Evidence map›Paper›PMID 41859328›Full record

ArticleScience in One Health2026

Quantitative microbial risk assessment of extended-spectrum β-lactamase-producing

Nunzio Sarnino, Subhasish Basak, Lucie Collineau, Roswitha Merle

Abstract read
In one paragraph

Article in Science in One 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.

Nunzio SarninoFreie Universität Berlin, Institute of Veterinary Epidemiology and Biostatistics, Veterinary Centre for Resistance Research Berlin, Germany.
Subhasish BasakUniversity of Lyon - French Agency for Food, Environmental and Occupational Health and Safety (ANSES), Epidemiology and Surveillance Support Unit, Lyon, France.
Lucie CollineauUniversity of Lyon - French Agency for Food, Environmental and Occupational Health and Safety (ANSES), Epidemiology and Surveillance Support Unit, Lyon, France.
Roswitha MerleFreie Universität Berlin, Institute of Veterinary Epidemiology and Biostatistics, Veterinary Centre for Resistance Research Berlin, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Extended-spectrum β-lactamase-producing Methods: A stochastic farm module simulated broiler colonization over a 36-day cycle and generated end-cycle litter loads. Field modules represented first-order decay, partitioning, and runoff to rivers; irrigation transfer yielded lettuce contamination for a 100 g serving. We estimated exposure, mapped gastrointestinal colonization to urinary tract infection (UTI) via conditional probabilities, and expressed the burden as disability-adjusted life years (DALYs) per serving. Global sensitivity analyses identified main exposure drivers. Environmental time was indexed as days since litter application and the planting interval denoted days from litter application to planting. Results: The farm model produced mean end-cycle litter of 1.6 × 10 Conclusions: Predicted health burdens decreased markedly with consumer washing and longer intervals between litter application and lettuce planting. Residual contamination persists, indicating value in evaluating the effectiveness of manure treatments and irrigation-water quality interventions on reducing environmental loads and human risk.

Indexed as

Broiler productionEnvironmental transmission pathwaysExtended-spectrum β-lactamase-producing Escherichia coliHuman exposure assessmentQuantitative microbial risk assessment

Identifiers

PMID41859328
PMCPMC12996673

What Socratic 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 Socratic graph.