Evidence map›Paper›PMID 39993020›Full record

ArticlePLoS computational biology2025

An agent-based model to simulate the transmission dynamics of bloodborne pathogens within hospitals.

Paul Henriot, Mohamed El-Kassas, Wagida Anwar, Samia A Girgis, Maha El Gaafary, Kévin Jean, Laura Temime

Abstract read
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Article in PLoS computational biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Paul HenriotLaboratoire Modélisation, Épidémiologie Et Surveillance Des Risques Sanitaires, Conservatoire national des arts et métiers (CNAM), Paris, France.ORCID 0000-0002-9410-0867
Mohamed El-KassasEndemic Medicine Department, Faculty of Medicine, Helwan University, Cairo, Egypt.
Wagida AnwarDepartment of Community, Environmental and Occupational Medicine, Faculty of Medicine, Ain Shams University, Cairo, Egypt.
Samia A GirgisDepartment of Clinical Pathology, Faculty of Medicine, Ain Shams University, Cairo, Egypt.
Maha El GaafaryDepartment of Community, Environmental and Occupational Medicine, Faculty of Medicine, Ain Shams University, Cairo, Egypt.
Kévin JeanLaboratoire Modélisation, Épidémiologie Et Surveillance Des Risques Sanitaires, Conservatoire national des arts et métiers (CNAM), Paris, France.ORCID 0000-0001-6462-7185
Laura TemimeLaboratoire Modélisation, Épidémiologie Et Surveillance Des Risques Sanitaires, Conservatoire national des arts et métiers (CNAM), Paris, France.ORCID 0000-0002-8850-5403

Funding

Agence Nationale de Recherches sur le Sida et les Hépatites Virales (ANRS)
6 · The paper itself

Abstract

Mathematical models are powerful tools to analyze pathogen spread and assess control strategies in healthcare settings. Nevertheless, available models focus on nosocomial transmission through direct contact or aerosols rather than through blood, even though bloodborne pathogens remain a significant source of iatrogenic infectious risk. Herein, we propose an agent-based SEI (Susceptible-Exposed-Infected) model to reproduce the transmission of bloodborne pathogens dynamically within hospitals. This model simulates the dynamics of patients between hospital wards, from admission to discharge, as well as the dynamics of the devices used during at-risk invasive procedures, considering that patient contamination occurs after exposure to a contaminated device. We first illustrate the use of this model through a case study on hepatitis C virus (HCV) in Egypt. Model parameters, such as HCV upon-admission prevalence and transition probabilities between wards or ward-specific probabilities of undergoing different invasive procedures, are informed with data collected in Ain Shams University Hospital in Cairo. Our results suggest a low risk of HCV acquisition for patients hospitalized in this university hospital. However, we show that in a low-resource hospital, frequent device shortages could lead to increased risk. We also find that systematically screening patients in a few selected high-risk wards could significantly reduce this risk. We then further explore potential model applications through a second illustrative case study based on HBV nosocomial transmission in Ethiopia. In the future, this model could be used to predict the potential burden of emerging bloodborne pathogens and help implement effective control strategies in various hospital contexts.

Indexed as

Blood-Borne InfectionsBlood-Borne PathogensCross InfectionModels, BiologicalComputational BiologyComputer SimulationEgyptHepacivirusHepatitis CHospitalsHumans

Identifiers

PMID39993020
PMCPMC11882061

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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.