Dataset Information

Stochastic modelling and inference in electronic hospital databases for the spread of infections: Clostridium difficile transmission in Oxfordshire hospitals 2007-2010.

ABSTRACT: The combination of genetic information with electronic patient records promises to provide a powerful new resource for understanding human disease and its treatment. Here we develop and apply a novel stochastic compartmental model to a large dataset on Clostridium difficile infection (CDI) in three Oxfordshire hospitals over a 2.5 year period which combines genetic information on 858 confirmed cases of CDI with a database of 750,000 patient records. C. difficile is a major cause of healthcare-associated diarrhoea and is responsible for substantial mortality and morbidity, with relatively little known about its biology or its transmission epidemiology. Bayesian analysis of our model, via Markov chain Monte Carlo, provides new information about the biology of CDI, including genetic heterogeneity in infectiousness across different sequence types, and evidence for ward contamination as a significant mode of transmission, and allows inferences about the contribution of particular individuals, wards, or hospitals to transmission of the bacterium, and assessment of changes in these over time following changes in hospital practice. Our work demonstrates the value of using statistical modelling and computational inference on large-scale hospital patient databases and genetic data.

SUBMITTER: Cule M

PROVIDER: S-EPMC6520235 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Stochastic modelling and inference in electronic hospital databases for the spread of infections: Clostridium difficile transmission in Oxfordshire hospitals 2007-2010.

Cule Madeleine M Donnelly Peter P

The annals of applied statistics 20170101 2

The combination of genetic information with electronic patient records promises to provide a powerful new resource for understanding human disease and its treatment. Here we develop and apply a novel stochastic compartmental model to a large dataset on Clostridium difficile infection (CDI) in three Oxfordshire hospitals over a 2.5 year period which combines genetic information on 858 confirmed cases of CDI with a database of 750,000 patient records. C. difficile is a major cause of ...[more]

PMID: 31105805

Similar Datasets

Project description:Background: Approximately 30-40% of children <1 year of age are Clostridium difficile colonized, and may represent a reservoir for adult C. difficile infections (CDI). Risk factors for colonization with toxigenic versus non-toxigenic C. difficile strains and longitudinal acquisition dynamics in infants remain incompletely characterized.Methods: Predominantly healthy infants (?2 years) were recruited in Oxfordshire, UK, and provided ?1 fecal samples. Independent risk factors for toxigenic/non-toxigenic C. difficile colonization and acquisition were identified using multivariable regression. Infant C. difficile isolates were whole-genome sequenced to assay genetic diversity and prevalence of toxin-associated genes, and compared with sequenced strains from Oxfordshire CDI cases.Results: 338/365 enrolled infants provided 1332 fecal samples, representing 158 C. difficile colonization or carriage episodes (107[68%] toxigenic). Initial colonization was associated with age, and reduced with breastfeeding but increased with pet dogs. Acquisition was associated with older age, Caesarean delivery, and diarrhea. Breastfeeding and pre-existing C. difficile colonization reduced acquisition risk. Overall 13% of CDI C. difficile strains were genetically related to infant strains. 29(18%) infant C. difficile sequences were consistent with recent direct/indirect transmission to/from Oxfordshire CDI cases (?2 single nucleotide variants [SNVs]); 79(50%) shared a common origin with an Oxfordshire CDI case within the last ~5 years (0-10 SNVs). The hypervirulent, epidemic ST1/ribotype 027 remained notably absent in infants in this large study, as did other lineages such as STs 10/44 (ribotype 015); the most common strain in infants was ST2 (ribotype 020/014)(22%).Conclusions: In predominantly healthy infants without significant healthcare exposure C. difficile colonization and acquisition reflect environmental exposures, with pet dogs identified as a novel risk factor. Genetic overlap between some infant strains and those isolated from CDI cases suggest common community reservoirs of these C. difficile lineages, contrasting with those lineages found only in CDI cases, and therefore more consistent with healthcare-associated spread.

Project description:BackgroundClostridium difficile is the major cause of pseudomembranous colitis associated with antibiotic use, and the spread of the hypervirulent epidemic ribotype 027/NAP-1 strain across hospitals worldwide has re-focused attention on this nosocomial pathogen. The overall incidence and trend of C. difficile-associated disease (CDAD) in Singapore is unknown, and a surveillance program to determine these via formal laboratory-based reporting was established.FindingsLaboratory and pharmacy data were collated from one tertiary and two secondary hospitals on a quarterly basis between 2006 and 2008. All hospitals tested for C. difficile using Immunocard Toxins A&B (Meridian Bioscience Inc., Cincinnati, OH) during this period. Duplicate positive C. difficile results within a 14-day period were removed. The CDAD results were compared with trends in hospital-based prescription of major classes of antibiotics.Overall CDAD incidence-density decreased from 5.16 (95%CI: 4.73 - 5.62) cases per 10,000 inpatient-days in 2006 to 2.99 (95%CI: 2.67 to 3.33) cases per 10,000 inpatient-days in 2008 (p < 0.001), while overall rates for C. difficile testing increased significantly (p < 0.001) within the same period. These trends were mirrored at the individual hospital level. Evaluation of antibiotic prescription data at all hospitals showed increasing use of carbapenems and fluoroquinolones, while cephalosporin and clindamycin prescription remained stable.ConclusionsOur results demonstrate a real decline of CDAD rates in three large local hospitals. The cause is unclear and is not associated with improved infection control measures or reduction in antibiotic prescription. Lack of C. difficile stool cultures as part of routine testing precluded determination of the decline of a major clone as a potential explanation. For more accurate epidemiological trending of CDAD and early detection of epidemic clones, data collection will have to be expanded and resources set in place for reference laboratory culture and typing.

Dataset Information

Stochastic modelling and inference in electronic hospital databases for the spread of infections: Clostridium difficile transmission in Oxfordshire hospitals 2007-2010.

Publications

Stochastic modelling and inference in electronic hospital databases for the spread of infections: <i>Clostridium difficile</i> transmission in Oxfordshire hospitals 2007-2010.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets