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...

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Detalles Bibliográficos
Autores: Chalub, Fabio A.C.C., Gómez-Corral, Antonio, López-García, Martín, Palacios-Rodríguez, Fátima
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
Descripción
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.