Model-based methods for hospital infection prevention and control: potential and challenges

Jessica R. E. Bridgen; Chris Jewell; Joseph M. Lewis; Stacy Todd; Malcolm G. Semple; Nicholas Feasey; Jonathan M. Read

doi:10.1186/s44263-025-00229-8

Model-based methods for hospital infection prevention and control: potential and challenges

Jessica R. E. Bridgen^*, Chris Jewell, Joseph M. Lewis, Stacy Todd, Malcolm G. Semple, Nicholas Feasey, Jonathan M. Read

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

Abstract

Hospital-acquired infections remain a major challenge for ensuring patient safety. Model-based methods offer a pathway to proactive, data-driven infection control, supporting earlier decision-making and tailored control policies. We outline the potential of these approaches, the key methodological and implementation challenges, and the importance of co-creation for operational use.

Original language	English
Article number	111
Pages (from-to)	1-4
Number of pages	4
Journal	BMC Global and Public Health
Volume	3
DOIs	https://doi.org/10.1186/s44263-025-00229-8
Publication status	Published - 5 Dec 2025

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1186/s44263-025-00229-8Licence: CC BY

Bridgen-et-al-2025-Model-based-methods-BMCGlobal&PublicHealth-3-111-CCBY
Copyright © The Author(s) 2025. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
Final published version, 845 KBLicence: CC BY

Cite this

@article{805db0a3c1db40b3a5091b7662a9d299,

title = "Model-based methods for hospital infection prevention and control: potential and challenges",

abstract = "Hospital-acquired infections remain a major challenge for ensuring patient safety. Model-based methods offer a pathway to proactive, data-driven infection control, supporting earlier decision-making and tailored control policies. We outline the potential of these approaches, the key methodological and implementation challenges, and the importance of co-creation for operational use.",

author = "Bridgen, \{Jessica R. E.\} and Chris Jewell and Lewis, \{Joseph M.\} and Stacy Todd and Semple, \{Malcolm G.\} and Nicholas Feasey and Read, \{Jonathan M.\}",

note = "Funding: This work was supported by Research England under the Expanding Excellence in England (E3) funding stream, which was awarded to MARS: Mathematics for AI in Real-world Systems in the School of Mathematical Sciences at Lancaster University. The workshop was funded by the Data Science Institute, Lancaster University.",

year = "2025",

month = dec,

day = "5",

doi = "10.1186/s44263-025-00229-8",

language = "English",

volume = "3",

pages = "1--4",

journal = "BMC Global and Public Health",

issn = "2731-913X",

publisher = "Springer Nature",

}

TY - JOUR

T1 - Model-based methods for hospital infection prevention and control

T2 - potential and challenges

AU - Bridgen, Jessica R. E.

AU - Jewell, Chris

AU - Lewis, Joseph M.

AU - Todd, Stacy

AU - Semple, Malcolm G.

AU - Feasey, Nicholas

AU - Read, Jonathan M.

N1 - Funding: This work was supported by Research England under the Expanding Excellence in England (E3) funding stream, which was awarded to MARS: Mathematics for AI in Real-world Systems in the School of Mathematical Sciences at Lancaster University. The workshop was funded by the Data Science Institute, Lancaster University.

PY - 2025/12/5

Y1 - 2025/12/5

N2 - Hospital-acquired infections remain a major challenge for ensuring patient safety. Model-based methods offer a pathway to proactive, data-driven infection control, supporting earlier decision-making and tailored control policies. We outline the potential of these approaches, the key methodological and implementation challenges, and the importance of co-creation for operational use.

AB - Hospital-acquired infections remain a major challenge for ensuring patient safety. Model-based methods offer a pathway to proactive, data-driven infection control, supporting earlier decision-making and tailored control policies. We outline the potential of these approaches, the key methodological and implementation challenges, and the importance of co-creation for operational use.

U2 - 10.1186/s44263-025-00229-8

DO - 10.1186/s44263-025-00229-8

M3 - Article

SN - 2731-913X

VL - 3

SP - 1

EP - 4

JO - BMC Global and Public Health

JF - BMC Global and Public Health

M1 - 111

ER -

Model-based methods for hospital infection prevention and control: potential and challenges

Abstract

UN SDGs

Access to Document

Fingerprint

Cite this