Evidence map›Paper›PMID 42768357›Full record

ArticleBMC proceedings2026

Fostering cross-community collaboration to advance pandemic and epidemic intelligence.

Julia Fitzner, Barbara Tornimbene, Hugo Gruson, Adam Kucharski, Kevin J Olival, Chloe Rice, Lisa Waddell

Abstract read
In one paragraph

Article in BMC proceedings, 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

7 authors.

Julia FitznerWorld Health Organization (WHO), WHO Hub for Pandemic and Epidemic Intelligence, Berlin, Germany.
Barbara TornimbeneWorld Health Organization (WHO), WHO Hub for Pandemic and Epidemic Intelligence, Berlin, Germany. tornimbeneb@who.int.
Hugo GrusonData.Org, New York, NY, USA.
Adam KucharskiLondon School of Hygiene & Tropical Medicine, London, UK.
Kevin J OlivalEcoHealth Alliance, New York, NY, USA.
Chloe RiceWorld Health Organization (WHO), WHO Hub for Pandemic and Epidemic Intelligence, Berlin, Germany.
Lisa WaddellPublic Health Agency of Canada, Ottawa, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The twelfth session of the WHO Pandemic and Epidemic Intelligence Innovation Forum focused on how cross-community collaboration can accelerate progress in pandemic and epidemic intelligence. The session explored how the Collaboratory, a WHO digital initiative connecting diverse communities of practice, fosters co-creation, supports the development of collaborative analytical tools, and strengthens the translation of evidence-base into public health action. Through a combination of short presentations and a panel discussion, the session examined key Collaboratory initiatives, including the Global Repository of Epidemiological Parameters (grEPI), AI-enabled pipelines for evidence synthesis, the Epiverse toolkit for outbreak analysis, and semantic search tools to improve the discoverability of epidemiological resources. Discussions addressed challenges of integration into national public health systems, governance models, sustainability, capacity-building, AI reliability, and ethical use. Across the session a common message emerged: advancing epidemic intelligence requires not only new tools but also sustained collective action, trust, and shared ownership across sectors, disciplines, and regions.

Indexed as

Artificial intelligenceCo-creationCommunities of practiceCross-community collaborationEpidemic intelligencePandemic intelligencePublic health

Identifiers

PMID42768357
PMCPMC13591668

What OpenQuestion 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 OpenQuestion graph.