dc.contributorUniversidade Estadual Paulista (Unesp)
dc.contributorUniversity of Georgia
dc.date.accessioned2019-10-06T16:10:49Z
dc.date.accessioned2022-12-19T18:43:57Z
dc.date.available2019-10-06T16:10:49Z
dc.date.available2022-12-19T18:43:57Z
dc.date.created2019-10-06T16:10:49Z
dc.date.issued2019-03-01
dc.identifierEpidemics, v. 26, p. 104-115.
dc.identifier1878-0067
dc.identifier1755-4365
dc.identifierhttp://hdl.handle.net/11449/188520
dc.identifier10.1016/j.epidem.2018.11.001
dc.identifier2-s2.0-85058781109
dc.identifier2052749698204617
dc.identifier0000-0002-9404-6098
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/5369558
dc.description.abstractHealthcare-associated infections cause significant patient morbidity and mortality, and contribute to growing healthcare costs, whose effects may be felt most strongly in developing countries. Active surveillance systems, hospital staff compliance, including hand hygiene, and a rational use of antimicrobials are among the important measures to mitigate the spread of healthcare-associated infection within and between hospitals. Klebsiella pneumoniae is an important human pathogen that can spread in hospital settings, with some forms exhibiting drug resistance, including resistance to the carbapenem class of antibiotics, the drugs of last resort for such infections. Focusing on the role of patient movement within and between hospitals on the transmission and incidence of enterobacteria producing the K. pneumoniae Carbapenemase (KPC, an enzyme that inactivates several antimicrobials), we developed a metapopulation model where the connections among hospitals are made using a theoretical hospital network based on Brazilian hospital sizes and locations. The pathogen reproductive number, R 0 that measures the average number of new infections caused by a single infectious individual, was calculated in different scenarios defined by both the links between hospital environments (regular wards and intensive care units) and between different hospitals (patient transfer). Numerical simulation was used to illustrate the infection dynamics in this set of scenarios. The sensitivity of R 0 to model input parameters, such as hospital connectivity and patient-hospital staff contact rates was also established, highlighting the differential importance of factors amenable to change on pathogen transmission and control.
dc.languageeng
dc.relationEpidemics
dc.rightsAcesso aberto
dc.sourceScopus
dc.subjectBasic reproductive number
dc.subjectControl
dc.subjectDifferential equation
dc.subjectKlebsiella pneumoniae
dc.subjectNetwork
dc.subjectSensitivity analysis
dc.titleThe role of intra and inter-hospital patient transfer in the dissemination of heathcare-associated multidrug-resistant pathogens
dc.typeArtículos de revistas


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