Dataset Information

Probabilistic transmission models incorporating sequencing data for healthcare-associated Clostridioides difficile outperform heuristic rules and identify strain-specific differences in transmission.

ABSTRACT: Fitting stochastic transmission models to electronic patient data can offer detailed insights into the transmission of healthcare-associated infections and improve infection control. Pathogen whole-genome sequencing may improve the precision of model inferences, but computational constraints have limited modelling applications predominantly to small datasets and specific outbreaks, whereas large-scale sequencing studies have mostly relied on simple rules for identifying/excluding plausible transmission. We present a novel approach for integrating detailed epidemiological data on patient contact networks in hospitals with large-scale pathogen sequencing data. We apply our approach to study Clostridioides difficile transmission using a dataset of 1223 infections in Oxfordshire, UK, 2007-2011. 262 (21% [95% credibility interval 20-22%]) infections were estimated to have been acquired from another known case. There was heterogeneity by sequence type (ST) in the proportion of cases acquired from another case with the highest rates in ST1 (ribotype-027), ST42 (ribotype-106) and ST3 (ribotype-001). These same STs also had higher rates of transmission mediated via environmental contamination/spores persisting after patient discharge/recovery; for ST1 these persisted longer than for most other STs except ST3 and ST42. We also identified variation in transmission between hospitals, medical specialties and over time; by 2011 nearly all transmission from known cases had ceased in our hospitals. Our findings support previous work suggesting only a minority of C. difficile infections are acquired from known cases but highlight a greater role for environmental contamination than previously thought. Our approach is applicable to other healthcare-associated infections. Our findings have important implications for effective control of C. difficile.

SUBMITTER: Eyre DW

PROVIDER: S-EPMC7840057 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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Probabilistic transmission models incorporating sequencing data for healthcare-associated Clostridioides difficile outperform heuristic rules and identify strain-specific differences in transmission.

Eyre David W DW Laager Mirjam M Walker A Sarah AS Cooper Ben S BS Wilson Daniel J DJ

PLoS computational biology 20210114 1

Fitting stochastic transmission models to electronic patient data can offer detailed insights into the transmission of healthcare-associated infections and improve infection control. Pathogen whole-genome sequencing may improve the precision of model inferences, but computational constraints have limited modelling applications predominantly to small datasets and specific outbreaks, whereas large-scale sequencing studies have mostly relied on simple rules for identifying/excluding plausible trans ...[more]

PMID: 33444378

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Project description:ObjectiveLack of judicious testing can result in the incorrect diagnosis of Clostridioides difficile infection (CDI), unnecessary CDI treatment, increased costs and falsely augmented hospital-acquired infection (HAI) rates. We evaluated facility-wide interventions used at the VA San Diego Healthcare System (VASDHS) to reduce healthcare-onset, healthcare-facility-associated CDI (HO-HCFA CDI), including the use of diagnostic stewardship with test ordering criteria.DesignWe conducted a retrospective study to assess the effectiveness of measures implemented to reduce the rate of HO-HCFA CDI at the VASDHS from fiscal year (FY)2015 to FY2018.InterventionsMeasures executed in a stepwise fashion included a hand hygiene initiative, prompt isolation of CDI patients, enhanced terminal room cleaning, reduction of fluoroquinolone and proton-pump inhibitor use, laboratory rejection of solid stool samples, and lastly diagnostic stewardship with C. difficile toxin B gene nucleic acid amplification testing (NAAT) criteria instituted in FY2018.ResultsFrom FY2015 to FY2018, 127 cases of HO-HCFA CDI were identified. All rate-reducing initiatives resulted in decreased HO-HCFA cases (from 44 to 13; P ≤ .05). However, the number of HO-HCFA cases (34 to 13; P ≤ .05), potential false-positive testing associated with colonization and laxative use (from 11 to 4), hospital days (from 596 to 332), CDI-related hospitalization costs (from $2,780,681 to $1,534,190) and treatment cost (from $7,158 vs $1,476) decreased substantially following the introduction of diagnostic stewardship with test criteria from FY2017 to FY2018.ConclusionsInitiatives to decrease risk for CDI and diagnostic stewardship of C. difficile stool NAAT significantly reduced HO-HCFA CDI rates, detection of potential false-positives associated with laxative use, and lowered healthcare costs. Diagnostic stewardship itself had the most dramatic impact on outcomes observed and served as an effective tool in reducing HO-HCFA CDI rates.

Project description:Clostridioides difficile is a ubiquitous, diarrhoeagenic pathogen often associated with healthcare-acquired infections that can cause a range of symptoms from mild, self-limiting disease to toxic megacolon and death. Since the early 2000s, a large proportion of C. difficile cases have been attributed to the ribotype 027 (RT027) lineage, which is associated with sequence type 1 (ST1) in the C. difficile multilocus sequence typing scheme. The spread of ST1 has been attributed, in part, to resistance to fluoroquinolones used to treat unrelated infections, which creates conditions ideal for C. difficile colonization and proliferation. In this study, we analysed 27 isolates from a healthcare network in northern Arizona, USA, and 1352 publicly available ST1 genomes to place locally sampled isolates into a global context. Whole genome, single nucleotide polymorphism analysis demonstrated that at least six separate introductions of ST1 were observed in healthcare facilities in northern Arizona over an 18-month sampling period. A reconstruction of transmission networks identified potential nosocomial transmission of isolates, which were only identified via whole genome sequence analysis. Antibiotic resistance heterogeneity was observed among ST1 genomes, including variability in resistance profiles among locally sampled ST1 isolates. To investigate why ST1 genomes are so common globally and in northern Arizona, we compared all high-quality C. difficile genomes and identified that ST1 genomes have gained and lost a number of genomic regions compared to all other C. difficile genomes; analyses of other toxigenic C. difficile sequence types demonstrate that this loss may be anomalous and could be related to niche specialization. These results suggest that a combination of antimicrobial resistance and gain and loss of specific genes may explain the prominent association of this sequence type with C. difficile infection cases worldwide. The degree of genetic variability in ST1 suggests that classifying all ST1 genomes into a quinolone-resistant hypervirulent clone category may not be appropriate. Whole genome sequencing of clinical C. difficile isolates provides a high-resolution surveillance strategy for monitoring persistence and transmission of C. difficile and for assessing the performance of infection prevention and control strategies.

Dataset Information

Probabilistic transmission models incorporating sequencing data for healthcare-associated Clostridioides difficile outperform heuristic rules and identify strain-specific differences in transmission.

Publications

Probabilistic transmission models incorporating sequencing data for healthcare-associated Clostridioides difficile outperform heuristic rules and identify strain-specific differences in transmission.

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