The Age and Structure of the Galactic Bulge from Mira Variables

We report periods and JHKL observations for 648 oxygen-rich Mira variables found in two outer bulge fields at b=-7 degrees and l=+/-8 degrees and combine these with data on 8057 inner bulge Miras from the OGLE, Macho and 2MASS surveys, which are concentrated closer to the Galactic centre. Distance moduli are estimated for all these stars. Evidence is given showing that the bulge structure is a function of age. The longer period Miras (log P > 2.6, age about 5 Gyr and younger) show clear evidence of a bar structure inclined to the line of sight in both the inner and outer regions. The distribution of the shorter period (metal-rich globular cluster age) Miras, appears spheroidal in the outer bulge. In the inner region these old stars are also distributed differently from the younger ones and possibly suggest a more complex structure. These data suggest a distance to the Galactic centre, R0, of 8.9 kpc with an estimated uncertainty of 0.4 kpc. The possible effect of helium enrichment on our conclusions is discussed.Comment: Accepted for MNRAS, 12 pages, 12 figure

Assessing the use of hospital staff influenza-like absence (ILA) for enhancing hospital preparedness and national surveillance

BACKGROUND: Early warning and robust estimation of influenza burden are critical to inform hospital preparedness and operational, treatment, and vaccination policies. Methods to enhance influenza-like illness (ILI) surveillance are regularly reviewed. We investigated the use of hospital staff ‘influenza-like absences’ (hospital staff-ILA), i.e. absence attributed to colds and influenza, to improve capture of influenza dynamics and provide resilience for hospitals. METHODS: Numbers and rates of hospital staff-ILA were compared to regional surveillance data on ILI primary-care presentations (15–64 years) and to counts of laboratory confirmed cases among hospitalised patients from April 2008 to April 2013 inclusive. Analyses were used to determine comparability of the ILI and hospital-ILA and how systems compared in early warning and estimating the burden of disease. RESULTS: Among 20,021 reported hospital-ILA and 4661 community ILI cases, correlations in counts were high and consistency in illness measurements was observed. In time series analyses, both hospital-ILA and ILI showed similar timing of the seasonal component. Hospital-ILA data often commenced and peaked earlier than ILI according to a Bayesian prospective alarm algorithm. Hospital-ILA rates were more comparable to model-based estimates of ‘true’ influenza burden than ILI. CONCLUSIONS: Hospital-ILA appears to have the potential to be a robust, yet simple syndromic surveillance method that could be used to enhance estimates of disease burden and early warning, and assist with local hospital preparedness. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12879-015-0789-z) contains supplementary material, which is available to authorized users

Drivers for emerging issues in animal and plant health.

The history of agriculture includes many animal and plant disease events that have had major consequences for the sector, as well as for humans. At the same time, human activities beyond agriculture have often driven the emergence of diseases. The more that humans expand the footprint of the global population, encroach into natural habitats, alter these habitats to extract resources and intensify food production, as well as move animals, people and commodities along with the pathogens they carry, the greater the potential for pathogens and pests to spread and for infection to emerge or re-emerge. While essential to human well-being, producing food also plays a major role in disease dynamics. The risk of emergence of pests and pathogens has increased as a consequence of global changes in the way food is produced, moved and consumed. Climate change is likely to increase pressure on the availability of food and provide newly suitable conditions for invasive pests and pathogens. Human population displacements due to economic, political and humanitarian crises represent another set of potential drivers for emerging issues. The overlapping drivers of plant, animal and human disease emergence and environmental changes point towards the concept of 'One Health'. This paradigm underlines the urgent need to understand the influence of human behaviour and incorporate this understanding into our approach to emerging risks. For this, we face two major challenges. One is cultural; the second is methodological. We have to look at systems not under the narrow view of specific hazards but with a wider approach to system dynamics, and consider a broad spectrum of potential outcomes in terms of risk. In addition, we have to make sense of the vast amounts of data that are available in the modern age. This paper aims to help in preparing for the cultural and methodological shifts needed in our approach to emerging risks

Syndromic surveillance: two decades experience of sustainable systems – its people not just data!

Syndromic surveillance is a form of surveillance that generates information for public health action by collecting, analysing and interpreting routine health-related data on symptoms and clinical signs reported by patients and clinicians rather than being based on microbiologically or clinically confirmed cases. In England, a suite of national real-time syndromic surveillance systems (SSS) have been developed over the last 20 years, utilising data from a variety of health care settings (a telehealth triage system, general practice and emergency departments). The real-time systems in England have been used for early detection (e.g. seasonal influenza), for situational awareness (e.g. describing the size and demographics of the impact of a heatwave) and for reassurance of lack of impact on population health of mass gatherings (e.g. the London 2012 Olympic and Paralympic Games).We highlight the lessons learnt from running SSS, for nearly two decades, and propose questions and issues still to be addressed. We feel that syndromic surveillance is an example of the use of ‘big data’, but contend that the focus for sustainable and useful systems should be on the added value of such systems and the importance of people working together to maximise the value for the public health of syndromic surveillance services

A genome-wide association study identifies novel candidate genes for susceptibility to diabetes mellitus in non-obese cats

Diabetes mellitus (DM) is a common feline endocrinopathy, which is similar to human type 2 diabetes (T2DM) in terms of its pathophysiology. T2DM occurs due to peripheral insulin resistance and/or β-cell dysfunction. Several studies have identified genetic and environmental factors that contribute to susceptibility to human T2DM. In cats, environmental factors such as obesity and physical inactivity have been linked with DM, although to date, the only genetic association that has been demonstrated is with a polymorphism in the feline MC4R gene. The aim of this study was to perform a genome-wide association study (GWAS) to identify polymorphisms associated with feline DM.Illumina Infinium 63k iSelect DNA arrays were used to analyse genomic DNA samples from 192 diabetic domestic shorthair cats and 389 non-diabetic control cats. Data was analysed using PLINK whole genome data analysis toolset. Significance was established at

Preventing the next 'SARS' - European healthcare workers' attitudes towards monitoring their health for the surveillance of newly emerging infections: qualitative study

<p>Abstract</p> <p>Background</p> <p>Hospitals are often the epicentres of newly circulating infections. Healthcare workers (HCWs) are at high risk of acquiring infectious diseases and may be among the first to contract emerging infections. This study aims to explore European HCWs' perceptions and attitudes towards monitoring their absence and symptom reports for surveillance of newly circulating infections.</p> <p>Methods</p> <p>A qualitative study with thematic analysis was conducted using focus group methodology. Forty-nine hospital-based HCWs from 12 hospitals were recruited to six focus groups; two each in England and Hungary and one each in Germany and Greece.</p> <p>Results</p> <p>HCWs perceived risk factors for occupationally acquired infectious diseases to be 1.) exposure to patients with undiagnosed infections 2.) break-down in infection control procedures 3.) immuno-naïvety and 4.) symptomatic colleagues. They were concerned that a lack of monitoring and guidelines for infectious HCWs posed a risk to staff and patients and felt employers failed to take a positive interest in their health. Staffing demands and loss of income were noted as pressures to attend work when unwell. In the UK, Hungary and Greece participants felt monitoring staff absence and the routine disclosure of symptoms could be appropriate provided the effectiveness and efficiency of such a system were demonstrable. In Germany, legislation, privacy and confidentiality were identified as barriers.</p> <p>All HCWs highlighted the need for knowledge and structural improvements for timelier recognition of emerging infections. These included increased suspicion and awareness among staff and standardised, homogenous absence reporting systems.</p> <p>Conclusions</p> <p>Monitoring absence and infectious disease symptom reports among HCWs may be a feasible means of surveillance for emerging infections in some settings. A pre-requisite will be tackling the drivers for symptomatic HCWs to attend work.</p

Identification of Genomic Regions Associated with Phenotypic Variation between Dog Breeds using Selection Mapping

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