425 research outputs found
sj-docx-1-mdm-10.1177_0272989X211045070 – Supplemental material for Generating, Presenting, and Interpreting Cost-Effectiveness Results in the Context of Uncertainty: A Tutorial for Deeper Knowledge and Better Practice
No full textSupplemental material, sj-docx-1-mdm-10.1177_0272989X211045070 for Generating, Presenting, and Interpreting Cost-Effectiveness Results in the Context of Uncertainty: A Tutorial for Deeper Knowledge and Better Practice by Joke Bilcke and Philippe Beutels in Medical Decision Making</p
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
DS_10.1177_0272989X18776636 – Supplemental material for Sponsorship Bias in Base-Case Values and Uncertainty Bounds of Health Economic Evaluations?
No full textSupplemental material, DS_10.1177_0272989X18776636 for Sponsorship Bias in Base-Case Values and Uncertainty Bounds of Health Economic Evaluations? by Joke Bilcke, Frederik Verelst and Philippe Beutels in Medical Decision Making</p
Cost effectiveness of pediatric pneumococcal conjugate vaccines: a comparative assessment of decision-making tools.
No full textBACKGROUND: Several decision support tools have been developed to aid policymaking regarding the adoption of pneumococcal conjugate vaccine (PCV) into national pediatric immunization programs. The lack of critical appraisal of these tools makes it difficult for decision makers to understand and choose between them. With the aim to guide policymakers on their optimal use, we compared publicly available decision-making tools in relation to their methods, influential parameters and results. METHODS: The World Health Organization (WHO) requested access to several publicly available cost-effectiveness (CE) tools for PCV from both public and private provenance. All tools were critically assessed according to the WHO's guide for economic evaluations of immunization programs. Key attributes and characteristics were compared and a series of sensitivity analyses was performed to determine the main drivers of the results. The results were compared based on a standardized set of input parameters and assumptions. RESULTS: Three cost-effectiveness modeling tools were provided, including two cohort-based (Pan-American Health Organization (PAHO) ProVac Initiative TriVac, and PneumoADIP) and one population-based model (GlaxoSmithKline's SUPREMES). They all compared the introduction of PCV into national pediatric immunization program with no PCV use. The models were different in terms of model attributes, structure, and data requirement, but captured a similar range of diseases. Herd effects were estimated using different approaches in each model. The main driving parameters were vaccine efficacy against pneumococcal pneumonia, vaccine price, vaccine coverage, serotype coverage and disease burden. With a standardized set of input parameters developed for cohort modeling, TriVac and PneumoADIP produced similar incremental costs and health outcomes, and incremental cost-effectiveness ratios. CONCLUSIONS: Vaccine cost (dose price and number of doses), vaccine efficacy and epidemiology of critical endpoint (for example, incidence of pneumonia, distribution of serotypes causing pneumonia) were influential parameters in the models we compared. Understanding the differences and similarities of such CE tools through regular comparisons could render decision-making processes in different countries more efficient, as well as providing guiding information for further clinical and epidemiological research. A tool comparison exercise using standardized data sets can help model developers to be more transparent about their model structure and assumptions and provide analysts and decision makers with a more in-depth view behind the disease dynamics. Adherence to the WHO guide of economic evaluations of immunization programs may also facilitate this process. Please see related article: http://www.biomedcentral.com/1741-7007/9/55
Modelling distortions in seroprevalence data using change-point fractional polynomials
No full textAbstract: This paper shows how to model seroprevalence data using change-point fractional polynomials (FPs). The inclusion of a change point in the FP framework allows to detect distortions arising from common (often untestable) assumptions made in the estimation of the age-specific prevalence and force of infection from cross-sectional data. The method is motivated using seroprevalence data on the parvovirus B19 and the varicella zoster virus in Belgium
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
Indications for healthcare surge capacity in European countries facing an exponential increase in coronavirus disease (COVID-19) cases, March 2020
No full textEuropean healthcare systems face extreme pressure from coronavirus disease (COVID-19). We relate country-specific accumulated COVID-19 deaths (intensity approach) and active COVID-19 cases (magnitude approach) to measures of healthcare system capacity: hospital beds, healthcare workers and healthcare expenditure. Modelled by the intensity approach with a composite measure for healthcare capacity, the countries experiencing the highest pressure on 25 March 2020 - relative to Italy on 11 March - were Italy, Spain, the Netherlands and France (www.covid-hcpressure.org).This work is funded by the Epipose project from the European Union's SC1- PHE-CORONAVIRUS-2020 programme, project number 101003688.0Verelst, F (reprint author), Univ Antwerp, Vaccine & Infect Dis Inst VAXINFECTIO, CHERMID, Antwerp, Belgium.
[email protected]
Immunogenicity and persistence of trivalent measles, mumps, and rubella vaccines : a systematic review and meta-analysis
No full textAbstract: Background Despite the universal use of the two-dose trivalent measles-mumps-rubella (MMR) vaccine in the past two decades, outbreaks of these diseases still occur in countries with high vaccine uptake, giving rise to concerns about primary and secondary failure of MMR vaccine components. We aimed to provide seroconversion and waning rate estimates for the measles, mumps, and rubella components of MMR vaccines. Methods In this systematic review and meta-analysis we searched PubMed (including MEDLINE), Web of Science, and Embase for randomised controlled trials, cohort studies, or longitudinal studies reporting the immunogenicity and persistence of MMR vaccines, published in English from database inception to Dec 31, 2019. Studies were included if they investigated vaccine-induced immunity in healthy individuals who received a trivalent MMR vaccine, including different dosages and timepoints of vaccine administration. Studies featuring coadministration of MMR with other vaccines, maternal immunity to the MMR vaccine, or non-trivalent formulations of the vaccine were excluded. Pooled seroconversion and waning rates were estimated by random-effects meta-analyses. This study is registered with PROSPERO, CRD42019116705. Findings We identified 3615 unique studies, 62 (1.7%) of which were eligible for analysis. Estimated overall seroconversion rates were 96.0% (95% CI 94.5-97.4; I-2=91.1%) for measles, 93.3% (91.1-95.2; I-2=94.9%) for mumps when excluding the Rubini strain, 91.1% (87.4-94.1; I-2=96.6%) for mumps when including the Rubini strain, and 98.3% (97.3-99.2; I-2=93.0%) for rubella. Estimated overall annual waning rates were 0.009 (95% CI 0.005-0.016; I-2=85.2%) for measles, 0.024 (0.016-0.039; I-2=94.7%) for mumps, and 0.012 (0.010-0.014; I-2=93.3%) for rubella. Interpretation Our meta-analysis provides estimates of primary and secondary vaccine failure, which are essential to improve the accuracy of mathematical and statistical modelling to understand and predict the occurrence of future measles, mumps, and rubella outbreaks in countries with high vaccine uptake. Funding European Research Council. Copyright (C) 2020 Elsevier Ltd. All rights reserved
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
Determinants of COVID-19 vaccination coverage in European and Organisation for Economic Co-operation and Development (OECD) countries
No full textIntroduction In relatively wealthy countries, substantial between-country variability in COVID-19 vaccination coverage occurred. We aimed to identify influential national-level determinants of COVID-19 vaccine uptake at different COVID-19 pandemic stages in such countries.Methods We considered over 50 macro-level demographic, healthcare resource, disease burden, political, socio-economic, labor, cultural, life-style indicators as explanatory factors and coverage with at least one dose by June 2021, completed initial vaccination protocols by December 2021, and booster doses by June 2022 as outcomes. Overall, we included 61 European or Organisation for Economic Co-operation and Development (OECD) countries. We performed 100 multiple imputations correcting for missing data and partial least squares regression for each imputed dataset. Regression estimates for the original covariates were pooled over the 100 results obtained for each outcome. Specific analyses focusing only on European Union (EU) or OECD countries were also conducted.Results Higher stringency of countermeasures, and proportionately more older adults, female and urban area residents, were each strongly and consistently associated with higher vaccination rates. Surprisingly, socio-economic indicators such as gross domestic product (GDP), democracy, and education had limited explanatory power. Overall and in the OECD, greater perceived corruption related strongly to lower vaccine uptake. In the OECD, social media played a noticeable positive role. In the EU, right-wing government ideology exhibited a consistently negative association, while cultural differences had strong overall influence.Conclusion Relationships between country-level factors and COVID-19 vaccination uptake depended on immunization stage and country reference group. Important determinants include stringency, population age, gender and urbanization, corruption, government ideology and cultural context.The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This study received funding from the Research Foundation Flanders (FWO project number G0D5917N) and the European Union’s Horizon 2020 research and innovation programme (Project EpiPose – project number 101003688, 2020 and Project ESCAPE – project number 101095619). The sponsors had no role in the study design;
in the collection, analysis and interpretation of data; in writing the article; and in the decision to submit it for publication. This work reflects only the authors’ views. The European Commission is not responsible for any use that may be made of the information it contains
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