A comparison of self-report and health care provider data to assess surveillance definitions of influenza-like illness in outpatients

Objective: Several surveillance definitions of influenza-like illness (ILI) have been proposed, based on the presence of symptoms. Symptom data can be obtained from patients, medical records, or both. Past research has found that agreements between health record data and self-report are variable depending on the specific symptom. Therefore, we aimed to explore the implications of using data on influenza symptoms extracted from medical records, similar data collected prospectively from outpatients, and the combined data from both sources as predictors of laboratory-confirmed influenza. Methods: Using data from the Hutterite Influenza Prevention Study, we calculated: 1) the sensitivity, specificity and predictive values of individual symptoms within surveillance definitions; 2) how frequently surveillance definitions correlated to laboratory-confirmed influenza; and 3) the predictive value of surveillance definitions. Results: Of the 176 participants with reports from participants and medical records, 142 (81%) were tested for influenza and 37 (26%) were PCR positive for influenza. Fever (alone) and fever combined with cough and/or sore throat were highly correlated with being PCR positive for influenza for all data sources. ILI surveillance definitions, based on symptom data from medical records only or from both medical records and self-report, were better predictors of laboratory-confirmed influenza with higher odds ratios and positive predictive values. Discussion: The choice of data source to determine ILI will depend on the patient population, outcome of interest, availability of data source, and use for clinical decision making, research, or surveillance. © Canadian Public Health Association, 2012.

'Dare the boist'rous main': the role of the Belfast Newsletter in the process of emigration from Ulster to North America 1760-1800

Before the mass migrations from Ireland in the nineteenth century, earlier waves of migration in the eighteenth century saw significant numbers of people leave Ireland, predominantly from Ulster, to settle in North America. This article, using as its principal data source the Belfast News Letter ( BNL), its letters, advertisements and reports, focuses firstly on reconstructing the late eighteenth-century migration process and voyage, highlighting the barriers represented by the Atlantic Ocean. In addition to the challenges of the sea, there were problems with the ships, the ever-present danger of disease and also threats from other vessels, from privateers to press gangs. The voyage was recognized as a ‘universal dread’, and the risks taken to ‘dare the boist’rous main’ were perhaps not minimized in the pages of the BNL, whose editorial stance was antipathetic to the migration for the potential harm it caused to Ulster by removing so many of its industrious young. The second part of this article goes on to consider the newspaper’s and others’ vested interests in the emigration process, demonstrates how these were manifested in the press and sets the coverage of this very significant early emigration flow within the context of contemporary religious and colonial discourses at a period of very lively transatlantic interactions.

Disparities in breast cancer mortality trends between 30 European countries: Retrospective trend analysis of WHO mortality database

Objective: To examine changes in temporal trends in breast cancer mortality in women living in 30 European countries.
Design: Retrospective trend analysis.
Data source: WHO mortality database on causes of deaths
Subjects reviewed: Female deaths from breast cancer from 1989 to 2006
Main outcome measures: Changes in breast cancer mortality for all women and by age group (<50, 50-69, and >= 70 years) calculated from linear regressions of log transformed, age adjusted death rates. Joinpoint analysis was used to identify the year when trends in all age mortality began to change.
Results: From 1989 to 2006, there was a median reduction in breast cancer mortality of 19%, ranging from a 45% reduction in Iceland to a 17% increase in Romania. Breast cancer mortality decreased by >= 20% in 15 countries, and the reduction tended to be greater in countries with higher mortality in 1987-9. England and Wales, Northern Ireland, and Scotland had the second, third, and fourth largest decreases of 35%, 29%, and 30%, respectively. In France, Finland, and Sweden, mortality decreased by 11%, 12%, and 16%, respectively. In central European countries mortality did not decline or even increased during the period. Downward mortality trends usually started between 1988 and 1996, and the persistent reduction from 1999 to 2006 indicates that these trends may continue. The median changes in the age groups were -37% (range -76% to -14%) in women aged <50, -21% (-40% to 14%) in 50-69 year olds, and -2% (-42% to 80%) in >= 70 year olds.
Conclusions: Changes in breast cancer mortality after 1988 varied widely between European countries, and the UK is among the countries with the largest reductions. Women aged <50 years showed the greatest reductions in mortality, also in countries where screening at that age is uncommon. The increasing mortality in some central European countries reflects avoidable mortality.

Increasing the accuracy of Nitrogen Dioxide (NO2) pollution mapping using geographically weighted regression (GWR) and geostatistics.

Nitrogen Dioxide (NO2) is known to act as an environmental trigger for many respiratory illnesses. As a pollutant it is difficult to map accurately, as concentrations can vary greatly over small distances. In this study three geostatistical techniques were compared, producing maps of NO2 concentrations in the United Kingdom (UK). The primary data source for each technique was NO2 point data, generated from background automatic monitoring and background diffusion tubes, which are analysed by different laboratories on behalf of local councils and authorities in the UK. The techniques used were simple kriging (SK), ordinary kriging (OK) and simple kriging with a locally varying mean (SKlm). SK and OK make use of the primary variable only. SKlm differs in that it utilises additional data to inform prediction, and hence potentially reduces uncertainty. The secondary data source was Oxides of Nitrogen (NOx) derived from dispersion modelling outputs, at 1km x 1km resolution for the UK. These data were used to define the locally varying mean in SKlm, using two regression approaches: (i) global regression (GR) and (ii) geographically weighted regression (GWR). Based upon summary statistics and cross-validation prediction errors, SKlm using GWR derived local means produced the most accurate predictions. Therefore, using GWR to inform SKlm was beneficial in this study.

Availability of stage at diagnosis, cancer treatment delay and compliance with cancer guidelines as cancer registry indicators for cancer care in Europe:Results of EUROCHIP-3 survey

EUROCHIP (European Cancer Health Indicators Project) focuses on understanding inequalities in the cancer burden, care and survival by the indicators "stage at diagnosis," "cancer treatment delay" and "compliance with cancer guidelines" as the most important indicators. Our study aims at providing insight in whether cancer registries collect well-defined variables to determine these indicators in a comparative way. Eighty-six general European population-based cancer registries (PBCR) from 32 countries responded to the questionnaire, which was developed by EUROCHIP in collaboration with ENCR (European Network of Cancer Registries) and EUROCOURSE. Only 15% of all the PBCR in EU had all three indicators available. The indicator "stage at diagnosis" was gathered for at least one cancer site by 81% (using TNM in 39%). Variables for the indicator "cancer treatment delay" were collected by 37%. Availability of type of treatment (30%), surgery date (36%), starting date of radiotherapy (26%) and starting date of chemotherapy (23%) resulted in 15% of the PBCRs to be able to gather the indicator "compliance to guidelines". Lack of data source access and qualified staff were the major reasons for not collecting all the variables. In conclusion, based on self-reporting, a few of the participating PBCRs had data available which could be used for clinical audits, evaluation of cancer care projects, survival and for monitoring national cancer control strategies. Extra efforts should be made to improve this very efficient tool to compare cancer burden and the effects of the national cancer plans over Europe and to learn from each other. © 2012 UICC.

The canadian longitudinal study on aging (CLSA)

Canadians are living longer, and older persons are making up a larger share of the population (14% in 2006, projected to rise to 20% by 2021). The Canadian Longitudinal Study on Aging (CLSA) is a national longitudinal study of adult development and aging that will recruit 50,000 Canadians aged 45 to 85 years of age and follow them for at least 20 years. All participants will provide a common set of information concerning many aspects of health and aging, and 30,000 will undergo an additional in-depth examination coupled with the donation of biological specimens (blood and urine). The CLSA will become a rich data source for the study of the complex interrelationship among the biological, physical, psychosocial, and societal factors that affect healthy aging. © 2009 Canadian Association on Gerontology.

Predicting forest attributes In southeast Alaska using artificial neural networks

Artificial neural network (ANN) methods are used to predict forest characteristics. The data source is the Southeast Alaska (SEAK) Grid Inventory, a ground survey compiled by the USDA Forest Service at several thousand sites. The main objective of this article is to predict characteristics at unsurveyed locations between grid sites. A secondary objective is to evaluate the relative performance of different ANNs. Data from the grid sites are used to train six ANNs: multilayer perceptron, fuzzy ARTMAP, probabilistic, generalized regression, radial basis function, and learning vector quantization. A classification and regression tree method is used for comparison. Topographic variables are used to construct models: latitude and longitude coordinates, elevation, slope, and aspect. The models classify three forest characteristics: crown closure, species land cover, and tree size/structure. Models are constructed using n-fold cross-validation. Predictive accuracy is calculated using a method that accounts for the influence of misclassification as well as measuring correct classifications. The probabilistic and generalized regression networks are found to be the most accurate. The predictions of the ANN models are compared with a classification of the Tongass national forest in southeast Alaska based on the interpretation of satellite imagery and are found to be of similar accuracy.

Video Lecture Capture : Student Engagement

Video Capture of university lectures enables learners to be more flexible in their learning behaviour, for instance choosing to attend lectures in person or watch later. However attendance at lectures has been linked to academic success and is of concern for faculty staff contemplating the introduction of Video Lecture Capture. This research study was devised to assess the impact on learning of recording lectures in computer programming courses. The study also considered behavioural trends and attitudes of the students watching recorded lectures, such as when, where, frequency, duration and viewing devices used. The findings suggest there is no detrimental effect on attendance at lectures with video materials being used to support continual and reinforced learning with most access occurring at assessment periods. The analysis of the viewing behaviours provides a rich and accessible data source that could be potentially leveraged to improve lecture quality and enhance lecturer and learning performance.

Late-Glacial and early Holocene marine 14C reservoir ages off North Iceland (16-9 cal kyr BP)

Tephrochronological age models and 48 14C age determinations on molluscs and foraminifera (planktonic and benthic) are applied for the calculation of marine 14C reservoir age variability during a time period covering the Heinrich event H1 to early Holocene (16–9 cal kyr BP). Our data source consists of four high-resolution marine sediment cores (HM107-04, HM107-05, MD99-2271, MD99-2275) from the North Icelandic shelf. The marine reservoir age (ΔR) is found to be extremely variable, ranging from 385 to 1065 14C years. Extreme ΔR values occur at the end of H1, with values around 1000 14C years (~15 cal kyr BP), probably due to reduced northward flow of well-ventilated subtropical surface waters and a southward expansion of polar waters, as well as an expansion of sea ice limiting air-sea gas exchange. With the onset of the Bølling-Allerød interstadial, the ΔR values decrease towards 0 14C years suggesting a more vigorous North Atlantic Current and an active meridional overturning circulation system. During the Younger Dryas stadial, ΔR values are consistently around 700 14C years suggesting e renewed expansion of polar waters and a weakened meridional overtuning circulation. Interestingly, ΔR values remain high (~200 14C years) at the onset of the Holocene suggesting continued high influence of polar waters. Subsequently, ΔR values rapidly decrease to ~¬ 250 14C years around 11 cal kyr BP, indicating increased air-sea CO2 exchange with the coeval atmosphere. The ΔR values average around 0 14C years from around 10.5 to 9.0 cal kyr BP.