Determining infectious cross-transmission events in healthcare settings involves manual surveillance of case clusters by infection control personnel, followed by strain typing of clinical/environmental isolates suspected in said clusters. Recent advances in genomic sequencing and cloud computing now allow for the rapid molecular typing of infecting isolates.

To facilitate rapid recognition of transmission clusters, we aimed to assess infection control surveillance using whole-genome sequencing (WGS) of microbial pathogens to identify cross-transmission events for epidemiologic review.

Clinical isolates of Staphylococcus aureus, Enterococcus faecium, Pseudomonas aeruginosa, and Klebsiella pneumoniae were obtained prospectively at an academic medical center, from September 1, 2016, to September 30, 2017. Isolate genomes were sequenced, followed by single-nucleotide variant analysis; a cloud-computing platform was used for whole-genome sequence analysis and cluster identification.

Most strains of the 4 studied pathogens were unrelated, and 34 potential transmission clusters were present. The characteristics of the potential clusters were complex and likely not identifiable by traditional surveillance alone. Notably, only 1 cluster had been suspected by routine manual surveillance.

Our work supports the assertion that integration of genomic and clinical epidemiologic data can augment infection control surveillance for both the identification of cross-transmission events and the inclusion of missed and exclusion of misidentified outbreaks (ie, false alarms). The integration of clinical data is essential to prioritize suspect clusters for investigation, and for existing infections, a timely review of both the clinical and WGS results can hold promise to reduce HAIs. A richer understanding of cross-transmission events within healthcare settings will require the expansion of current surveillance approaches.

The current study examined the pattern of neurocognitive impairments in a community-recruited sample of clinical high-risk (CHR) participants and established relationships with psychosocial functioning.

CHR-participants (n = 108), participants who did not fulfil CHR-criteria (CHR-negatives) (n = 42) as well as a group of healthy controls (HCs) (n = 55) were recruited. CHR-status was assessed using the Comprehensive Assessment of At-Risk Mental States (CAARMS) and the Schizophrenia Proneness Instrument, Adult Version (SPI-A). The Brief Assessment of Cognition in Schizophrenia Battery (BACS) as well as tests for emotion recognition, working memory and attention were administered. In addition, role and social functioning as well as premorbid adjustment were assessed.

CHR-participants were significantly impaired on the Symbol-Coding and Token-Motor task and showed a reduction in total BACS-scores. Moreover, CHR-participants were characterised by prolonged response times (RTs) in emotion recognition as well as by reductions in both social and role functioning, GAF and premorbid adjustments compared with HCs. Neurocognitive impairments in emotion recognition accuracy, emotion recognition RT, processing speed and motor speed were associated with several aspects of functioning explaining between 4% and 12% of the variance.

The current data obtained from a community sample of CHR-participants highlight the importance of dysfunctions in motor and processing speed and emotion recognition RT. Moreover, these deficits were found to be related to global, social and role functioning, suggesting that neurocognitive impairments are an important aspect of sub-threshold psychotic experiences and a possible target for therapeutic interventions.