  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.
