1,721,145 research outputs found
Estimating health utility associated with mental well-being: mapping GHQ-12 responses onto EQ-5D-5L
No full textcitation ID: ckaf161.006 Cost effectiveness of improving HPV vaccine uptake in This contributes to preventable disease burdens and widening health inequities. Within the framework of the RIVER-EU project, interventions were designed to address health system barriers to vaccine access. This study evaluates the cost-effectiveness of one of these interventions aimed at improving HPV vaccine uptake among the underserved populations in the Netherlands focusing on the Turkish and Moroccan communities. Methods: A gender-neutral static cohort model considering six HPV-related cancers was developed to simulate the lifetime health and economic impacts of the intervention. Input parameters were sourced from national databases and published literature. Primary outcome measures were cancer cases and deaths averted and the incremental cost effectiveness ratio (ICER). Costs were adjusted to 2024 euros using the Dutch consumer price index (CPI), with discount rates of 3% and 1.5% applied on costs and effects respectively. Probabilistic and one-way sensitivity analyses assessed model and parameter uncertainty. Results: Preliminary results estimated discounted incremental costs and QALYs of e1.04million and 627 QALYs respectively, resulting in an ICER of e1665 per QALY. These early results reflect reductions in HPV-related cancer cases and deaths from increased vaccination. Sensitivity analyses revealed that the model was most influenced by and intervention costs and vaccination coverage. Final results incorporating updated parameters will be presented during the conference. Conclusions: Implementing targeted interventions to improve HPV vaccine uptake in underserved populations has the potential to be cost-effective while advancing health equity. These findings support scaling such strategies to close vaccination gaps and reduce HPV-related disease burdens. Key messages: • Targeted interventions in marginalized communities can be cost-effective. • Improving HPV vaccine uptake in underserved populations promotes health equity. Abstract citation ID: ckaf161.007 Background: Mental well-being measures are common in population surveys but cannot be directly used for utility-based economic evaluations. Existing mapping studies, mostly pre-Covid-19, relied on linear regression, and may not reflect individuals' evolving preferences on quality of life. This study explores methods to estimate health utility associated with mental well-being, by linking EQ-5D-5L and GHQ-12 responses collected in a large population sample. Methods: We used data from 12701 respondents participating in the 46th Wave of the Belgian "Great Corona Study", in March 2022. We compared direct methods (linear and inflated beta regression) that map source responses directly to utility values, with indirect methods that estimate responses for each EQ-5D-5L dimension using non-parametric or ordered logistic regression before generating utilities. Regression models used either individual GHQ-12 items or the total score as the dependent variable, controlling for sociodemo-graphic factors. Model performance was assessed using root mean squared error (RMSE). Results: Greater GHQ-12 distress, at both item and total score levels was linked with greater problems across EQ-5D dimensions and lower utility values. RMSE ranged from 0.142 (linear model with GHQ-12 items) to 0.157 (beta inflated model with GHQ-12 scores), with linear and ordered logistic models performing best, although linear models performed worse than beta when estimating values at the lower end. Despite violated normality assumptions, linear regression yielded the lowest RMSE. Indirect mapping is conceptually more robust, as it aligns closely with the dimensional structure of EQ-5D-5L and minimises variations associated with the use of different value sets. Conclusions: This study provides up-to-date algorithms for mapping mental well-being data to health utility values. The mapping can enable the integration of mental health data for use in QALY-based economic evaluations, where utility data are not available. Key messages: • This study provides updated algorithms for estimating health utility values from mental well-being data, enabling the integration of mental health measures into QALY-based economic evaluations. • Choosing the best mapping method involves balancing predictive performance with conceptual appropriateness and simplicity
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
HOW WILL DEMOGRAPHIC CHANGE AFFECT THE DISEASE BURDEN OF FUTURE EPIDEMICS?
No full texton the cobas SARS-CoV-2 assay (Roche) and the Aptima SARS-CoV-2 assay (Hologic). Findings: We demonstrated comparable sensitivity, specificity, and agreement between self-collected nasal and Rhinoswab samples , compared to HCW-collected samples tested using the cobas SARS-CoV-2 and Aptima SARS-CoV-2 assays. In our study the clinical performance of self-collected specimens was comparable to HCW-collected samples, with both self-collect nasal and Rhi-noswab samples resulting in 90-95% sensitivity, and in most cases > 95% specificity. Discussion: Without the availability of samples for NAAT the ability to perform genomic testing is limited, reducing surveillance and public health investigations. We showed that genomic sequencing from self-collected samples can correctly identify the virus lineage and that the main determination of successful ge-nomic testing is a high viral load rather than collection method. Conclusion: These data support self-collection as an accessible method for community testing for COVID-19 and introduces a novel collection device, the Rhinoswab as an alternative to the standard nasal swab. The testing method of self-collection can be expanded from the widely used RATs to NAAT and genomic testing which may inform the management and public health response to the COVID-19 pandemic
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Seventy-five years of estimating the force of infection from current status data
No full textThe force of infection, describing the rate at which a susceptible person acquires an infection, is a key parameter in models estimating the infectious disease burden, and the effectiveness and cost-effectiveness of infectious disease prevention. Since Muench formulated the first catalytic model to estimate the force of infection from current status data in 1934, exactly 75 years ago, several authors addressed the estimation of this parameter by more advanced statistical methods, while applying these to seroprevalence and reported incidence/case notification data. In this paper we present an historical overview, discussing the relevance of Muench's work, and we explain the wide array of newer methods with illustrations on pre-vaccination serological survey data of two airborne infections: rubella and parvovirus B19. We also provide guidance on deciding which method(s) to apply to estimate the force of infection, given a particular set of data.We thank the editor and both referees for their valuable suggestions that have led to an improved version of the manuscript. This work was supported by research project (MSM 0021620839), funded by 'SIMID', a strategic basic research project funded by the institute for the Promotion of Innovation by Science and Technology in Flanders (IWT) (project number 06008); by the Fund of Scientific Research (FWO, Research Grant G039304) in Flanders, Belgium; and by the TAP research network (no. P6/03) of the Belgian Government (Belgian Science Policy). The R-code used to analyse the datasets in this manuscript is available from the authors
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
Estimating transmission parameters using social contact data and serological data
No full textIn order to restrict the damage caused by an epidemic, intervention strategies are needed to reduce the transmission of infected-specific antigens. To this purpose, the estimation of age-dependent transmission rates is required. In the past, different mixing patterns were imposed to the so-called Who-Acquires-Infection-From-Whom matrix (WAIFW) to make them estimable from seroprevalence data (Anderson and May, 1991). These mixing assumptions, however are rather artificial and result in large differences on the estimation of the basic reproduction number R0, a basic quantity in infectious disease epidemiology. More recently, an alternative approach has come up, originating from assuming transmission rates for directly transmitted airborne infections are proportional to rates of conversational contact making (Wallinga et al., 2006). In this paper, we shown how transmission parameters can be estimated using serological data on varicella zoster virus (VZV) and social contact data from Belgium. We elaborate on the methodology as presented by Walling et al. (2006), by explicitly accounting for the different sources of variability, using a continuous rather than discrete modeling approach and by testing the proportionality assumption. A cross-sectional survey on social contacts was conducted in Belgium from March to June 2006. Contacted persons had to record their contacts during one day including characteristics as age, gender, location and duration of the contact. Moreover, a distinction between two types of contact was made: non-close contacts, defined as a two-way conversation of at least three words in each others proximity, and close contacts that involve any sort of physical skin-to-skin touching. The 'social contact matrix' is estimated using a bivariate smoothing approach based on thin plate regression splines. Using the mass action principle, these estimated contact rates are contrasted to seroprevalence data to obtain transmission parameters. A first analysis focuses on the constant proportionality assumption: transmission rates are proportional to contact rates up to a constant q. Five contact types which are likely to be responsible for VZV transmission are considered. According to the AIC-criterion, close contacts lasting longer than 15 minutes are most capable of explaining the observed serological profile. A non-parametric bootstrap approach is applied to assess sampling variability and to account for age uncertainty. Secondly, we explore whether the proportionality factor q depends on the age of the susceptible person, the age of the infected person or both. This consideration makes logical sense, since transmission dynamics might also be influenced by age differences in susceptibility, infectivity, hygiene, etc. Age dependence is modeled using discrete structures as well as loglinear regression models. For VZV in Belgium, extending the model to age-dependent proportionality entails an improvement in fit. Concepts of model selection uncertainty are illustrated for the set of candidate models and a model averaged estimate is calculated for the set of candidate models and a model averaged estimate is calculated for the basic reproduction number R0
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