A major challenge is to select the most precise and accurate allometric model among existing ones, depending on the species composition and forest type where the model is to be applied. To propose a principle to select tree H–D and tree CA–D allometric models, we build a method based on k -fold cross-validation using a large dataset spanning six forest types from central Africa. We then compared the errors and biases using 22 previously established H–D and CA–D allometric model forms via three inter-comparable scenarios: locally derived for the forest type vs. regional vs. pantropical; regional (encompassing the forest type) vs . pantropical; regional (not encompassing the forest type) vs. pantropical model. H–D allometries were more variable across forest types in central Africa than CA–D allometries: (i) forest type explained 6% of the variance in H–D allometry and 2% of the variance in CA–D allometry, while species explained 9% and 2% of the variance in H–D allometry and CA–D allometry, respectively; (ii) for H–D allometry, the six forest types resulted in five best-fit models whereas, for CA–D allometry, four models provided the best fit for the six forest types. We recommend using allometric models specific to the forest type, preferentially to regional ones. Regional models should in turn be preferred to pantropical allometric models