@article{Myall_A-2022_91453,
title = {Prediction of hospital-onset COVID-19 infections using dynamic networks of patient contact: an international retrospective cohort study},
author = {Myall, A. and Price, J. and Peach, R. and Abbas, M. and Mookerjee, S. and Zhu, N. and Ahmad, I. and Ming, D. and Ramzan, F. and Teixeira, D. and Graf, C. and Weiße, A. and Harbarth, S. and Holmes, A. and Barahona, M.},
month = {aug},
year = {2022},
abstract = {Background: Real-time prediction is key to prevention and control of infections associated with health-care settings. Contacts enable spread of many infections, yet most risk prediction frameworks fail to account for their dynamics. We developed, tested, and internationally validated a real-time machine-learning framework, incorporating dynamic patient-contact networks to predict hospital-onset COVID-19 infections (HOCIs) at the individual level.},
pages = {e573-e583},
volume = {4},
issue = {8},
journal = {The Lancet Digital Health},
publisher = {Elsevier},
url = {https://doi.org/10.1016/S2589-7500(22)00093-0},
}
