Evidence map›Paper›PMID 42546042›Full record

ArticlePLoS computational biology2026

Accounting for the long-distance transmission route: An epidemiological model of airborne disease transmission in hospitals.

Olivier Gaufrès, Quentin J Leclerc, Julien Derdevet, George Shirreff, Solen Kernéis, Lulla Opatowski, Laura Temime, Maylis Layan

Abstract read
In one paragraph

Article in PLoS computational biology, 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.

Olivier GaufrèsPACRI unit, Institut Pasteur, Conservatoire national des arts et métiers, Paris, France.ORCID 0009-0008-3378-0070
Quentin J LeclercPACRI unit, Institut Pasteur, Conservatoire national des arts et métiers, Paris, France.
Julien DerdevetAssistance Publique - Hôpitaux de Paris (AP-HP), Paris, France.
George ShirreffPACRI unit, Institut Pasteur, Conservatoire national des arts et métiers, Paris, France.
Solen KernéisIAME, Université Paris Cité, Inserm, Paris, France.
Lulla OpatowskiEpidemiology and Modelling of Bacterial Escape to Antimicrobials (EMEA), Institut Pasteur, Université Paris Cité, Paris, France.
Laura TemimePACRI unit, Institut Pasteur, Conservatoire national des arts et métiers, Paris, France.ORCID 0000-0002-8850-5403
Maylis LayanPACRI unit, Institut Pasteur, Conservatoire national des arts et métiers, Paris, France.ORCID 0000-0003-3092-686X

Funding

Institut PasteurPfizer and Sanofi Pasteur
6 · The paper itself

Abstract

Nosocomial transmission of respiratory infections poses a major threat to patient safety, while also affecting healthcare workers' (HCW) health, generating substantial costs for hospitals. These infections spread through both close-proximity interactions at short distances, and via aerosols that remain suspended in the air, enabling long-range transmission within a room when a susceptible individual is at a distance from an infectious individual. The relative contribution of each transmission route is pathogen-dependent. However, models distinguishing them remain scarce, limiting the design of effective intervention strategies. Here, we propose a novel agent-based stochastic model of respiratory pathogen transmission in a hospital ward that integrates both transmission routes together with contact patterns and individual movements. After informing our model with real close-proximity interaction data collected in two French intensive care units, we simulate a range of combinations of short- and long-range transmission levels to investigate their differences. Selecting parameter values that keep overall ward transmission intensity stable across combinations, the model is used to further evaluate the impact of intervention strategies on incidence risk. We find that the predominance of one route over another has little effect on overall outbreak dynamics, though the impact across individuals varies markedly. Patients are mostly at risk of short-range transmission from HCWs, while HCWs are mostly affected by whichever route is predominant. This directly influences intervention effectiveness. Universal masking emerges as the most effective strategy, reducing both transmission routes. Its stringency can be relaxed with limited loss of effectiveness when combined with ventilation in relevant rooms. Importantly, interventions targeting HCWs, notably ventilation in rooms not accessible to patients, indirectly reduces incidence in patients, with a stronger effect when coupled with relaxed masking interventions. Finally, intervention ranking remains robust across parameter values, as confirmed by a sensitivity analysis. This new model highlights the importance of explicitly considering physical mechanisms of transmission, and the need for interventions that remain effective irrespective of pathogen characteristics and ward organization.

Indexed as

Air MicrobiologyCross InfectionEpidemiological ModelsModels, BiologicalRespiratory Tract InfectionsComputer SimulationDisease OutbreaksFranceHospitalsHumansStochastic Processes

Identifiers

PMID42546042
PMCPMC13460748

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LicenceCC BY
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Registered trials

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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.