A Markov chain model to investigate the spread of antibiotic-resistant bacteria in hospitals
This paper proposes a Markov chain model to describe the spread of a single bacterial species in a hospital ward where patients may be free of bacteria or may carry bacterial strains that are either sensitive or resistant to antimicrobial agents. The aim is to determine the probability law of the ex...
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2023 |
| País: | España |
| Institución: | Universidad Complutense de Madrid (UCM) |
| Repositorio: | Docta Complutense |
| Idioma: | inglés |
| OAI Identifier: | oai:docta.ucm.es:20.500.14352/72422 |
| Acceso en línea: | https://hdl.handle.net/20.500.14352/72422 |
| Access Level: | acceso abierto |
| Palabra clave: | 519.217 Epidemic model Markov chain Quasi-birth-death process Reproduction number Investigación operativa (Matemáticas) Procesos estocásticos Biomatemáticas 1207 Investigación Operativa 1208.08 Procesos Estocásticos 2404 Biomatemáticas |
| Sumario: | This paper proposes a Markov chain model to describe the spread of a single bacterial species in a hospital ward where patients may be free of bacteria or may carry bacterial strains that are either sensitive or resistant to antimicrobial agents. The aim is to determine the probability law of the exact reproduction number Rexact,0 which is here defined as the random number of secondary infections generated by those patients who are accommodated in a predetermined bed before a patient who is free of bacteria is accommodated in this bed for the first time. Specifically, we decompose the exact reproduction number Rexact,0 into two contributions allowing us to distinguish between infections due to the sensitive and the resistant bacterial strains. Our methodology is mainly based on structured Markov chains and the use of related matrix-analytic methods. |
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