A simulation study on the statistical monitoring of condemnation rates from slaughterhouses for syndromic surveillance: an evaluation based on Swiss data

Syndromic surveillance (SyS) systems currently exploit various sources of health-related data, most of which are collected for purposes other than surveillance (e.g. economic). Several European SyS systems use data collected during meat inspection for syndromic surveillance of animal health, as some diseases may be more easily detected post-mortem than at their point of origin or during the ante-mortem inspection upon arrival at the slaughterhouse. In this paper we use simulation to evaluate the performance of a quasi-Poisson regression (also known as an improved Farrington) algorithm for the detection of disease outbreaks during post-mortem inspection of slaughtered animals. When parameterizing the algorithm based on the retrospective analyses of 6 years of historic data, the probability of detection was satisfactory for large (range 83-445 cases) outbreaks but poor for small (range 20-177 cases) outbreaks. Varying the amount of historical data used to fit the algorithm can help increasing the probability of detection for small outbreaks. However, while the use of a 0·975 quantile generated a low false-positive rate, in most cases, more than 50% of outbreak cases had already occurred at the time of detection. High variance observed in the whole carcass condemnations time-series, and lack of flexibility in terms of the temporal distribution of simulated outbreaks resulting from low reporting frequency (monthly), constitute major challenges for early detection of outbreaks in the livestock population based on meat inspection data. Reporting frequency should be increased in the future to improve timeliness of the SyS system while increased sensitivity may be achieved by integrating meat inspection data into a multivariate system simultaneously evaluating multiple sources of data on livestock health.

In situ dehydration behavior of zeolite-like cavansite: A single-crystal X-ray study

To track dehydration behavior of cavansite, Ca(VO)(Si4O10)·4H2O space group Pnma, a = 9.6329(2), b = 13.6606(2), c = 9.7949(2) Å, V = 1288.92(4) Å3 single-crystal X-ray diffraction data on a crystal from Wagholi quarry, Poona district (India) were collected up to 400 °C in steps of 25 °C up to 250 °C and in steps of 50 °C between 250 and 400 °C. The structure of cavansite is characterized by layers of silicate tetrahedra connected by V4+O5 square pyramids. This way a porous framework structure is formed with Ca and H2O as extraframework occupants. At room temperature, the hydrogen bond system was analyzed. Ca is eightfold coordinated by four bonds to O of the framework structure and four bonds to H2O molecules. H2O linked to Ca is hydrogen bonded to the framework and also to adjacent H2O molecules. The dehydration in cavansite proceeds in four steps.At 75 °C, H2O at O9 was completely expelled leading to 3 H2O pfu with only minor impact on framework distortion and contraction V = 1282.73(3) Å3. The Ca coordination declined from originally eightfold to sevenfold and H2O at O7 displayed positional disorder.At 175 °C, the split O7 sites approached the former O9 position. In addition, the sum of the three split positions O7, O7a, and O7b decreased to 50% occupancy yielding 2 H2O pfu accompanied by a strong decrease in volume V = 1206.89(8) Å3. The Ca coordination was further reduced from sevenfold to sixfold.At 350 °C, H2O at O8 was released leading to a formula with 1 H2O pfu causing additional structural contraction (V = 1156(11) Å3). At this temperature, Ca adopted fivefold coordination and O7 rearranged to disordered positions closer to the original O9 H2O site.At 400 °C, cavansite lost crystallinity but the VO2+ characteristic blue color was preserved. Stepwise removal of water is discussed on the basis of literature data reporting differential thermal analyses, differential thermo-gravimetry experiments and temperature dependent IR spectra in the range of OH stretching vibrations.

Improving the dependability of research in personality and social psychology: Recommendations for research and educational practice

In this article, the Society for Personality and Social Psychology (SPSP) Task Force on Publication and Research Practices offers a brief statistical primer and recommendations for improving the dependability of research. Recommendations for research practice include (a) describing and addressing the choice of N (sample size) and consequent issues of statistical power, (b) reporting effect sizes and 95% confidence intervals (CIs), (c) avoiding “questionable research practices” that can inflate the probability of Type I error, (d) making available research materials necessary to replicate reported results, (e) adhering to SPSP’s data sharing policy, (f) encouraging publication of high-quality replication studies, and (g) maintaining flexibility and openness to alternative standards and methods. Recommendations for educational practice include (a) encouraging a culture of “getting it right,” (b) teaching and encouraging transparency of data reporting, (c) improving methodological instruction, and (d) modeling sound science and supporting junior researchers who seek to “get it right.”

Estimating market access in non-GPA countries: A suggested methodology

The WTO’s Agreement on Government Procurement (GPA) has data reporting obligations for all its Contracting Parties. Submitting such data promotes transparency in public procurement and also signals tendencies towards discrimination. However, most developing countries, especially emerging economies, are non-members of the GPA and therefore have no comparable data reporting obligations. In most cases, this has led to an absence of any reliable data on these countries’ public purchases, which poses a serious challenge in international negotiations on the subject and in examining the impact of protectionist measures in these countries’ public markets. In this short paper, we attempt to overcome these data challenges by developing a methodology to estimate the size of procurement markets in non-GPA countries as well as foreign market access therein. We also show the results from this methodology for estimating the EU’s access in select emerging economies’ public markets.

Reporting and handling missing outcome data in mental health: a systematic review of Cochrane systematic reviews and meta-analyses

OBJECTIVES The purpose of the study was to provide empirical evidence about the reporting of methodology to address missing outcome data and the acknowledgement of their impact in Cochrane systematic reviews in the mental health field. METHODS Systematic reviews published in the Cochrane Database of Systematic Reviews after January 1, 2009 by three Cochrane Review Groups relating to mental health were included. RESULTS One hundred ninety systematic reviews were considered. Missing outcome data were present in at least one included study in 175 systematic reviews. Of these 175 systematic reviews, 147 (84%) accounted for missing outcome data by considering a relevant primary or secondary outcome (e.g., dropout). Missing outcome data implications were reported only in 61 (35%) systematic reviews and primarily in the discussion section by commenting on the amount of the missing outcome data. One hundred forty eligible meta-analyses with missing data were scrutinized. Seventy-nine (56%) of them had studies with total dropout rate between 10 and 30%. One hundred nine (78%) meta-analyses reported to have performed intention-to-treat analysis by including trials with imputed outcome data. Sensitivity analysis for incomplete outcome data was implemented in less than 20% of the meta-analyses. CONCLUSIONS Reporting of the techniques for handling missing outcome data and their implications in the findings of the systematic reviews are suboptimal.

Timely Reporting and Interactive Visualization of Animal Health and Slaughterhouse Surveillance Data in Switzerland

The reporting of outputs from health surveillance systems should be done in a near real-time and interactive manner in order to provide decision makers with powerful means to identify, assess, and manage health hazards as early and efficiently as possible. While this is currently rarely the case in veterinary public health surveillance, reporting tools do exist for the visual exploration and interactive interrogation of health data. In this work, we used tools freely available from the Google Maps and Charts library to develop a web application reporting health-related data derived from slaughterhouse surveillance and from a newly established web-based equine surveillance system in Switzerland. Both sets of tools allowed entry-level usage without or with minimal programing skills while being flexible enough to cater for more complex scenarios for users with greater programing skills. In particular, interfaces linking statistical softwares and Google tools provide additional analytical functionality (such as algorithms for the detection of unusually high case occurrences) for inclusion in the reporting process. We show that such powerful approaches could improve timely dissemination and communication of technical information to decision makers and other stakeholders and could foster the early-warning capacity of animal health surveillance systems.

Appropriateness of reporting statistical results in orthodontics: the dominance of P values over confidence intervals

The purpose of this study was to search the orthodontic literature and determine the frequency of reporting of confidence intervals (CIs) in orthodontic journals with an impact factor. The six latest issues of the American Journal of Orthodontics and Dentofacial Orthopedics, the European Journal of Orthodontics, and the Angle Orthodontist were hand searched and the reporting of CIs, P values, and implementation of univariate or multivariate statistical analyses were recorded. Additionally, studies were classified according to the type/design as cross-sectional, case-control, cohort, and clinical trials, and according to the subject of the study as growth/genetics, behaviour/psychology, diagnosis/treatment, and biomaterials/biomechanics. The data were analyzed using descriptive statistics followed by univariate examination of statistical associations, logistic regression, and multivariate modelling. CI reporting was very limited and was recorded in only 6 per cent of the included published studies. CI reporting was independent of journal, study area, and design. Studies that used multivariate statistical analyses had a higher probability of reporting CIs compared with those using univariate statistical analyses. Misunderstanding of the use of P values and CIs may have important implications in implementation of research findings in clinical practice.

A multi-level decomposition of variance in somatic symptom reporting in families with adolescent children

OBJECTIVES: This paper examines four different levels of possible variation in symptom reporting: occasion, day, person and family. DESIGN: In order to rule out effects of retrospection, concurrent symptom reporting was assessed prospectively using a computer-assisted self-report method. METHODS: A decomposition of variance in symptom reporting was conducted using diary data from families with adolescent children. We used palmtop computers to assess concurrent somatic complaints from parents and children six times a day for seven consecutive days. In two separate studies, 314 and 254 participants from 96 and 77 families, respectively, participated. A generalized multilevel linear models approach was used to analyze the data. Symptom reports were modelled using a logistic response function, and random effects were allowed at the family, person and day level, with extra-binomial variation allowed for on the occasion level. RESULTS: Substantial variability was observed at the person, day and occasion level but not at the family level. CONCLUSIONS: To explain symptom reporting in normally healthy individuals, situational as well as person characteristics should be taken into account. Family characteristics, however, would not help to clarify symptom reporting in all family members.

When one depends on the other: reporting of interaction in case-control and cohort studies

BACKGROUND: Interaction refers to the situation in which the effect of 1 exposure on an outcome differs across strata of another exposure. We did a survey of epidemiologic studies published in leading journals to examine how interaction is assessed and reported. METHODS: We selected 150 case-control and 75 cohort studies published between May 2001 and May 2007 in leading general medicine, epidemiology, and clinical specialist journals. Two reviewers independently extracted data on study characteristics. RESULTS: Of the 225 studies, 138 (61%) addressed interaction. Among these, 25 (18%) presented no data or only a P value or a statement of statistical significance; 40 (29%) presented stratum-specific effect estimates but no meaningful comparison of these estimates; and 58 (42%) presented stratum-specific estimates and appropriate tests for interaction. Fifteen articles (11%) presented the individual effects of both exposures and also their joint effect or a product term, providing sufficient information to interpret interaction on an additive and multiplicative scale. Reporting was poorest in articles published in clinical specialist articles and most adequate in articles published in general medicine journals, with epidemiology journals in an intermediate position. CONCLUSIONS: A majority of articles reporting cohort and case-control studies address possible interactions between exposures. However, in about half of these, the information provided was unsatisfactory, and only 1 in 10 studies reported data that allowed readers to interpret interaction effects on an additive and multiplicative scale.

STrengthening the REporting of Genetic Association studies (STREGA)--an extension of the STROBE statement

Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information in the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association studies (STREGA) initiative builds on the STrengthening the Reporting of OBservational Studies in Epidemiology (STROBE) Statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modelling haplotype variation, Hardy-Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data and the volume of data issues that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed, but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct or analysis.

STrengthening the REporting of Genetic Association Studies (STREGA)--an extension of the STROBE statement

Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information in the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association studies (STREGA) initiative builds on the STrengthening the Reporting of OBservational Studies in Epidemiology (STROBE) Statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modelling haplotype variation, Hardy-Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data, and the volume of data issues that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct, or analysis.