Preliminary estimates and forecasts of the population prevalence of self reported of hypertension, of ischaemic heart disease and stroke in the Republic of Ireland from 2005 - 2015

Ireland and Northern Ireland’s Population Health Observatory (INIsPHO) recently published estimates of the population prevalence of diabetes in 2005 and forecasts to 2010 and 2015 for the island of Ireland, at the national and sub-national levels. These estimates are based the PBS Model developed by York and Humber Public Health Observatory (YHPHO), Brent NHS Trust and the School of Health and Related Research (ScHARR).The Department of Health and Children (DoHC) has requested additional estimates and forecasts for hypertension.This paper outlines the results from preliminary work from the initial steps towards a more systematic approach to monitoring the prevalence of other chronic diseases on the island.

The London Health Commission prospectus 2006-2008: Partnership for health: challenges for action

The London Health Commission programme of work to 2008 has identified four Health Challenges to stimulate action on its top priorities durng the next three years. It is urging organisations to join in action to increase the number of disabled people in employment; introduce smoke-free workplace policies; improve access to effective language support services for their users; help improve the emotional health and well being of young Londoners.

Combining multivariate density forecasts using predictive criteria

This paper combines multivariate density forecasts of output growth, inflationand interest rates from a suite of models. An out-of-sample weighting scheme based onthe predictive likelihood as proposed by Eklund and Karlsson (2005) and Andersson andKarlsson (2007) is used to combine the models. Three classes of models are considered: aBayesian vector autoregression (BVAR), a factor-augmented vector autoregression (FAVAR)and a medium-scale dynamic stochastic general equilibrium (DSGE) model. Using Australiandata, we find that, at short forecast horizons, the Bayesian VAR model is assignedthe most weight, while at intermediate and longer horizons the factor model is preferred.The DSGE model is assigned little weight at all horizons, a result that can be attributedto the DSGE model producing density forecasts that are very wide when compared withthe actual distribution of observations. While a density forecast evaluation exercise revealslittle formal evidence that the optimally combined densities are superior to those from thebest-performing individual model, or a simple equal-weighting scheme, this may be a resultof the short sample available.

Prospectus dictionarii quinque linguarum, armenicae scilicet litteralis, armenicae vulgaris, latinae, italicae nec non gallicae. [Obsignatus nomine Fr. P. Gabrielis Villa-For-Alexandrini, missionarii cappucini.]

[Prospectus. Livres]

CJJP Forecasts Increase in Special Sentence Sex Offenders Caseloads, Data Download, Iowa Department of Corrections, December 2011

The Iowa Sex Offender Research Council recently released a report to the Iowa General Assembly focusing on sex offender registration and the special sentence for sex offenders. Regarding the latter, the Council (staffed by the state’s Division of Criminal & Juvenile Justice Planning) projected a steady increase in community-based corrections’ special sentence caseloads from 619 offenders in 2011 to 2,651 offenders in 2021:

A probabilistic approach to niche-based community models for spatial forecasts of assemblage properties and their uncertainties

Aim Conservation strategies are in need of predictions that capture spatial community composition and structure. Currently, the methods used to generate these predictions generally focus on deterministic processes and omit important stochastic processes and other unexplained variation in model outputs. Here we test a novel approach of community models that accounts for this variation and determine how well it reproduces observed properties of alpine butterfly communities. Location The western Swiss Alps. Methods We propose a new approach to process probabilistic predictions derived from stacked species distribution models (S-SDMs) in order to predict and assess the uncertainty in the predictions of community properties. We test the utility of our novel approach against a traditional threshold-based approach. We used mountain butterfly communities spanning a large elevation gradient as a case study and evaluated the ability of our approach to model species richness and phylogenetic diversity of communities. Results S-SDMs reproduced the observed decrease in phylogenetic diversity and species richness with elevation, syndromes of environmental filtering. The prediction accuracy of community properties vary along environmental gradient: variability in predictions of species richness was higher at low elevation, while it was lower for phylogenetic diversity. Our approach allowed mapping the variability in species richness and phylogenetic diversity projections. Main conclusion Using our probabilistic approach to process species distribution models outputs to reconstruct communities furnishes an improved picture of the range of possible assemblage realisations under similar environmental conditions given stochastic processes and help inform manager of the uncertainty in the modelling results