Evidence map›Paper›PMID 42698935›Full record

ArticleFrontiers in public health2026

Federated analytics for non-communicable disease surveillance in the European health data space: a scoping review and conceptual framework.

Fabrizio Carinci, Stephen Fava, Iztok Štotl, Nicholas Nicholson

Abstract readScoping Review
In one paragraph

Article in Frontiers in public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Fabrizio CarinciUnicamillus International Medical University, Rome, Italy.
Stephen FavaDepartment of Medicine, Mater Dei Hospital of Malta, Msida, Malta.
Iztok ŠtotlDepartment of Endocrinology, Diabetes and Metabolic Diseases, University Medical Center Ljubljana, Ljubljana, Slovenia.
Nicholas NicholsonJoint Research Center (JRC), European Commission, Ispra, Lombardy, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The growing burden of non-communicable diseases (NCDs) in Europe has intensified the need for timely, comparable, and policy-relevant health indicators derived from increasingly heterogeneous health data ecosystems. The European Health Data Space (EHDS) represents a major policy initiative to facilitate the secondary use of health data while preserving privacy, security, and national data sovereignty. In this context, federated analytics can foster international comparisons without requiring the transfer of person-level data. Objectives: This scoping review aimed to map federated analytical approaches relevant to the production of NCD indicators within the EHDS and to develop a conceptual framework linking distributed statistical methods, privacy-preserving infrastructures, and policy-oriented surveillance requirements. Materials and methods: A scoping review was conducted following the PRISMA Extension for Scoping Reviews. Searches were structured into three complementary conceptual domains: (a) federated analytical approaches, (b) distributed statistical inference methods, and (c) governance and health-data infrastructures relevant to the EHDS. Searches were performed in PubMed, Scopus, and IEEE Xplore, for studies published between 2010-26. Records were exported with abstracts and full bibliographic metadata. Deduplication and metadata-aware merging were conducted across databases using DOI and normalized-title matching. Results: We retrieved a total of 2,362 records, of which 1,285 were unique records and 104 were finally retained. The literature revealed a heterogeneous but rapidly expanding ecosystem of distributed analytical approaches. We identified three major domains: (1) distributed regression; (2) federated or distributed analytical infrastructures; and (3) privacy-preserving federated epidemiological analysis. Discussion: An increasing range of solutions for federated analytics is available for policy-grade NCD indicators. Longitudinal and survival models remain methodologically complex because of covariance structures and globally coupled risk sets. A modular approach is needed to incorporate public-health intelligence and a dynamic set of interoperable tools in the EHDS, with the active support of a decentralized network of active stakeholders. Conclusion: Federated analytics is shifting the paradigm from centralized data pooling to computation-to-data architectures. The successful implementation of NCD surveillance in the EHDS require integrating statistics with legal, IT, policy and governance mechanisms. The review outlined a conceptual framework that can couple technical innovation with the best architecture for public-health knowledge production.

Indexed as

Noncommunicable DiseasesPopulation SurveillanceEuropeFederated LearningHumansdistributed regressiondistributed statistical inferenceEHDSepidemiologyfederated analyticsNCD surveillanceobservational health dataprivacy-preserving analytics

Identifiers

PMID42698935
PMCPMC13543158

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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 Socratic graph.