Materials Map

Discover the materials research landscape. Find experts, partners, networks.

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The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

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The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

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in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (1/1 displayed)

  • 2023COVID-19 contact tracing at work in Belgium - how tracers tweak guidelines for the bettercitations

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Chart of shared publication
Raymenants, Joren
1 / 4 shared
Ruppol, Sandrine
1 / 1 shared
Speybroeck, Niko
1 / 2 shared
Kieltyka, Jerome
1 / 1 shared
Nicaise, Pablo
1 / 1 shared
Chart of publication period
2023

Co-Authors (by relevance)

  • Raymenants, Joren
  • Ruppol, Sandrine
  • Speybroeck, Niko
  • Kieltyka, Jerome
  • Nicaise, Pablo
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article

COVID-19 contact tracing at work in Belgium - how tracers tweak guidelines for the better

  • Raymenants, Joren
  • Ghattas, Jinane
  • Ruppol, Sandrine
  • Speybroeck, Niko
  • Kieltyka, Jerome
  • Nicaise, Pablo
Abstract

<jats:title>Abstract</jats:title><jats:sec><jats:title>Background</jats:title><jats:p>When conducting COVID-19 contact tracing, pre-defined criteria allow differentiating high-risk contacts (HRC) from low-risk contacts (LRC). Our study aimed to evaluate whether contact tracers in Belgium followed these criteria in practice and whether their deviations improved the infection risk assessment.</jats:p></jats:sec><jats:sec><jats:title>Method</jats:title><jats:p>We conducted a retrospective cohort study in Belgium, through an anonymous online survey, sent to 111,763 workers by email. First, we evaluated the concordance between the guideline-based classification of HRC or LRC and the tracer’s classification. We computed positive and negative agreements between both. Second, we used a multivariate Poisson regression to calculate the risk ratio (RR) of testing positive depending on the risk classification by the contact tracer and by the guideline-based risk classification.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>For our first research question, we included 1105 participants. The positive agreement between the guideline-based classification in HRC or LRC and the tracer’s classification was 0.53 (95% CI 0.49–0.57) and the negative agreement 0.70 (95% CI: 0.67–0.72). The type of contact tracer (occupational doctors, internal tracer, general practitioner, other) did not significantly influence the results. For the second research question, we included 589 participants. The RR of testing positive after an HRC compared to an LRC was 3.10 (95% CI: 2.71–3.56) when classified by the contact tracer and 2.24 (95% CI: 1.94–2.60) when classified by the guideline-based criteria.</jats:p></jats:sec><jats:sec><jats:title>Conclusion</jats:title><jats:p>Our study indicates that contact tracers did not apply pre-defined criteria for classifying high and low risk contacts. Risk stratification by contact tracers predicts who is at risk of infection better than guidelines only. This result indicates that a knowledgeable tracer can target testing better than a general guideline, asking for a debate on how to adapt the guidelines.</jats:p></jats:sec>

Topics
  • impedance spectroscopy
  • size-exclusion chromatography
  • chemical ionisation