Spatial smoothing in Bayesian models: a comparison of weights matrix specifications and their impact on inference.

Background: When analysing spatial data, it is important to account for spatial autocorrelation. In Bayesian statistics, spatial autocorrelation is commonly modelled by the intrinsic conditional autoregressive prior distribution. At the heart of this model is a spatial weights matrix which controls the behaviour and degree of spatial smoothing.

Improved Diagnosis and Care for Rare Diseases through Implementation of Precision Public Health Framework.

Public health relies on technologies to produce and analyse data, as well as effectively develop and implement policies and practices. An example is the public health practice of epidemiology, which relies on computational technology to monitor the health status of populations, identify disadvantaged or at risk population groups and thereby inform health policy and priority setting. Critical to achieving health improvements for the underserved population of people living with rare diseases is early diagnosis and best care.

Initiating an undiagnosed diseases program in the Western Australian public health system.

Background: New approaches are required to address the needs of complex undiagnosed diseases patients. These approaches include clinical genomic diagnostic pipelines, utilizing intra- and multi-disciplinary platforms, as well as specialty-specific genomic clinics. Both are advancing diagnostic rates.

3-Dimensional Facial Analysis-Facing Precision Public Health.

Precision public health is a new field driven by technological advances that enable more precise descriptions and analyses of individuals and population groups, with a view to improving the overall health of populations. This promises to lead to more precise clinical and public health practices, across the continuum of prevention, screening, diagnosis, and treatment. A phenotype is the set of observable characteristics of an individual resulting from the interaction of a genotype with the environment.

Terrestrial Water Storage in African Hydrological Regimes Derived from GRACE Mission Data: Intercomparison of Spherical Harmonics, Mass Concentration, and Scalar Slepian Methods.

Spherical harmonics (SH) and mascon solutions are the two most common types of solutions for Gravity Recovery and Climate Experiment (GRACE) mass flux observations. However, SH signals are degraded by measurement and leakage errors. Mascon solutions (the Jet Propulsion Laboratory (JPL) release, herein) exhibit weakened signals at submascon resolutions.

Spatially Enabling the Health Sector.

Spatial information describes the physical location of either people or objects, and the measured relationships between them. In this article, we offer the view that greater utilization of spatial information and its related technology, as part of a broader redesign of the architecture of health information at local and national levels, could assist and speed up the process of health reform, which is taking place across the globe in richer and poorer countries alike. In making this point, we describe the impetus for health sector reform, recent developments in spatial information and analytics, and current Australasian spatial health research.

Spatio-temporal variation of mood and anxiety symptom treatments in Christchurch in the context of the 2010/11 Canterbury earthquake sequence.

This article explores the spatio-temporal variation of mood and anxiety treatments in the context of a severe earthquake sequence. The aim was to examine a possible earthquake exposure effect, identify populations at risk and areas with particularly large mood and anxiety treatment rate increases or decreases in the affected Christchurch urban area. A significantly stronger increase of mood and anxiety treatments among residents in Christchurch compared to others in New Zealand have been found, as well as children and elderly identified as especially vulnerable.

Spatio-temporal relative survival of breast and colorectal cancer in Queensland, Australia 2001-2011.

Despite improvements in cancer survival across many developed countries, it is unclear how survival is changing over time in small areas. This study investigated changes in breast and colorectal cancer survival across 478 areas over 11 years (2001-2011), and the influence of early diagnosis on changes. Queensland Cancer Registry data were analysed using an introduced Bayesian spatio-temporal flexible parametric relative survival model.

Ultrahigh Dimensional Variable Selection for Interpolation of Point Referenced Spatial Data: A Digital Soil Mapping Case Study.

Modern soil mapping is characterised by the need to interpolate point referenced (geostatistical) observations and the availability of large numbers of environmental characteristics for consideration as covariates to aid this interpolation. Modelling tasks of this nature also occur in other fields such as biogeography and environmental science. This analysis employs the Least Angle Regression (LAR) algorithm for fitting Least Absolute Shrinkage and Selection Operator (LASSO) penalized Multiple Linear Regressions models.

The effects of spatially varying earthquake impacts on mood and anxiety symptom treatments among long-term Christchurch residents following the 2010/11 Canterbury earthquakes, New Zealand.

This study investigates the effects of disruptions to different community environments, community resilience and cumulated felt earthquake intensities on yearly mood and anxiety symptom treatments from the New Zealand Ministry of Health's administrative databases between September 2009 and August 2012. The sample includes 172,284 long-term residents from different Christchurch communities. Living in a better physical environment was associated with lower mood and anxiety treatment rates after the beginning of the Canterbury earthquake sequence whereas an inverse effect could be found for social community environment and community resilience.

A flexible parametric approach to examining spatial variation in relative survival.

Most of the few published models used to obtain small-area estimates of relative survival are based on a generalized linear model with piecewise constant hazards under a Bayesian formulation. Limitations of these models include the need to artificially split the time scale, restricted ability to include continuous covariates, and limited predictive capacity. Here, an alternative Bayesian approach is proposed: a spatial flexible parametric relative survival model.

The rare and undiagnosed diseases diagnostic service - application of massively parallel sequencing in a state-wide clinical service.

Background: The Rare and Undiagnosed Diseases Diagnostic Service (RUDDS) refers to a genomic diagnostic platform operating within the Western Australian Government clinical services delivered through Genetic Services of Western Australia (GSWA). GSWA has provided a state-wide service for clinical genetic care for 28 years and it serves a population of 2.5 million people across a geographical area of 2.

Bayesian spatiotemporal modelling for identifying unusual and unstable trends in mammography utilisation.

Objectives: To compare two Bayesian models capable of identifying unusual and unstable temporal patterns in spatiotemporal data.

Setting: Annual counts of mammography screening users from each statistical local area (SLA) in Brisbane, Australia, recorded between 1997 and 2008 inclusive.

Primary Outcome Measures: Mammography screening counts.

The effects of relocation and level of affectedness on mood and anxiety symptom treatments after the 2011 Christchurch earthquake.

In this longitudinal study, we compare the effects of different types of relocation and level of affectedness on the incidence and relapse of mood and anxiety symptom treatments identified by publicly funded care or treatment one year before and one and two years after the '2011 Christchurch earthquake' in New Zealand. Based on a subset of Christchurch residents from differently affected areas of the city identified by area-wide geotechnical land assessments (no to severe land damage) 'stayers', 'within-city movers', 'out-of-city movers' and 'returners' were identified to assess the interaction effect of different levels of affectedness and relocation on the incidence and relapse of mood and anxiety symptom treatments over time. Health and sample information were drawn from the New Zealand Ministry of Health's administrative databases allowing us to do a comparison of the pre-/post-disaster treatment status and follow-up on a large study sample.

Impact of geography on the control of type 2 diabetes mellitus: a review of geocoded clinical data from general practice.

Objective: To review the clinical data for people with diabetes mellitus with reference to their location and clinical care in a general practice in Australia.

Materials And Methods: Patient data were extracted from a general practice in Western Australia. Iterative data-cleansing steps were taken.

Detecting and Quantifying Forest Change: The Potential of Existing C- and X-Band Radar Datasets.

This paper evaluates the opportunity provided by global interferometric radar datasets for monitoring deforestation, degradation and forest regrowth in tropical and semi-arid environments. The paper describes an easy to implement method for detecting forest spatial changes and estimating their magnitude. The datasets were acquired within space-borne high spatial resolutions radar missions at near-global scales thus being significant for monitoring systems developed under the United Framework Convention on Climate Change (UNFCCC).

Inferring lung cancer risk factor patterns through joint Bayesian spatio-temporal analysis.

Background: Preventing risk factor exposure is vital to reduce the high burden from lung cancer. The leading risk factor for developing lung cancer is tobacco smoking. In Australia, despite apparent success in reducing smoking prevalence, there is limited information on small area patterns and small area temporal trends.

The impact of spatial scales and spatial smoothing on the outcome of bayesian spatial model.

Discretization of a geographical region is quite common in spatial analysis. There have been few studies into the impact of different geographical scales on the outcome of spatial models for different spatial patterns. This study aims to investigate the impact of spatial scales and spatial smoothing on the outcomes of modelling spatial point-based data.

Performance comparisons of contour-based corner detectors.

Corner detectors have many applications in computer vision and image identification and retrieval. Contour-based corner detectors directly or indirectly estimate a significance measure (e.g.