Evidence map›Paper›PMID 30309313›Full record

ArticleBMC infectious diseases2018

Mathematical modelling of vancomycin-resistant enterococci transmission during passive surveillance and active surveillance with contact isolation highlights the need to identify and address the source of acquisition.

Agnes Loo Yee Cheah, Allen C Cheng, Denis Spelman, Roger L Nation, David C M Kong, Emma S McBryde

Abstract read
In one paragraph

Article in BMC infectious diseases, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. A successfully shortened outbreak of vancomycin-resistantAntimicrobial stewardship & healthcare epidemiology : ASHE · 2025
    Article
  4. Article
  5. Review
  6. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Agnes Loo Yee CheahCentre for Medicine Use and Safety, Monash University, Parkville, VIC, Australia.
Allen C ChengDepartment of Infectious Diseases, Alfred Health, Prahran, VIC, Australia.
Denis SpelmanDepartment of Infectious Diseases, Alfred Health, Prahran, VIC, Australia.
Roger L NationDrug Delivery, Disposition and Dynamics, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, VIC, Australia.
David C M KongCentre for Medicine Use and Safety, Monash University, Parkville, VIC, Australia. david.kong@monash.edu.
Emma S McBrydeVictorian Infectious Diseases Service, Royal Melbourne Hospital, Melbourne, VIC, Australia. emma.mcbryde@jcu.edu.au.ORCID http://orcid.org/0000-0002-9570-9172

Funding

National Health and Medical Research Council 1034464National Health and Medical Research Council 1068732
6 · The paper itself

Abstract

backgroundClinical studies and mathematical simulation suggest that active surveillance with contact isolation is associated with reduced vancomycin-resistant enterococci (VRE) prevalence compared to passive surveillance. Models using pre- and post-intervention data that account for the imperfect observation and serial dependence of VRE transmission events can better estimate the effectiveness of active surveillance and subsequent contact isolation; however, such analyses have not been performed.

methodsA mathematical model was fitted to surveillance data collected pre- and post-implementation of active surveillance with contact isolation in the haematology-oncology ward. We developed a Hidden Markov Model to describe undetected and observed VRE colonisation/infection status based on the detection activities in the ward. Bayesian inference was used to estimate transmission rates. The effectiveness of active surveillance was assumed to be via increased detection and subsequent contact isolation of VRE positive patients.

resultsWe estimated that 31% (95% credible interval: 0.33-85%) of the VRE transmissions were due to cross-transmission between patients. The ratio of transmission rates from patients with contact isolation versus those without contact isolation was 0.33 (95% credible interval: 0.050-1.22).

conclusionsThe majority of the VRE acquisitions in the haematology-oncology ward was estimated to be due to background rates of VRE, rather than within ward patient to patient acquisition. The credible interval for cross-transmission was wide which results in a large degree of uncertainty in the estimates. Factors that could account for background VRE acquisition include endogenous acquisition from antibiotic selection pressure and VRE in the environment. Contact isolation was not significantly associated with reduced VRE transmission in settings where the majority of VRE acquisition was due to background acquisition, emphasising the need to identify and address the source of acquisition. As the credible interval for the ratio of VRE transmission in contact isolated versus non-contact isolated patients crossed 1, there is a probability that the transmission rate in contact isolation was not lower. Our finding highlights the need to optimise infection control measures other than active surveillance for VRE and subsequent contact isolation to reduce VRE transmission. Such measures could include antimicrobial stewardship, environmental cleaning, and hand hygiene.

Indexed as

Models, TheoreticalBayes TheoremGram-Positive Bacterial InfectionsHumansMarkov ChainsVancomycin-Resistant EnterococciActive surveillanceMathematical modellingNon-rinse chlorhexidine skin cleansingPreventionVancomycin-resistant enterococci

Identifiers

PMID30309313
PMCPMC6182842

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.