Sentence examples for exogenous transmission from inspiring English sources

The MRSA control strategy is predominantly based on distancing carriers from non-carriers to prevent exogenous transmission, and was, therefore, assumed not to change MSSA bacteremia rates.

By specifically accounting in our model for the routes by which active TB disease developed, we differentiate notifications due to recent exogenous transmission versus endogenous reactivation, with implications for control measures and trends in disease burden in the short- to medium-term future.

Rare cases of exogenous transmission have been described due to contaminated solutions and materials or transmission from healthcare workers to patients and from patients to patients [ 37, 38].

Species with low genetic variability that are more often associated with exogenous transmission could be less well adapted to human hosts, may predominantly undergo clonal reproduction, and might have recently diverged during their evolutionary histories [ 12, 58, 63].

34 The lack of association between procurement data and MSSA bacteraemia 28 29 33 could indicate that hand hygiene is less effective at interrupting endogenous transmission of infection (which is more likely for MSSA), than at interrupting the exogenous transmission (which in hospital settings is more likely to be associated with MRSA).

BAL: broncho-alveolar lavage; CDC Centers for Disease Control and Preventionn; EXIT: exogenous infection transmission; GER: gastro-oesophageal reflux; NNIS: National Nosocomial Infection Surveillance; VAP: ventilator-associated pneumonia.

The high incidence of Klebsiella and Acinetobacter (especially if multi-resistant organisms) implies exogenous infection transmission (EXIT) and/or late-onset VAP.

The separate pathways through RLTBI and LLTBI to, RIITB, RAITB, RINTB or RANTB allow us to quantify the number of active TB cases due to endogenous reactivation and exogenous recent transmission.

We performed Monte Carlo ensembles of stochastic dynamic simulations operating on the contact data, where the primary variables drawn from distributions were disease stage durations, exogenous infection event rates and the probability of transmission from infected endogenous contacts.

We analysed the response of our simulated infections to changing endogenous and exogenous infection pressure and the proximity threshold required for transmission to confirm that the simulation did not produce any significant artefacts.

Within a given scenario, stochastics associated with exogenous and endogenous infection transmission and duration of different phases in the natural history of infection induced variability in simulation output.