A digital twin for Escherichia coli K1 neonatal meningitis
Year: 2026
Type: article
Abstract: K1 infection in neonates that integrates clinical, microbiological, physiological and molecular data within a continuously adaptive computational model. This twin would simulate bloodstream invasion, blood-brain barrier traversal and central nervous system inflammation in real time, enabling dynamic prediction of disease and optimization of antibiotic regimens. The framework is intended as a technical resource for clinicians and modellers working in neonatal infectious disease. A digital twin may advance neonatal infectious disease management, i.e. transforming empirical treatment into evidence-based, patient-specific precision care while providing new mechanistic insights into host-pathogen interactions.
Source: Journal of Medical Microbiology
DOI: 10.1099/jmm.0.002143
Authors: Ruqaiyyah Siddiqui, Naveed Ahmed Khan
Institutions: Heriot-Watt University, Istinye University, University of Derby
Language: English
Subfield: Endocrinology
Domain: Life Sciences
Open Access status: hybrid
OpenAlex ID: W7136132521