Background: Recent evidence suggests that less than one-quarter of patients with symptomatic nosocomial Clostridium difficile infections (CDI) are linked to other in-patients. However, this evidence was limited to one geographic area. We aimed to investigate the level of symptomatic CDI transmission in hospitals located across England from 2008 to 2012.
Methods: A generalized additive mixed-effects Poisson model was fitted to English hospital-surveillance data. After adjusting for seasonal fluctuations and between-hospital variation in reported CDI over time, possible clustering (transmission between symptomatic in-patients) of CDI cases was identified. We hypothesised that a temporal proximity would be reflected in the degree of correlation between in-hospital CDI cases per week. This correlation was modelled through a latent autoregressive structure of order 1 (AR(1)).
Findings: Forty-six hospitals (33 general, seven specialist, and six teaching hospitals) located in all English regions met our criteria. In total, 12,717 CDI cases were identified; seventy-five per cent of these occurred >48 hours after admission. There were slight increases in reports during winter months. We found a low, but statistically significant, correlation between successive weekly CDI case incidences (phi = 0.029, 95%CI: 0.009-0.049). This correlation was five times stronger in a subgroup analysis restricted to teaching hospitals (phi = 0.104, 95%CI: 0.048-0.159).
Conclusions: The results suggest that symptomatic patient-to-patient transmission has been a source of CDI-acquisition in English hospitals in recent years, and that this might be a more important transmission route in teaching hospitals. Nonetheless, the weak correlation indicates that, in line with recent evidence, symptomatic cases might not be the primary source of nosocomial CDI in England.
- Clostridioides difficile/physiology
- Clostridium Infections/microbiology
- Cross Infection/microbiology
- Hospitals/statistics & numerical data
- Hospitals, Teaching/statistics & numerical data
- Models, Biological