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Elife. 2018 Dec 18;7. pii: e40977. doi: 10.7554/eLife.40977.

Inference and control of the nosocomial transmission of methicillin-resistant Staphylococcus aureus.

Author information

1
Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, United States.
2
Levich Institute and Physics Department, City College of New York, New York, United States.
3
Department of Sociology, Stockholm University, Stockholm, Sweden.

Abstract

Methicillin-resistant Staphylococcus aureus (MRSA) is a continued threat to human health in both community and healthcare settings. In hospitals, control efforts would benefit from accurate estimation of asymptomatic colonization and infection importation rates from the community. However, developing such estimates remains challenging due to limited observation of colonization and complicated transmission dynamics within hospitals and the community. Here, we develop an inference framework that can estimate these key quantities by combining statistical filtering techniques, an agent-based model, and real-world patient-to-patient contact networks, and use this framework to infer nosocomial transmission and infection importation over an outbreak spanning 6 years in 66 Swedish hospitals. In particular, we identify a small number of patients with disproportionately high risk of colonization. In retrospective control experiments, interventions targeted to these individuals yield a substantial improvement over heuristic strategies informed by number of contacts, length of stay and contact tracing.

KEYWORDS:

antibiotic-resistant pathogens; antimicrobial-resistant bacteria; computational biology; epidemiology; global health; methicillin-resistant Staphylococcus aureus; systems biology

PMID:
30560786
PMCID:
PMC6298769
DOI:
10.7554/eLife.40977
[Indexed for MEDLINE]
Free PMC Article

Conflict of interest statement

SP, FM, FL, HM No competing interests declared, JS Discloses partial ownership of SK Analytics.

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