Article

Predicting hospital-onset COVID-19 infections using dynamic networks of patient contacts: an observational study

2021-09-29

Abstract excerpt

<h4>ABSTRACT</h4> <h4>Background</h4> Real-time prediction is key to prevention and control of healthcare-associated infections. Contacts between individuals drive infections, yet most prediction frameworks fail to capture the dynamics of contact. We develop a real-time machine learning framework that incorporates dynamic patient contact networks to predict patient-level hospital-onset COVID-19 infections (HOCIs),...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: c3c76e5e-26f8-5cf4-baed-cdb70208b2f2
DOI: 10.1101/2021.09.28.21264240

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Predicting hospital-onset COVID-19 infections using dynamic networks of patient contacts: an observational studyDOI 10.1101/2021.09.28.21264240Read

Characterising contact in disease outbreaks via a network model of spatial-temporal proximitySemantic proximity Read

Early Prediction of COVID-19 Associated Hospitalization at the Time of CDC Contact Tracing using Machine Learning: Towards Pandemic PreparednessSemantic proximity Read

An algorithm to build synthetic temporal contact networks based on close-proximity interactions dataSemantic proximity Read

Contact Network Analysis of COVID-19 Delta variant Outbreak in Urban China ——Based on 2,050 Confirmed Cases in Xi'an, ChinaSemantic proximity Read

Prediction of COVID-19 infection risk using personal mobile location data onlySemantic proximity Read

Hospital vulnerability to spread of respiratory infections: close contact data collection and mathematical modellingSemantic proximity Read

Hospital vulnerability to spread of respiratory infections: close contact data collection and mathematical modellingSemantic proximity Read

Characterising within-hospital SARS-CoV-2 transmission events: a retrospective analysis integrating epidemiological and viral genomic data from a UK tertiary care setting across two pandemic wavesSemantic proximity Read

Uncovering COVID-19 Transmission Tree: Identifying Traced and Untraced Infections in an Infection NetworkSemantic proximity Read

Predicting COVID-19 related death using the OpenSAFELY platformSemantic proximity Read

Tracking COVID-19 in England and Wales: Insights from Virus Watch - a prospective community cohort studySemantic proximity Read

Contact network structure shaped pandemic transmission despite lockdownsSemantic proximity Read