Evidence map›Paper›PMID 42394636›Full record

ArticleEuro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin2026

Artificial intelligence (AI) in action: a cross-continental survey of AI adoption among field epidemiology fellows in Canada, the United States, and Europe, 2024.

Courtney R Smith, Natalie Girin, Kathleen Laberge, Seth Manthey, Pasha Marcynuk, Eric Pevzner, Adam Roth, Louis Wong

Abstract read
In one paragraph

Article in Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin, 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

8 authors.

Courtney R SmithCanadian Field Epidemiology Program, Public Health Agency of Canada; 100 Colonnade Road, Ottawa, Ontario, Canada.
Natalie GirinFellowship Programme Section, Surveillance Preparedness and Response, European Centre for Disease Prevention and Control, Stockholm, Sweden.
Kathleen LabergeCanadian Field Epidemiology Program, Public Health Agency of Canada; 100 Colonnade Road, Ottawa, Ontario, Canada.
Seth MantheyEpidemic Intelligence Service, Centers for Disease Control and Prevention; 1600 Clifton Road, Atlanta, Georgia, United States.
Pasha MarcynukCanadian Field Epidemiology Program, Public Health Agency of Canada; 100 Colonnade Road, Ottawa, Ontario, Canada.
Eric PevznerEpidemic Intelligence Service, Centers for Disease Control and Prevention; 1600 Clifton Road, Atlanta, Georgia, United States.
Adam RothFellowship Programme Section, Surveillance Preparedness and Response, European Centre for Disease Prevention and Control, Stockholm, Sweden.
Louis WongCanadian Field Epidemiology Program, Public Health Agency of Canada; 100 Colonnade Road, Ottawa, Ontario, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUNDTechnologies available for applied public health practice are rapidly evolving. Artificial intelligence (AI) tools have become more accessible, however, their utilisation by field epidemiologists has not been described.AIMWe explored AI use among Canadian, European, and United States (US) Field Epidemiology Training Program (FETP) fellows.METHODSFellows in the three programmes (n = 220) were invited to an online survey available from 25 November 2024 to 5 December 2024. Quantitative and qualitative data were collected concerning the AI platforms fellows used, AI applications, comfort level when applying AI, use frequency, impact on work, barriers, ethical concerns, AI policy/guideline availability, and AI training.RESULTSThere were 105 (48%) survey respondents: 13, 56 and 36 in the Canadian, US and European FETPs respectively. The proportion of respondents who reported applying AI for work was 66% (69/105) overall, and highest among respondents of the European programme (32/36). The most adopted platform was ChatGPT (60/69; 87%), and the most common application was analytical coding assistance (63/69; 91%). Among AI users, most felt somewhat comfortable (34/69; 49%) or comfortable (24/69; 35%) with AI and reported weekly (29/69; 42%) or daily (21/69; 30%) use. Generally, AI's reported impact was positive. Challenges included technical difficulties, accuracy concerns, bias introduction, uncertainty regarding permissible uses, and data privacy issues. Among respondents, 47% (49/105) affirmed having AI policies/guidelines in their institutions and 20% (21/105) had received AI training.CONCLUSIONTo further incorporate AI use among its fellows, FETPs should monitor AI's evolving role, and provide guidance and adapt curricula accordingly.

Indexed as

Artificial IntelligenceEpidemiologyPublic HealthCanadaEuropeHumansSurveys and QuestionnairesUnited StatesAIArtificial intelligencefield epidemiologyfield epidemiology training programs

Identifiers

PMID42394636
PMCPMC13332366

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.