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Assessing control bundles for Clostridium difficile: a review and mathematical model.

ABSTRACT: Clostridium difficile is the leading cause of infectious diarrhea in hospitalized patients. Integrating several infection control and prevention methods is a burgeoning strategy for reducing disease incidence in healthcare settings. We present an up-to-date review of the literature on 'control bundles' used to mitigate the transmission of this pathogen. All clinical studies of control bundles reported substantial reductions in disease rates, in the order of 33%-61%. Using a biologically realistic mathematical model we then simulated the efficacy of different combinations of the most prominent control methods: stricter antimicrobial stewardship; the administering of probiotics/intestinal microbiota transplantation; and improved hygiene and sanitation. We also assessed the health gains that can be expected from reducing the average length of stay of inpatients. In terms of reducing the rates of colonization, all combinations had the potential to give rise to marked improvements. For example, halving the number of inpatients on broad-spectrum antimicrobials combined with prescribing probiotics or intestinal microbiota transplantation could cut pathogen carriage by two-thirds. However, in terms of symptomatic disease incidence reduction, antimicrobials, probiotics and intestinal microbiota transplantation proved substantially less effective. Eliminating within-ward transmission by improving sanitation and reducing average length of stay (from six to three days) yielded the most potent symptomatic infection control combination, cutting rates down from three to less than one per 1000 hospital bed days. Both the empirical and theoretical exploration of C. difficile control combinations presented in the current study highlights the potential gains that can be achieved through strategically integrated infection control.

SUBMITTER: Yakob L

PROVIDER: S-EPMC4078791 | biostudies-other | 2014 Jun

REPOSITORIES: biostudies-other

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Project description:IntroductionMathematical modelling of Clostridium difficile infection dynamics could contribute to the optimisation of strategies for its prevention and control. The objective of this systematic review was to summarise the available literature specifically identifying the quantitative parameters required for a compartmental mathematical model of Clostridium difficile transmission.MethodsSix electronic healthcare databases were searched and all screening, data extraction and study quality assessments were undertaken in duplicate. Results were synthesised using a narrative approach.ResultsFifty-four studies met the inclusion criteria. Reproduction numbers for hospital based epidemics were described in two studies with a range from 0.55 to 7. Two studies provided consistent data on incubation periods. For 62% of cases, symptoms occurred in less than 4 weeks (3-28 days) after infection. Evidence on contact patterns was identified in four studies but with limited data reported for populating a mathematical model. Two studies, including one without clinically apparent donor-recipient pairs, provided information on serial intervals for household or ward contacts, showing transmission intervals of <1 week in ward based contacts compared to up to 2 months for household contacts. Eight studies reported recovery rates of between 75%-100% for patients who had been treated with either metronidazole or vancomycin. Forty-nine studies gave recurrence rates of between 3% and 49% but were limited by varying definitions of recurrence. No study was found which specifically reported force of infection or net reproduction numbers.ConclusionsThere is currently scant literature overtly citing estimates of the parameters required to inform the quantitative modelling of Clostridium difficile transmission. Further high quality studies to investigate transmission parameters are required, including through review of published epidemiological studies where these quantitative estimates may not have been explicitly estimated, but that nonetheless contain the relevant data to allow their calculation.

Project description:BackgroundWe conducted a systematic review of mathematical models of transmission dynamic of Clostridium difficile infection (CDI) in healthcare settings, to provide an overview of existing models and their assessment of different CDI control strategies.MethodsWe searched MEDLINE, EMBASE and Web of Science up to February 3, 2016 for transmission-dynamic models of Clostridium difficile in healthcare settings. The models were compared based on their natural history representation of Clostridium difficile, which could include health states (S-E-A-I-R-D: Susceptible-Exposed-Asymptomatic-Infectious-Resistant-Deceased) and the possibility to include healthcare workers and visitors (vectors of transmission). Effectiveness of interventions was compared using the relative reduction (compared to no intervention or current practice) in outcomes such as incidence of colonization, CDI, CDI recurrence, CDI mortality, and length of stay.ResultsNine studies describing six different models met the inclusion criteria. Over time, the models have generally increased in complexity in terms of natural history and transmission dynamics and number/complexity of interventions/bundles of interventions examined. The models were categorized into four groups with respect to their natural history representation: S-A-I-R, S-E-A-I, S-A-I, and S-E-A-I-R-D. Seven studies examined the impact of CDI control strategies. Interventions aimed at controlling the transmission, lowering CDI vulnerability and reducing the risk of recurrence/mortality were predicted to reduce CDI incidence by 3-49%, 5-43% and 5-29%, respectively. Bundles of interventions were predicted to reduce CDI incidence by 14-84%.ConclusionsAlthough CDI is a major public health problem, there are very few published transmission-dynamic models of Clostridium difficile. Published models vary substantially in the interventions examined, the outcome measures used and the representation of the natural history of Clostridium difficile, which make it difficult to synthesize results and provide a clear picture of optimal intervention strategies. Future modeling efforts should pay specific attention to calibration, structural uncertainties, and transparent reporting practices.

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Assessing control bundles for Clostridium difficile: a review and mathematical model.

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