ArticleBundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz2021
[How to assess the elimination of viral hepatitis B, C, and D in Germany? Outcomes of an interdisciplinary workshop].
Article in Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed, 5 citations in OpenAlex.
- Aspects that facilitate access to care for viral hepatitis: An evaluative research.Sao Paulo medical journal = Revista paulista de medicina · 2024Article
- [HIV/HCV Among Drug Users in Germany: Elimination Targets in the Mirror of Practice].Gesundheitswesen (Bundesverband der Arzte des Offentlichen Gesundheitsdienstes (Germany)) · 2023Article
- [Ten years of the National Reference Center for hepatitis B viruses and hepatitis D viruses in Giessen, Germany: activities and experiences].Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIn 2016, the World Health Organization (WHO) released a strategy to eliminate hepatitis B, C, and D and defined indicators to monitor the progress. The Robert Koch Institute organized an interdisciplinary working meeting in 2019 to identify data sources and gaps.
objectivesThe objectives were to network, to create an overview of the data sources available in Germany on hepatitis B and C, and to discuss how to construct indicators. MATERIALS AND
methodsWe extracted the WHO indicators relevant for Germany and determined how they can be constructed on the basis of available data. Stakeholders from public health services, clinics, laboratories, health insurance companies, research institutes, data holders, and registries attended a workshop and discussed methods of constructing the indicators for which data are lacking. Data sources and data were evaluated and prioritized with regard to their quality and completeness.
resultsIndicators on prevalence, incidence, prevention, testing and diagnosis, treatment, cure, burden of sequelae, and mortality for the general population can be constructed using secondary data such as diagnosis, health service, and registry data, data from laboratories and hospitals as well as population-based studies. Data sources for vulnerable groups are limited to studies among drug users, men who have sex with men, and about HIV coinfected patients. Data for migrants, prisoners, and sex workers are largely lacking as well as data on burden of disease from chronic viral hepatitis in the general population.
conclusionsWe identified data sources, their limitations, and methods for construction for all selected indicators. The next step is to convert the ideas developed into concrete projects with individual stakeholders.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.