Work

Identifying asymptomatic spreaders of antimicrobial-resistant pathogens in hospital settings

Year: 2021

Type: article

Abstract: Significance Healthcare-associated infections caused by antimicrobial-resistant agents are hard to eliminate in hospitals partly because of the existence of asymptomatic spreaders who unwittingly transmit these pathogens to others. In practice, identifying asymptomatic patients colonized with antimicrobial-resistant agents is challenging, as only a limited number of carriers are typically observed. Here, we develop an efficient, individual-level inference method capable of estimating the colonization probability for each individual in a hospital network. Using real-world patient-to-patient contact networks and sparse observations of colonization, the proposed method identifies carriers of methicillin-resistant Staphylococcus aureus , a prevalent antimicrobial-resistant pathogen, more accurately than competing approaches informed by hospitalization history and contact tracing. In in silica control experiments, the individual-level inference supports improved, targeted interventions against healthcare-associated infections.

Source: Proceedings of the National Academy of Sciences

DOI: 10.1073/pnas.2111190118

Authors: Sen Pei, Fredrik Liljeros, Jeffrey Shaman

Institutions: Columbia University, Stockholm University, Karolinska Institutet

Language: English

Topic: Infection Control in Healthcare

Subfield: Infectious Diseases

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: green

Funders: Centers for Disease Control and Prevention, National Institute of General Medical Sciences