A unified stochastic modeling framework for the spread of nosocomial infections
Over the last years, a number of stochastic models have been proposed for analysing the spread of nosocomial infections in hospital settings. These models often account for a number of factors governing the spread dynamics: spontaneous patient colonization, patient-staff contamination/colonization,...
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| Format: | Article |
| Language: | English English |
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Royal Society
2018
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| Online Access: | https://eprints.nottingham.ac.uk/51819/ |
| _version_ | 1848798581158313984 |
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| author | López-García, Martín Kypraios, Theodore |
| author_facet | López-García, Martín Kypraios, Theodore |
| author_sort | López-García, Martín |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | Over the last years, a number of stochastic models have been proposed for analysing the spread of nosocomial infections in hospital settings. These models often account for a number of factors governing the spread dynamics: spontaneous patient colonization, patient-staff contamination/colonization, environmental contamination, patient cohorting, or health-care workers (HCWs) hand-washing compliance levels. For each model, tailor-designed methods are implemented in order to analyse the dynamics of the nosocomial outbreak, usually by means of studying quantities of interest such as the reproduction number of each agent in the hospital ward, which is usually computed by means of stochastic simulations or deterministic approximations. In this work, we propose a highly versatile stochastic modelling framework that can account for all these factors simultaneously, and which allows for the exact analysis of the reproduction number of each agent at the hospital ward during a nosocomial outbreak. By means of five representative case studies, we show how this unified modelling framework comprehends, as particular cases, many of the existing models in the literature. We implement various numerical studies via which we: i) highlight the importance of maintaining high hand-hygiene compliance levels by HCWs, ii) support infection control strategies including to improve environmental cleaning during an outbreak, and iii) show the potential of some HCWs to act as super-spreaders during nosocomial outbreaks. |
| first_indexed | 2025-11-14T20:22:03Z |
| format | Article |
| id | nottingham-51819 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| language | English English |
| last_indexed | 2025-11-14T20:22:03Z |
| publishDate | 2018 |
| publisher | Royal Society |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-518192018-06-26T12:44:41Z https://eprints.nottingham.ac.uk/51819/ A unified stochastic modeling framework for the spread of nosocomial infections López-García, Martín Kypraios, Theodore Over the last years, a number of stochastic models have been proposed for analysing the spread of nosocomial infections in hospital settings. These models often account for a number of factors governing the spread dynamics: spontaneous patient colonization, patient-staff contamination/colonization, environmental contamination, patient cohorting, or health-care workers (HCWs) hand-washing compliance levels. For each model, tailor-designed methods are implemented in order to analyse the dynamics of the nosocomial outbreak, usually by means of studying quantities of interest such as the reproduction number of each agent in the hospital ward, which is usually computed by means of stochastic simulations or deterministic approximations. In this work, we propose a highly versatile stochastic modelling framework that can account for all these factors simultaneously, and which allows for the exact analysis of the reproduction number of each agent at the hospital ward during a nosocomial outbreak. By means of five representative case studies, we show how this unified modelling framework comprehends, as particular cases, many of the existing models in the literature. We implement various numerical studies via which we: i) highlight the importance of maintaining high hand-hygiene compliance levels by HCWs, ii) support infection control strategies including to improve environmental cleaning during an outbreak, and iii) show the potential of some HCWs to act as super-spreaders during nosocomial outbreaks. Royal Society 2018-06-13 Article PeerReviewed application/pdf en cc_by https://eprints.nottingham.ac.uk/51819/1/UnifiedStochasticNosocomial_LopezGarcia_Kypraios_Revised_May2018.pdf application/pdf en cc_by https://eprints.nottingham.ac.uk/51819/2/SupplementaryMaterial_Revised_May2018.pdf López-García, Martín and Kypraios, Theodore (2018) A unified stochastic modeling framework for the spread of nosocomial infections. Interface, 15 (143). ISSN 1742-5662 Hospital-acquired or nosocomial infections; Antibiotic resistant bacteria; Infection control; Stochastic model; Markov chain; Reproduction number http://rsif.royalsocietypublishing.org/content/15/143/20180060 doi:10.1098/rsif.2018.0060 doi:10.1098/rsif.2018.0060 |
| spellingShingle | Hospital-acquired or nosocomial infections; Antibiotic resistant bacteria; Infection control; Stochastic model; Markov chain; Reproduction number López-García, Martín Kypraios, Theodore A unified stochastic modeling framework for the spread of nosocomial infections |
| title | A unified stochastic modeling framework for the spread of nosocomial infections |
| title_full | A unified stochastic modeling framework for the spread of nosocomial infections |
| title_fullStr | A unified stochastic modeling framework for the spread of nosocomial infections |
| title_full_unstemmed | A unified stochastic modeling framework for the spread of nosocomial infections |
| title_short | A unified stochastic modeling framework for the spread of nosocomial infections |
| title_sort | unified stochastic modeling framework for the spread of nosocomial infections |
| topic | Hospital-acquired or nosocomial infections; Antibiotic resistant bacteria; Infection control; Stochastic model; Markov chain; Reproduction number |
| url | https://eprints.nottingham.ac.uk/51819/ https://eprints.nottingham.ac.uk/51819/ https://eprints.nottingham.ac.uk/51819/ |