Nosocomial infections have important consequences for patients and hospital staff: they worsen patient outcomes and their management stresses already overburdened health systems. Accurate judgements of whether an infection is nosocomial helps staff make appropriate choices to protect other patients within the hospital. Nosocomiality cannot be properly assessed without considering whether the infected patient came into contact with high risk potential infectors within the hospital. We developed a Bayesian model that integrates epidemiological, contact and pathogen genetic data to determine how likely an infection is to be nosocomial and the probability of given infection candidates being the source of the infection.
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