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Respiratory disorders are responsible for considerable morbidity, health care utilisation, societal costs and approximately one in five deaths worldwide [1-4]. Yet, despite this substantial health and societal burden – which particularly affects the world’s poorest populations and as such is a major contributor to global health inequalities – respiratory disorders have historically not received the\ud policy priority they warrant. For example, despite causing an estimated 1000 deaths per day, less than half of the world’s countries collect data on asthma prevalence (http://www.globalasthmareport.org/). This\ud is true for both communicable and non-communicable respiratory disorders, many of which are either amenable to treatment or preventable.

In the last two decades the use of species distribution modeling (SDM) for the study and management of marine species has increased dramatically. The availability of predictor variables on a global scale and the ease of use of SDM techniques have resulted in a proliferation of research on the topic of species distribution in the deep sea. Translation of research projects into management tools that can be used to make decisions in the face of changing climate and increasing exploitation of deep-sea resources has been less rapid but necessary. The goal of this workshop was to discuss methods and variables for modeling species distributions in deep-sea habitats and produce standards that can be used to judge SDMs that may be useful to meet management and conservation goals. During the workshop, approaches to modeling and environmental data were discussed and guidelines developed including the desire that 1) environmental variables should be chosen for ecological significance a priori; 2) the scale and accuracy of environmental data should be considered in choosing a modeling method; 3) when possible proxy variables such as depth should be avoided if causal variables are available; 4) models with statistically robust and rigorous outputs are preferred, but not always possible; and 5) model validation is important. Although general guidelines for SDMs were developed, in most cases management issues and objectives should be considered when designing a modeling project. In particular, the trade-off between model complexity and researcher’s ability to communicate input data, modeling method, results and uncertainty is an important consideration for the target audience. RÉSUMÉ. Au cours des deux dernières décennies, le recours à la modélisation de la répartition des espèces pour étudier et gérer les espèces marines a considérablement augmenté. La disponibilité des variables prédictives à l’échelle mondiale et la convivialité de ces techniques de modélisation ont entraîné la multiplication des recherches sur la répartition des espèces en haute mer. La traduction des projets de recherche en outils de gestion pouvant servir à prendre des décisions dans le contexte des changements climatiques et de l’exploitation accrue des ressources en haute mer est moins rapide, quoique nécessaire. Cet atelier visait à discuter des méthodes et variables pour la modélisation de la répartition des espèces dans les habitats en haute mer, et à établir des normes pour évaluer les méthodes de modélisation pouvant aider à atteindre les objectifs en matière de gestion et de conservation. Pendant l’atelier, les approches envers la modélisation et les données environnementales ont fait l’objet de discussions, et des lignes directrices ont été élaborées. Celles-ci comprenaient les caractéristiques souhaitées qui suivent: 1) les variables environnementales devraient être choisies selon leur importance écologique a priori; 2) l’ampleur et l’exactitude des données environnementales devraient être prises en compte durant la sélection d’une méthode de modélisation; 3) dans la mesure du possible, les variables substitutives, comme la profondeur, doivent être évitées si des variables causales sont disponibles; 4) les modèles dont les résultats sont statistiquement solides et rigoureux sont privilégiés, mais leur utilisation n’est pas toujours possible; 5) la validation du modèle est importante. Même si des lignes générales sur la modélisation de la répartition des espèces ont été mises au point, les objectifs et enjeux de gestion devraient généralement être pris en compte pendant la conception d’un projet de modélisation. En particulier, le compromis entre la complexité du modèle et la capacité du chercheur à communiquer les données d’entrée, la méthode de modélisation, les résultats et les incertitudes sont des facteurs importants pour le public cible.

Background: Catheter-associated urinary tract infections (CAUTIs) are among the most common hospital-acquired infections, leading to increased morbidity and mortality. A major reason for this is that urinary catheters are not yet capable of preventing CAUTIs. Aim: To develop an anti-infective urinary catheter. Methods: An efficient silver-polytetrafluoroethylene (Ag-PTFE) nanocomposite coating was deposited on whole silicone catheters, and two in-vitro bladder models were designed to test antibacterial (against Escherichia coli) and anti-encrustation (against Proteusmirabilis) performances. Each model was challenged with two different concentrations of bacterial suspension. Findings: Compared with uncoated catheters, coated catheters significantly inhibited bacterial migration and biofilm formation on the external catheter surfaces. The time to develop bacteriuria was an average of 1.8 days vs 4 days and 6 days vs 41 days when the urethral meatus was infected with 106 and 102 cells/mL, respectively. For anti encrustation tests, the coated catheter significantly resisted encrustation, although it did not strongly inhibit the increases in bacterial density and urinary pH. The time to blockage, which was found to be independent of the initial bacterial concentration in the bladder, was extended from 36.21.1 h (uncoated) to 89.53.54 h (coated) following bacterial contamination with 103 cells/mL in the bladder. Moreover, the coated catheter exhibited excellent biocompatibility with L929 fibroblast cells. Conclusion: Ag-PTFE coated Foley catheters should undergo further clinical trials to determine their ability to prevent CAUTIs during catheterization.

Use of Species Distribution Modeling in the Deep Sea. Published in the Canadian Technical Report of Fisheries and Aquatic Sciences 3296 (2019) In the last two decades the use of species distribution modeling (SDM) for the study and management of marine species has increased dramatically. The availability of predictor variables on a global scale and the ease of use of SDM techniques have resulted in a proliferation of research on the topic of species distribution in the deep sea. Translation of research projects into management tools that can be used to make decisions in the face of changing climate and increasing exploitation of deep-sea resources has been less rapid but necessary. The goal of this workshop was to discuss methods and variables for modeling species distributions in deep-sea habitats and produce standards that can be used to judge SDMs that may be useful to meet management and conservation goals. During the workshop, approaches to modeling and environmental data were discussed and guidelines developed including the desire that 1) environmental variables should be chosen for ecological significance a priori; 2) the scale and accuracy of environmental data should be considered in choosing a modeling method; 3) when possible proxy variables such as depth should be avoided if causal variables are available; 4) models with statistically robust and rigorous outputs are preferred, but not always possible; and 5) model validation is important. Although general guidelines for SDMs were developed, in most cases management issues and objectives should be considered when designing a modeling project. In particular, the trade-off between model complexity and researcher’s ability to communicate input data, modeling method, results and uncertainty is an important consideration for the target audience.

Recent increases in marine traffic in the Arctic have amplified the demand for reliable ice and marine environmental predictions. This article presents the verification of ice forecast skill from a new system implemented recently at the Canadian Meteorological Centre called the Global Ice Ocean Prediction System (GIOPS). GIOPS provides daily global ice and ocean analyses and 10-day forecasts on a 1/4°-resolution grid. GIOPS includes a multivariate ocean data assimilation system that combines satellite observations of sea-level anomaly and sea-surface temperature (SST) together with in situ observations of temperature and salinity. Ice analyses are produced using a 3D-Var method that assimilates satellite observations from SSM/I and SSMIS together with manual analyses from the Canadian Ice Service. Analyses of total ice concentration are projected onto the thickness categories used in the ice model using spatially and temporally varying weighting functions derived from ice model tendencies. This method may reduce deleterious impacts on the ice thickness distribution when assimilating ice concentration, as it can directly modulate (and reverse) nonlinear processes such as ice deformation. An objective verification of sea ice forecasts is made using two methods: analysis-based error assessment focusing on the marginal ice zone, and a contingency table approach to evaluate ice extent as compared to an independent analysis. Together the methods demonstrate a consistent picture of skilful medium-range forecasts in both the Northern and Southern Hemispheres as compared to persistence. Using the contingency table approach, GIOPS forecasts show a significant open-water bias during spring and summer. However, this bias depends on the choice of threshold used. Ice forecast skill is found to be highly sensitive to the assimilation of SST near the ice edge. Improved observational coverage in these areas (including salinity) would be extremely valuable for further improvement in ice forecast skill.

Operational ocean forecast systems provide routine marine products to an ever-widening community of users and stakeholders. The majority of users need information about the quality and reliability of the products to exploit them fully. Hence, forecast centres have been developing improved methods for evaluating and communicating the quality of their products. Global Ocean Data Assimilation Experiment (GODAE) OceanView, along with the Copernicus European Marine Core Service and other national and international programmes, has facilitated the development of coordinated validation activities among these centres. New metrics, assessing a wider range of ocean parameters, have been defined and implemented in real-time. An overview of recent progress and emerging international standards is presented here. © 2015 Institut de Recherche pour le Développement (IRD).