{"doi":"10.1093/ije/dyaf183","title":"Data Resource Profile: Global Trachoma Serology Data Repository","abstract":"Trachoma, a neglected tropical disease, is caused by repeated infection with the bacterium Chlamydia trachomatis (Ct) and is the most common infectious cause of blindness [1].Trachoma is targeted for global elimination as a public health problem by the year 2030; by 19 May 2025, 23 countries had been validated by the World Health Organization (WHO) as having eliminated trachoma as a public health problem [2].Surveillance of trachoma has traditionally relied on measurement of the clinical signs trachomatous inflammation-follicular (TF) and trachomatous trichiasis (TT) [3].Country health ministries are encouraged to share point prevalence data of TF and TT with the open-access Trachoma Atlas (https://www.trachomaatlas.org/)and, for countries in the WHO's Africa region, the ESPEN (Expanded Special Project for Elimination of Neglected Tropical Diseases) portal (https://espen.afro.who.int/)[4].This is one example of trachoma prevalence data sharing.At low levels of transmission and after antibiotic mass drug administration, TF is an imperfect marker of Ct transmission.Serological testing-the detection of specific antibodies in blood-is an approach that is under consideration to monitor programmatic recrudescence (the return of active trachoma infection), including in post-validation surveillance.Serology is central to pathogen surveillance and the inference of infection history [5] and, in trachoma, monitoring transmission by incorporating dried blood samples into standard trachoma surveys has proven useful in supporting programs as populations approach elimination [6][7][8][9][10].We set out to map the trajectory of trachoma to elimination through the analysis of population-level antibody Key Features The Global Trachoma Serology Data Repository includes harmonized survey data with individual-level data on immunoglobulin G (IgG) antibodies to Pgp3 and CT694 Chlamydia trachomatis antigens, created to support operational research on the use of serosurveillance for the trachoma elimination endgame. The repository is unique in its scale: >60 000 anonymized individual records collected from children (1-9 years old) in 48 surveys in 15 countries, between 2012 and 2023, and across a range of trachoma endemicity from high-transmission settings to post-elimination. Featured variables include age, year of survey, geography (country, region, and/or district), and whether or not antibiotic mass drug administration was done prior to the survey.Individual-level records are linked to their sampling cluster, which is fundamental for population-level analyses. The repository also contains accompanying data for clinical signs of trachoma and nucleic acid amplification test-based measures of ocular C. trachomatis infection, which, together with IgG measurements, enable a more comprehensive understanding of trachoma epidemiology.","journal":"International Journal of Epidemiology","year":2025,"id":529384,"datarank":0.16479184330021646,"base_score":1.0986122886681096,"endowment":1.0986122886681096,"self_citation_contribution":0.16479184330021646,"citation_network_contribution":0.0,"self_endowment_contribution":0.16479184330021646,"citer_contribution":0.0,"corpus_percentile":29.844511487584125,"corpus_rank":8690,"citation_count":2,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":true,"is_dataset_confidence":0.9334,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":54.1667,"fair_percentile":68.66401712014674,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1326904,"name":"Pearl Anne Ante-Testard","orcid":"0000-0002-3416-0817","position":1,"is_corresponding":false},{"id":1408658,"name":"Julianna Colado","orcid":null,"position":2,"is_corresponding":false},{"id":392041,"name":"Scott D. 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Release the data at publication with no embargo, no registration wall, and no approval step — NIH's zero-embargo public- access rule (NOT-OD-25-101) has already made 'available at publication' the federal baseline for the article; the data should not lag behind it. For clinical / human-subjects data, deposit in dbGaP or the European Genome-phenome Archive (EGA).","anchors":["yes","partial","no"],"verdict":"partial","current":0.5,"evidence":"All datasets are freely accessible for download through the Open Science Framework at https://osf.io/vj8ts/ (current version: 4) and Dryad (https://datadryad.org) with the digital object identifier (DOI) https://doi.org/10.5061/dryad.5qfttdzhx.","why":"The access route is given with no stated precondition; the data are stated to be freely accessible now. [downgraded to 'partial' — no verifiable quote from the paper] [majority verdict 'partial' (3/5 passes agreed)]","gain":8.33,"priority":"essential","scored":true},{"key":"x_code_availability","dimension":"R","label":"Analysis code available","action":"Publish the analysis code in a public forge, archive a tagged release with a DOI (Zenodo/Software Heritage), and cite that DOI in the paper. NIH DMS Element 2 asks for the tools and code, not only the data — and 'available on request' is not a locator. Archive the analysis code in a versioned repository (GitHub + a Zenodo release DOI).","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"No code locator is provided; the study's own code is not mentioned.","gain":8.33,"priority":"important","scored":true},{"key":"f_dataset_cited","dimension":"F","label":"Dataset formally cited","action":"Cite the dataset in the reference list like a publication — creator, year, title, repository, DOI/accession — and cite it in-text where it is used. Only a reference- list entry is machine-readable to Crossref/DataCite, and only a citation lets the data earn credit. Cite the clinical / human-subjects repository accession (e.g. from dbGaP or the European Genome-phenome Archive (EGA)) in the reference list.","anchors":["yes","partial","no"],"verdict":"partial","current":0.5,"evidence":"All datasets are freely accessible at https://doi.org/10.5061/dryad.5qfttdzhx","why":"The dataset's DOI appears only in the body text, not in the reference list. [majority verdict 'partial' (4/5 passes agreed)]","gain":4.17,"priority":"important","scored":true},{"key":"f_data_availability_statement","dimension":"F","label":"Data-availability statement","action":"Replace the statement with the repository template: name the repository and give the accession or DOI (Colavizza category 3). This is the only DAS class associated with a measured citation advantage; 'available on reasonable request' and 'within the article' are not.","anchors":["yes","partial","no"],"verdict":"partial","current":0.5,"evidence":"All datasets are freely accessible for download through the Open Science Framework at https://osf.io/vj8ts/ (current version: 4) and Dryad (https://datadryad.org) with the digital object identifier (DOI) https://doi.org/10.5061/dryad.5qfttdzhx.","why":"The data-availability statement points to a repository record with a DOI and access link. [downgraded to 'partial' — no verifiable quote from the paper] [majority verdict 'partial' (3/5 passes agreed)]","gain":0.0,"priority":"essential","scored":false},{"key":"i_community_standard_vocabulary","dimension":"I","label":"Community standard / vocabulary","action":"Adopt and NAME your domain's data standard — the minimum-information checklist, metadata schema, or ontology your community uses (MIAME/MINSEQE, ISA-Tab, BIDS, an OBO ontology, HL7 FHIR/OMOP) — and say which one you followed. A reporting checklist standardises your paper; it does nothing for your data. In clinical / human-subjects, describe the data with OMOP CDM, CDISC SDTM or HL7 FHIR.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"No community data or metadata standard (e.g., MIAME, ISA-Tab, ontology) is named for the data.","gain":0.0,"priority":"important","scored":false},{"key":"r_provenance_methods","dimension":"R","label":"Provenance of the data","action":"Name the instruments, kits, and software — with versions — that produced the data, not just the verbs. 'Reads were aligned' is not provenance; 'aligned with STAR v2.7.9a to GRCh38' is, because someone else can rerun it.","anchors":["yes","partial","no"],"verdict":"partial","current":0.5,"evidence":"Details of the data capture, serologic testing, polymerase chain reaction (PCR) testing, and clinical exam are published independently for each survey and also in the Supplementary material","why":"The production description is generic, not naming specific instruments, kits, or software versions. [majority verdict 'partial' (3/5 passes agreed)]","gain":0.0,"priority":"important","scored":false},{"key":"a_controlled_access_for_sensitive","dimension":"A","label":"Gatekeeper for sensitive data","action":"Route sensitive data through an institutional gatekeeper — deposit in a controlled- access repository (dbGaP, EGA) with a Data Access Committee and a published DUA — rather than through the corresponding author's inbox. An author-gated dataset dies with the author's email address, and 'on reasonable request' has been shown repeatedly not to yield data. For sensitive/human clinical / human-subjects data, use a controlled-access repository such as dbGaP or EGA.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"The data are de-identified and publicly accessible, so no gatekeeper is needed and none is named.","gain":0.0,"priority":"useful","scored":false},{"key":"i_qualified_references","dimension":"I","label":"Identifiers for the resources the data depend on","action":"Cite by identifier every resource the data depend on — the source datasets' accessions, the reference build (GRCh38 / GCA_000001405.28), the cohort application number, the code DOI — and register those relations on the dataset record (IsDerivedFrom, IsSupplementTo). A name is not a link: it cannot be resolved, versioned, or followed by a machine.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":"Each contributing study/survey has an associated 'PMID' value that references the original publication PubMed ID","why":"The paper includes PubMed IDs (PMIDs) for the source studies, which are identifiers for external resources (publications) that the data derive from. [downgraded to 'no' — no verifiable quote from the paper] [majority verdict 'no' (3/5 passes agreed)]","gain":0.0,"priority":"useful","scored":false},{"key":"a_timeline_retention","dimension":"A","label":"Availability timing & retention","action":"State when the data become available AND how long they will be retained — cite the repository's preservation policy. NIH DMS Element 4 asks for both; most papers give neither.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":"All datasets are freely accessible for download through the Open Science Framework at https://osf.io/vj8ts/ (current version: 4) and Dryad (https://datadryad.org) with the digital object identifier (DOI) https://doi.org/10.5061/dryad.5qfttdzhx.","why":"The paper states the data are currently available but makes no commitment to persistence or retention period. [downgraded to 'no' — no verifiable quote from the paper] [majority verdict 'no' (3/5 passes agreed)]","gain":0.0,"priority":"useful","scored":false}],"suggestions":["Attach a standard, machine-readable open licence to the deposit — CC0 or CC BY, which is what Horizon Europe and most funders expect — and print the licence identifier in the paper. 'Free to use' is not a licence: it grants nothing a reuser's institution can rely on.","Deposit the data in a repository registered in re3data/FAIRsharing (a domain repository such as GEO, SRA, dbGaP, PRIDE, or a generalist such as Zenodo, Dryad, Dataverse) and name it explicitly in the paper. A lab website is not an archive: it has no retention commitment and no accession. For clinical / human-subjects data, deposit in dbGaP or the European Genome-phenome Archive (EGA).","Remove the precondition or justify it. Release the data at publication with no embargo, no registration wall, and no approval step — NIH's zero-embargo public- access rule (NOT-OD-25-101) has already made 'available at publication' the federal baseline for the article; the data should not lag behind it. For clinical / human-subjects data, deposit in dbGaP or the European Genome-phenome Archive (EGA).","Publish the analysis code in a public forge, archive a tagged release with a DOI (Zenodo/Software Heritage), and cite that DOI in the paper. NIH DMS Element 2 asks for the tools and code, not only the data — and 'available on request' is not a locator. Archive the analysis code in a versioned repository (GitHub + a Zenodo release DOI).","Cite the dataset in the reference list like a publication — creator, year, title, repository, DOI/accession — and cite it in-text where it is used. Only a reference- list entry is machine-readable to Crossref/DataCite, and only a citation lets the data earn credit. Cite the clinical / human-subjects repository accession (e.g. from dbGaP or the European Genome-phenome Archive (EGA)) in the reference list."],"model":"deepseek/deepseek-v4-flash","agent_version":"fair_agent_v8","fulltext_source":"epmc_xml"},"fair_model":"deepseek/deepseek-v4-flash","fair_agent_version":"fair_agent_v8","fair_fulltext_source":"epmc_xml","fair_has_llm":true,"fair_computed_at":"2026-07-20T13:31:24.961287Z","clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}