Dual-frequency GPS survey for validation of a regional DTM and for the generation of local DTM data for sea-level rise modelling in an estuarine salt marsh

Global average temperatures have risen by an average of 0.07°C per decade over the last 100 years, with a warming trend of 0.13°C per decade over the last 50 years. Temperatures are predicted to rise by 2°C - 4.4°C by 2100 leading to global average sealevel rise (SLR) of 2 – 6mm per year (20 – 60cms in total) up to 2100 (IPCC 2007) with impacts for protected coastal habitats in Ireland. Estuaries are predominantly sedimentary environments, and are characterised by shallow coastal slope gradients, making them sensitive to even modest changes in sea-level. The Shannon estuary is the largest river estuary in Ireland and is designated as a Special Area of Conservation (SAC) under the EU Habitats Directive (EU 1992) providing protection for listed habitats within it, including estuarine salt marsh. Trends in Shannon estuary tidal data from 1877 – 2004 suggest an average upward SLR trend of 4 - 5mm/yr over this period. A simple linear extension of this historical trend would imply that local SLR will be in the region of 40 - 45cm by 2100. However, this may underestimate actual SLR for the estuary by 2100, since it takes no account of predicted climate-driven global SLR acceleration (IPCC 2007) up to 2100

Cleostratus

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Predicting hospital costs for patients receiving renal replacement therapy to inform an economic evaluation.

OBJECTIVE: To develop a model to predict annual hospital costs for patients with established renal failure, taking into account the effect of patient and treatment characteristics of potential relevance for conducting an economic evaluation, such as age, comorbidities and time on treatment. The analysis focuses on factors leading to variations in inpatient and outpatient costs and excludes fixed costs associated with dialysis, transplant surgery and high cost drugs. METHODS: Annual costs of inpatient and outpatient hospital episodes for patients starting renal replacement therapy in England were obtained from a large retrospective dataset. Multiple imputation was performed to estimate missing costs due to administrative censoring. Two-part models were developed using logistic regression to first predict the probability of incurring any hospital costs before fitting generalised linear models to estimate the level of cost in patients with positive costs. Separate models were developed to predict inpatient and outpatient costs for each treatment modality. RESULTS: Data on hospital costs were available for 15,869 incident dialysis patients and 4511 incident transplant patients. The two-part models showed a decreasing trend in costs with increasing number of years on treatment, with the exception of dialysis outpatient costs. Age did not have a consistent effect on hospital costs; however, comorbidities such as diabetes and peripheral vascular disease were strong predictors of higher hospital costs in all four models. CONCLUSION: Analysis of patient-level data can result in a deeper understanding of factors associated with variations in hospital costs and can improve the accuracy with which costs are estimated in the context of economic evaluations.<br/

Differential risk of ST-Segment Elevation Myocardial Infarction in male and female smokers

Background Smoking is a well-documented risk for acute ST-segment elevation myocardial infarction (STEMI). The differential effect between sexes has yet to be quantified. Objectives The purpose of this study was to differentiate the effect of smoking on increased risk of STEMI between sexes. Methods For this retrospective ecological cohort study, all patients at a U.K. tertiary cardiothoracic center who presented between 2009 and 2014 with acute STEMI were combined with population data to generate incidence rates of STEMI. Age-standardized incidence rate ratios (IRRs) using the Poisson distribution were calculated comparing STEMI rates between smokers and nonsmokers stratified by sex and 3 age groups (18 to 49, 50 to 64, and >65 years). Results A total of 3,343 patients presented over 5,639,328 person-years. Peak STEMI rate for current smokers was in the 70 to 79 years age range for women (235 per 100,000 patient-years) and 50 to 59 years (425 per 100,000 patient-years) in men. Smoking was associated with a significantly greater increase in STEMI rate for women than men (IRR: 6.62; 95% confidence interval [CI]: 5.98 to 7.31, vs. 4.40; 95% CI: 4.15 to 4.67). The greatest increased risk was in women age 18 to 49 (IRR: 13.22; 95% CI: 10.33 to 16.66, vs. 8.60; 95% CI: 7.70 to 9.59 in men). The greatest risk difference was in the age 50 to 64 years group, with IRR of 9.66 (95% CI: 8.30 to 11.18) in women and 4.47 (95% CI: 4.10 to 4.86) in men. Conclusions This study quantifies the differential effect of smoking between sexes, with women having a significantly increased risk of STEMI than men. This information encourages continued efforts to prevent smoking uptake and promote cessation

Prévention des risques et lutte contre les incendies dans un paysage fortement marqué par la présence humaine : l'histoire des incendies de chaparral californien.

Les incendies de grande ampleur sont le produit inévitable du paysage et du climat californiens. Historiquement, les interventions contre les incendies n'ont jamais pu éliminer les feux des maquis en zone littorale, ce qui a pourtant été possible dans de nombreuses forêts de conifères de l'Ouest. Par le passé, les techniques de lutte contre les incendies ont été trop influencées par l'idée qu'elles pouvaient prévenir ou arrêter les feux dévastateurs. Cet objectif est impossible à atteindre à cause des conditions météorologiques sévères de cette région, d'où la nécessité de concentrer les efforts sur la création d'espaces défendables aux interfaces entre les zones urbaines et les espaces naturels. Grâce aux zones tampon et à une collaboration plus étroite entre les responsables de la lutte contre les incendies et les aménageurs, il sera peut-être possible de construire un environnement apte à minimiser les impacts des incendies

Estimation and inference in spatially varying coefficient models

Spatially varying coefficient models are a classical tool to explore the spatial nonstationarity of a regression relationship for spatial data. In this paper, we study the estimation and inference in spatially varying coefficient models for data distributed over complex domains. We use bivariate splines over triangulations to represent the coefficient functions. The estimators of the coefficient functions are consistent, and rates of convergence of the proposed estimators are established. A penalized bivariate spline estimation method is also introduced, in which a roughness penalty is incorporated to balance the goodness of fit and smoothness. In addition, we propose hypothesis tests to examine if the coefficient function is really varying over space or admits a certain parametric form. The proposed method is much more computationally efficient than the well-known geographically weighted regression technique and thus usable for analyzing massive data sets. The performances of the estimators and the proposed tests are evaluated by simulation experiments. An environmental data example is used to illustrate the application of the proposed method