ArticlePLoS computational biology2021
Probabilistic transmission models incorporating sequencing data for healthcare-associated Clostridioides difficile outperform heuristic rules and identify strain-specific differences in transmission.
Article in PLoS computational biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 20 citations in OpenAlex.
- Probiotics Ameliorate Histological Alterations and Prevent Increases in Cytokine and Toxin Levels in Mice Infected with Various Clostridioides difficile Strains.Probiotics and antimicrobial proteins · 2026Article
- Regression-based modeling of pairwise genomic linkage data identifies risk factors for healthcare-associated pathogen transmission: application to carbapenem-resistantMicrobiology spectrum · 2026Article
- Optimizing genomic sampling for demographic and epidemiological inference with Markov decision processes.Genetics · 2026Article
- Inferring asymptomatic carriers of antimicrobial-resistant organisms in hospitals using genomic, microbiological and patient mobility data.Nature communications · 2025Article
- Environmental and Health Care Personnel Sampling and Unobserved Clostridium difficile Transmission in ICU.JAMA network open · 2025Observational
- Expanding the use of mathematical modeling in healthcare epidemiology and infection prevention and control.Infection control and hospital epidemiology · 2024Review
- Ensemble inference of unobserved infections in networks using partial observations.PLoS computational biology · 2023Article
- Challenges in Forecasting Antimicrobial Resistance.Emerging infectious diseases · 2023Review
- Examining the impact of ICU population interaction structure on modeled colonization dynamics of Staphylococcus aureus.PLoS computational biology · 2022Article
- A review of epidemiological models of Clostridioides difficile transmission and control (2009-2021).Anaerobe · 2022Review
- Infection prevention and control insights from a decade of pathogen whole-genome sequencing.The Journal of hospital infection · 2022Review
- Modeling transmission of pathogens in healthcare settings.Current opinion in infectious diseases · 2021Review
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
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.
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