HIV and STI surveillance in Northern Ireland 2010: An analysis of data for the calendar year 2009

This annual analysis of data provides an overview of HIV and STI epidemiology in Northern Ireland for the calendar year 2009. Information from a variety of sources is collated and analysed in detail, while any evident trends over time are highlightedwithgraphs and tables. As well as a general summary of STI diagnoses and a number of overall conclusions, the report looks specifically at each of the following STIs: chlamydia, gonorrhoea, genital herpes, genital warts, syphilis, lymphogranuloma venereum (LGV) and HIV.

Alcohol-related and hepatocellular cancer deaths by country of birth in England and Wales: analysis of mortality and census data.

BACKGROUND: The incidence of and mortality from alcohol-related conditions, liver disease and hepatocellular cancer (HCC) are increasing in the UK. We compared mortality rates by country of birth to explore potential inequalities and inform clinical and preventive care. DESIGN: Analysis of mortality for people aged 20 years and over using the 2001 Census data and death data from 1999 and 2001-2003. SETTING: England and Wales. MAIN OUTCOME MEASURES: Standardized mortality ratios (SMRs) for alcohol-related deaths and HCC. RESULTS: Mortality from alcohol-related deaths (23 502 deaths) was particularly high for people born in Ireland (SMR for men [M]: 236, 95% confidence interval [CI]: 219-254; SMR for women [F]: 212, 95% CI: 191-235) and Scotland (SMR-M: 187, CI: 173-213; SMR-F 182, CI: 163-205) and men born in India (SMR-M: 161, CI: 144-181). Low alcohol-related mortality was found in women born in other countries and men born in Bangladesh, Middle East, West Africa, Pakistan, China and Hong Kong, and the West Indies. Similar mortality patterns were observed by country of birth for alcoholic liver disease and other liver diseases. Mortality from HCC (8266 deaths) was particularly high for people born in Bangladesh (SMR-M: 523, CI: 380-701; SMR-F: 319, CI: 146-605), China and Hong Kong (SMR-M: 492, CI: 168-667; SMR-F: 323, CI: 184-524), West Africa (SMR-M: 440, CI, 308-609; SMR-F: 319, CI: 165-557) and Pakistan (SMR-M: 216, CI: 113-287; SMR-F: 215, CI: 133-319). CONCLUSIONS: These findings show persistent differences in mortality by country of birth for both alcohol-related and HCC deaths and have important clinical and public health implications. New policy, research and practical action are required to address these differences.This resource was contributed by The National Documentation Centre on Drug Use.

Diabetes in the United Kingdom: Analysis of QRESEARCH Data

Report describing 10 year trends in incidence, prevalence and mortality of diabetes and obesity by age, sex, deprivation and ethnicity from this Primary Care database.

The effect of patient, provider and financing regulations on the intensity of ambulatory physical therapy episodes : a multilevel analysis based on routinely available data

Background: Many studies have found considerable variations in the resource intensity of physical therapy episodes. Although they have identified several patient-and provider-related factors, few studies have examined their relative explanatory power. We sought to quantify the contribution of patients and providers to these differences and examine how effective Swiss regulations are (nine-session ceiling per prescription and bonus for first treatments). Methods: Our sample consisted of 87,866 first physical therapy episodes performed by 3,365 physiotherapists based on referrals by 6,131 physicians. We modeled the number of visits per episode using a multilevel log linear regression with crossed random effects for physiotherapists and physicians and with fixed effects for cantons. The three-level explanatory variables were patient, physiotherapist and physician characteristics. Results: The median number of sessions was nine (interquartile range 6-13). Physical therapy use increased with age, women, higher health care costs, lower deductibles, surgery and specific conditions. Use rose with the share of nine-session episodes among physiotherapists or physicians, but fell with the share of new treatments. Geographical area had no influence. Most of the variance was explained at the patient level, but the available factors explained only 4% thereof. Physiotherapists and physicians explained only 6% and 5% respectively of the variance, although the available factors explained most of this variance. Regulations were the most powerful factors. Conclusion: Against the backdrop of abundant physical therapy supply, Swiss financial regulations did not restrict utilization. Given that patient-related factors explained most of the variance, this group should be subject to closer scrutiny. Moreover, further research is needed on the determinants of patient demand.

HIV and STI surveillance in Northern Ireland 2011: An analysis of data for the calendar year 2010

This annual analysis of data provides an overview of HIV and STI epidemiology in Northern Ireland for the calendar year 2010. Information from a variety of sources is collated and analysed in detail, while any evident trends over time are highlighted�with�graphs and tables. As well as a general summary of STI diagnoses and a number of overall conclusions, the report looks specifically at each of the following STIs: chlamydia, gonorrhoea, genital herpes, genital warts, syphilis, lymphogranuloma venereum (LGV) and HIV.

HIV surveillance in Northern Ireland 2013 : An analysis of data for the calendar year 2012.

This report aims to provide an overview of HIV epidemiology in Northern Ireland by collating and analysing information from a number of sources. Although it reflects epidemiological trends over time, its main focus will be on data collected in 2012.

HIV and STI surveillance in Northern Ireland 2010: An analysis of data for the calendar year 2009

This annual analysis of data provides an overview of HIV and STI epidemiology in Northern Ireland for the calendar year 2009. Information from a variety of sources is collated and analysed in detail, while any evident trends over time are highlighted�with�graphs and tables. As well as a general summary of STI diagnoses and a number of overall conclusions, the report looks specifically at each of the following STIs: chlamydia, gonorrhoea, genital herpes, genital warts, syphilis, lymphogranuloma venereum (LGV) and HIV.

Analysis and estimative of schistosomiasis prevalence for the state of Minas Gerais, Brazil, using multiple regression with social and environmental spatial data

The aim of this work is to establish a relationship between schistosomiasis prevalence and social-environmental variables, in the state of Minas Gerais, Brazil, through multiple linear regression. The final regression model was established, after a variables selection phase, with a set of spatial variables which contains the summer minimum temperature, human development index, and vegetation type variables. Based on this model, a schistosomiasis risk map was built for Minas Gerais.

Capillaria spp. eggs in Patagonian archaeological sites: statistical analysis of morphometric data

Discriminant analysis was used to identify eggs of Capillaria spp. at specific level found in organic remains from an archaeological site in Patagonia, Argentina, dated of 6,540 ± 110 years before present. In order to distinguish eggshell morphology 149 eggs were measured and grouped into four arbitrary subsets. The analysis used on egg width and length discriminated them into different morphotypes (Wilks' lambda = 0.381, p < 0.05). The correlation analysis suggests that width was the most important variable to discriminate among the Capillaria spp. egg morphotypes (Pearson coefficient = 0.950, p < 0.05). The study of eggshell patterns, the relative frequency in the sample, and the morphometric data allowed us to correlate the four morphotypes with Capillaria species.

Application of compositional data analysis to geochemical data of marine sediments

In an earlier investigation (Burger et al., 2000) five sediment cores near the RodriguesTriple Junction in the Indian Ocean were studied applying classical statistical methods(fuzzy c-means clustering, linear mixing model, principal component analysis) for theextraction of endmembers and evaluating the spatial and temporal variation ofgeochemical signals. Three main factors of sedimentation were expected by the marinegeologists: a volcano-genetic, a hydro-hydrothermal and an ultra-basic factor. Thedisplay of fuzzy membership values and/or factor scores versus depth providedconsistent results for two factors only; the ultra-basic component could not beidentified. The reason for this may be that only traditional statistical methods wereapplied, i.e. the untransformed components were used and the cosine-theta coefficient assimilarity measure.During the last decade considerable progress in compositional data analysis was madeand many case studies were published using new tools for exploratory analysis of thesedata. Therefore it makes sense to check if the application of suitable data transformations,reduction of the D-part simplex to two or three factors and visualinterpretation of the factor scores would lead to a revision of earlier results and toanswers to open questions . In this paper we follow the lines of a paper of R. Tolosana-Delgado et al. (2005) starting with a problem-oriented interpretation of the biplotscattergram, extracting compositional factors, ilr-transformation of the components andvisualization of the factor scores in a spatial context: The compositional factors will beplotted versus depth (time) of the core samples in order to facilitate the identification ofthe expected sources of the sedimentary process.Kew words: compositional data analysis, biplot, deep sea sediments

Dynamic graphics of parametrically linked multivariate methods used in compositional data analysis

Many multivariate methods that are apparently distinct can be linked by introducing oneor more parameters in their definition. Methods that can be linked in this way arecorrespondence analysis, unweighted or weighted logratio analysis (the latter alsoknown as "spectral mapping"), nonsymmetric correspondence analysis, principalcomponent analysis (with and without logarithmic transformation of the data) andmultidimensional scaling. In this presentation I will show how several of thesemethods, which are frequently used in compositional data analysis, may be linkedthrough parametrizations such as power transformations, linear transformations andconvex linear combinations. Since the methods of interest here all lead to visual mapsof data, a "movie" can be made where where the linking parameter is allowed to vary insmall steps: the results are recalculated "frame by frame" and one can see the smoothchange from one method to another. Several of these "movies" will be shown, giving adeeper insight into the similarities and differences between these methods

Robust Factor Analysis for Compositional Data

Factor analysis as frequent technique for multivariate data inspection is widely used also for compositional data analysis. The usual way is to use a centered logratio (clr)transformation to obtain the random vector y of dimension D. The factor model istheny = Λf + e (1)with the factors f of dimension k & D, the error term e, and the loadings matrix Λ.Using the usual model assumptions (see, e.g., Basilevsky, 1994), the factor analysismodel (1) can be written asCov(y) = ΛΛT + ψ (2)where ψ = Cov(e) has a diagonal form. The diagonal elements of ψ as well as theloadings matrix Λ are estimated from an estimation of Cov(y).Given observed clr transformed data Y as realizations of the random vectory. Outliers or deviations from the idealized model assumptions of factor analysiscan severely effect the parameter estimation. As a way out, robust estimation ofthe covariance matrix of Y will lead to robust estimates of Λ and ψ in (2), seePison et al. (2003). Well known robust covariance estimators with good statisticalproperties, like the MCD or the S-estimators (see, e.g. Maronna et al., 2006), relyon a full-rank data matrix Y which is not the case for clr transformed data (see,e.g., Aitchison, 1986).The isometric logratio (ilr) transformation (Egozcue et al., 2003) solves thissingularity problem. The data matrix Y is transformed to a matrix Z by usingan orthonormal basis of lower dimension. Using the ilr transformed data, a robustcovariance matrix C(Z) can be estimated. The result can be back-transformed tothe clr space byC(Y ) = V C(Z)V Twhere the matrix V with orthonormal columns comes from the relation betweenthe clr and the ilr transformation. Now the parameters in the model (2) can beestimated (Basilevsky, 1994) and the results have a direct interpretation since thelinks to the original variables are still preserved.The above procedure will be applied to data from geochemistry. Our specialinterest is on comparing the results with those of Reimann et al. (2002) for the Kolaproject data

Compositional data analysis: where we are and where should we be heading?

We take stock of the present position of compositional data analysis, of what has beenachieved in the last 20 years, and then make suggestions as to what may be sensibleavenues of future research. We take an uncompromisingly applied mathematical view,that the challenge of solving practical problems should motivate our theoreticalresearch; and that any new theory should be thoroughly investigated to see if it mayprovide answers to previously abandoned practical considerations. Indeed a main themeof this lecture will be to demonstrate this applied mathematical approach by a number ofchallenging examples