ReviewBundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz2023
[Establishment of genomic pathogen surveillance to strengthen pandemic preparedness and infection prevention in Germany].
Review in Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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
4 citing papers in PubMed.
- Response: Use of integrated genomic surveillance by local public health authorities: Recommendations based on a mixed-methods study of current adoption, applications and success factors, Germany, 2023.Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin · 2025Article
- Responsive population-based cohorts as platforms for characterising pathogen- and population-level infection dynamics for epidemic prevention, preparedness and response.Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin · 2025Article
- External quality assessment of molecular detection and variant typing of SARS-CoV-2 in European expert laboratories in 2023.Journal of clinical microbiology · 2025Article
- An appeal for strengthening genomic pathogen surveillance to improve pandemic preparedness and infection prevention: the German perspective.Infection · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
22 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The SARS-CoV‑2 pandemic has shown a deficit of essential epidemiological infrastructure, especially with regard to genomic pathogen surveillance in Germany. In order to prepare for future pandemics, the authors consider it urgently necessary to remedy this existing deficit by establishing an efficient infrastructure for genomic pathogen surveillance. Such a network can build on structures, processes, and interactions that have already been initiated regionally and further optimize them. It will be able to respond to current and future challenges with a high degree of adaptability.The aim of this paper is to address the urgency and to outline proposed measures for establishing an efficient, adaptable, and responsive genomic pathogen surveillance network, taking into account external framework conditions and internal standards. The proposed measures are based on global and country-specific best practices and strategy papers. Specific next steps to achieve an integrated genomic pathogen surveillance include linking epidemiological data with pathogen genomic data; sharing and coordinating existing resources; making surveillance data available to relevant decision-makers, the public health service, and the scientific community; and engaging all stakeholders. The establishment of a genomic pathogen surveillance network is essential for the continuous, stable, active surveillance of the infection situation in Germany, both during pandemic phases and beyond.
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.