Future planned updates include a) incorporation and filtering of additional metadata (e.g. isolate source), b) adding the ability to display data from bespoke genome collections (including user-defined) and c) extending to additional pathogens/vaccine targets.

vaccines.watch currently displays data for >100k high-quality genomes with geotemporal sampling information (post-2010), but we demonstrate that substantial biases and geographic gaps remain in the coverage of available genomes.

With analytics powered by Pathogenwatch (pathogen.watch), the platform uses the same “always-on” pipeline as the sister tool, amr.watch (amr.watch), with new genomes assembled, analysed and incorporated on an ongoing basis (every 4h) as public data are newly deposited.

The interactive interface enables users to assess vaccine target types (e.g. serotypes) within a broader population context by enabling assessment of their relationships with associated variant types (e.g. STs) and AMR markers, and within the context of existing pneumococcal vaccine formulations.

We’ve initially focused on showing data for existing/prospective multivalent polysaccharide-based vaccines for Streptococcus pneumoniae, Klebsiella pneumoniae (and related species) and Acinetobacter baumannii.

As global representativeness of data grows from increased genomic surveillance, we have designed vaccines.watch to support different stages of the vaccine pipeline, although caution in interpretation is currently important due to data representativeness (see below).

Pleased to share our latest preprint describing vaccines.watch (vaccines.watch), an interactive platform enabling exploration of vaccine target diversity from global genome data: www.biorxiv.org/content/10.1...

By combining survey data with additional public data, we also found substantial global spread of high-risk E. coli clones (e.g. ST167) with NDM-5 and other carbapenemases. We found many introductions of these clones into European hospitals in 2019, albeit with limited onward nosocomial transmission.

Our findings suggest that the situation with carbapenem-resistant K. pneumoniae has continued to worsen and that control measures have not been able to interrupt transmission of high-risk lineages circulating within European hospital networks.

Special thanks also to the project leads and collaborators @ecdc.europa.eu and Public Health Agency of Sweden, especially Anke Kohlenberg, Alma Brolund and Inga Froding, with whom it has been a pleasure to work with and learn from over the many years spanning the project.

The work comes together from the valiant efforts of all participating hospitals and national reference laboratories, forming the EURGen-Net CCRE Survey Working Group, who were able to continue with the data collection even despite onset of the COVID-19 pandemic shortly after the survey period.

The manuscripts, which follow up on the 2013-14 EuSCAPE survey, describe the occurrence and spread of carbapenem-resistant K. pneumoniae and E. coli using epidemiological, microbiological and WGS data obtained for isolates from >300 hospitals.

We’re pleased to share two new preprints with results from a structured survey of carbapenem- and/or colistin-resistant Enterobacterales (CCRE), conducted in 37 European countries in 2019.
E. coli: papers.ssrn.com/sol3/papers....
K. pneumoniae: papers.ssrn.com/sol3/papers....

amr.watch can be used to assess representation of geographic regions, e.g. with countries here in white currently lacking any public genomes. See more at amr.watch/all (6/6)

Huge disparity in genomic data. We support all efforts to increase the genomic surveillance of pathogens on a global scale as dynamics differ locally - what happens in one place does not translate to another and high-risk clones can emerge anywhere. (5/6)

Always on: all QC-d genomes with geotemporal metadata are ingested from archives, analysed in pathogen.watch and results visualised in amr.watch. Data are extracted and updated every 4h, with observed trends thus only delayed by time to genome deposition. More on filtering: amr.watch/summary (4/6)

We show disparities between high- and low-income settings, indicate vast gaps in our knowledge globally and highlight the need for ongoing, structured surveillance combined with timely data deposition (including metadata) to support public health. (3/6)

Supporting all WHO priority pathogens (2017), amr.watch summarises the geographic and temporal distribution of genotypic variants (e.g. STs) in the context of AMR to aid monitoring and prioritisation efforts. (2/6)

Our latest preprint is out describing amr.watch - a platform for monitoring AMR trends from global genomics data: www.biorxiv.org/content/10.1... (1/6)

We’ve just released a public Pathogenwatch collection of the MRSN Diversity Panel comprising 100 diverse K. pneumoniae clinical isolates: pathogen.watch/collection/8... #KlebClub

Hi Bluesky! We’re looking forward to engaging with the community and our users on here. Follow this account for updates on the Pathogenwatch platform (pathogen.watch), as well as our sister tools @microreact.bsky.social and @amrwatch.bsky.social developed by @thecgps.bsky.social