MATHEMATICAL SIMULATION OF NOSOCOMIAL INFECTION SPREAD AND THE ROLE OF NURSINGBASED INTERVENTIONS
Hospital-acquired infections (HAIs), or nosocomial infections, compromise patient safety and the provision of care worldwide. With their extensive patient contact, urses are key to HAIs transmission and prevention. This article employs a mathematical simulation of HAI dynamics for 60 days in a theo...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Institute of Mechanics of Continua and Mathematical Sciences
2025-06-01
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| Series: | Journal of Mechanics of Continua and Mathematical Sciences |
| Subjects: | |
| Online Access: | https://jmcms.s3.amazonaws.com/wp-content/uploads/2025/06/16154423/jmcms-2507012-Mathematical-Modeling-of-the-Spread-of-Hospital-SM-1.pdf |
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| Summary: | Hospital-acquired infections (HAIs), or nosocomial infections, compromise
patient safety and the provision of care worldwide. With their extensive patient contact, urses are key to HAIs transmission and prevention. This article employs a mathematical simulation of HAI dynamics for 60 days in a theoretical 1,000-person hospital ward using a modified Susceptible-Infected-Recovered (SIR) model, with and without nurse interventions such as hand hygiene, patient isolation, personal protective equipment (PPE) use, and environmental disinfection. Enhanced advancements, including the incorporation of genomic and epidemiological data, enhance the model's ability to track transmission clusters, particularly in the case of multidrug-resistant organisms (MDROs) such as MRSA (Illingworth et al., 2022). The simulation demonstrates that nurse interventions reduce infection rate by over 70%, retarding peak and lowering total cases (from ~830 to ~240). Findings are congruent with observations comparing interventions such as chlorhexidine bathing (Climo et al., 2016). Through model assumptions, e.g., asymptomatic transmission, this article offers
a concrete basis for hospital decision-making, emphasizing evidence-based nursing and interprofessional infection control practices. |
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| ISSN: | 0973-8975 2454-7190 |