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Over the last decade, computational modeling has proved a useful tool to simulate the transmission dynamics of nosocomial pathogens and can be used to predict optimal control measures in healthcare settings. Nosocomial infections are a major public health issue especially since the increase of antimicrobial resistance. Here, we present CTCmodeler, a framework that incorporates an agent-based model to simulate pathogen transmission through inter-individual contact in a hospital setting. CTCmodeler uses real admission, swab and contact data to deduce its own parameters, simulate inter-individual pathogen transmission across hospital wards and produce weekly incidence estimates. Most previous hospital models have not accounted for individual heterogeneity of contact patterns. By contrast, CTCmodeler explicitly captures temporal heterogeneous individual contact dynamics by modelling close-proximity interactions over time. Here, we illustrate the use of CTCmodeler to simulate methicillin-resistant Staphylococcus aureus dissemination in a French long-term care hospital, using longitudinal data on sensor-recorded contacts and weekly swabs from the i-Bird study.

Original publication




Publication Date



11537 LNCS


477 - 487