Clostridium difficile exposure as an insidious source of infection in healthcare settings: an epidemiological model

Prevalence of Clostridioides difficile contamination in the healthcare environment and instruments: A systematic review and meta-analysis

Introduction

Worldwide, Clostridioides difficile infection is becoming one of the most common healthcare-associated infections. Management and control of this infection in healthcare facilities are associated with screening for environmental and instrumental C. difficile contamination. This systematic review and meta-analysis aimed to assess the overall prevalence of C. difficile in hospital settings, medical devices, and instruments.

Methods

Four main databases, PubMed, Web of Science, Google Scholar, and Scopus, were searched using the keywords Clostridioides difficile, Clostridium difficile, C. difficile, clostridia, Clostridium spp., hospital environments, antibiotic associate colitis, intensive care unit, and ward in combination as a search strategy. The PRISMA checklist was used for selecting eligible studies.

Results

A total of 11 eligible articles published between 2012 and 2021 were included. The overall pooled prevalence of C. difficile in hospital environments was 14.9%. The highest and lowest prevalence were reported for India (51.1%) and the USA (1.6%), respectively. The highest prevalence was reported for beds (46.3%). A significant heterogeneity was seen between C. difficile prevalence in hospital environments in different samples. The highest and lowest prevalence was reported for floor corners (63.2%) and privacy curtains (1.4%), respectively.

Conclusions

In conclusion, hospitals' medical devices and environmental surfaces are considered a crucial source of Clostridioides difficile infection. In this regard, we strongly recommend revising and improving the cleaning and disinfection methods in hospitals and quality control of cleaning adequacy.

A review of epidemiological models of Clostridioides difficile transmission and control (2009-2021)

Clostridioides difficile is the leading cause of infectious diarrhea and one of the most common healthcare-acquired infections worldwide. We performed a systematic search and a bibliometric analysis of mathematical and computational models for Clostridioides difficile transmission. We identified 33 publications from 2009 to 2021. Models have underscored the importance of asymptomatic colonized patients in maintaining transmission in health-care settings. Infection control, antimicrobial stewardship, active testing, and vaccination have often been evaluated in models. Despite active testing and vaccination being not currently implemented, they are the most commonly evaluated interventions. Some aspects of C. difficile transmission, such community transmission and interventions in health-care settings other than in acute-care hospitals, remained less evaluated through modeling.

Comparing intervention strategies for reducing Clostridioides difficile transmission in acute healthcare settings: an agent-based modeling study

Background

Clostridioides difficile infection (CDI) is one of the most common healthcare infections. Common strategies aiming at controlling CDI include antibiotic stewardship, environmental decontamination, and improved hand hygiene and contact precautions. Mathematical models provide a framework to evaluate control strategies. Our objective is to evaluate the effectiveness of control strategies in decreasing C. difficile colonization and infection using an agent-based model in an acute healthcare setting.

Methods

We developed an agent-based model that simulates the transmission of C. difficile in medical wards. This model explicitly incorporates healthcare workers (HCWs) as vectors of transmission, tracks individual patient antibiotic histories, incorporates varying risk levels of antibiotics with respect to CDI susceptibility, and tracks contamination levels of ward rooms by C. difficile. Interventions include two forms of antimicrobial stewardship, increased environmental decontamination through room cleaning, improved HCW compliance, and a preliminary assessment of vaccination.

Results

Increased HCW compliance with CDI patients was ranked as the most effective intervention in decreasing colonizations, with reductions up to 56%. Antibiotic stewardship practices were highly ranked after contact precaution compliance. Vaccination and reduction of high-risk antibiotics were the most effective intervention in decreasing CDI. Vaccination reduced CDI cases to up to 90%, and the reduction of high-risk antibiotics decreased CDI cases up to 23%.

Conclusions

Overall, interventions that decrease patient susceptibility to colonization by C. difficile, such as antibiotic stewardship, were the most effective interventions in reducing both colonizations and CDI cases.

Some simple rules for estimating reproduction numbers in the presence of reservoir exposure or imported cases

For many diseases, the basic reproduction number (R0) is a threshold parameter for disease extinction or survival in isolated populations. However no human population is fully isolated from other human or animal populations. We use compartmental models to derive simple rules for the basic reproduction number in populations where an endemic disease is sustained by a combination of local transmission within the population and exposure from some other source: either a reservoir exposure or imported cases. We introduce the idea of a reservoir-driven or importation-driven disease: diseases that would become extinct in the population of interest without reservoir exposure or imported cases (since R0<1), but nevertheless may be sufficiently transmissible that many or most infections are acquired from humans in that population. We show that in the simplest case, R0<1 if and only if the proportion of infections acquired from the external source exceeds the disease prevalence and explore how population heterogeneity and the interactions of multiple strains affect this rule. We apply these rules in two case studies of Clostridium difficile infection and colonisation: C. difficile in the hospital setting accounting for imported cases, and C. difficile in the general human population accounting for exposure to animal reservoirs. We demonstrate that even the hospital-adapted, highly-transmissible NAP1/RT027 strain of C. difficile had a reproduction number <1 in a landmark study of hospitalised patients and therefore was sustained by colonised and infected admissions to the study hospital. We argue that C. difficile should be considered reservoir-driven if as little as 13.0% of transmission can be attributed to animal reservoirs.

Building upon current knowledge and techniques of indoor microbiology to construct the next era of theory into microorganisms, health, and the built environment

In the constructed habitat in which we spend up to 90% of our time, architectural design influences occupants' behavioral patterns, interactions with objects, surfaces, rituals, the outside environment, and each other. Within this built environment, human behavior and building design contribute to the accrual and dispersal of microorganisms; it is a collection of fomites that transfer microorganisms; reservoirs that collect biomass; structures that induce human or air movement patterns; and space types that encourage proximity or isolation between humans whose personal microbial clouds disperse cells into buildings. There have been recent calls to incorporate building microbiology into occupant health and exposure research and standards, yet the built environment is largely viewed as a repository for microorganisms which are to be eliminated, instead of a habitat which is inexorably linked to the microbial influences of building inhabitants. Health sectors have re-evaluated the role of microorganisms in health, incorporating microorganisms into prevention and treatment protocols, yet no paradigm shift has occurred with respect to microbiology of the built environment, despite calls to do so. Technological and logistical constraints often preclude our ability to link health outcomes to indoor microbiology, yet sufficient study exists to inform the theory and implementation of the next era of research and intervention in the built environment. This review presents built environment characteristics in relation to human health and disease, explores some of the current experimental strategies and interventions which explore health in the built environment, and discusses an emerging model for fostering indoor microbiology rather than fearing it.

Clinico-microbiological analysis of toxigenic clostridium difficile from hospitalised patients in a tertiary care hospital, Mangalore, Karnataka, India

Purpose

Prevalence of Clostridium difficile, an anaerobic, Gram-positive, spore-forming bacillus, is very much underestimated in India. The present study was intended to assess the burden of toxigenic C. difficile in hospitalised patients with clinically significant diarrhoea and analysis of their clinical picture.

Materials and Methods

This cross-sectional study was conducted in a tertiary care teaching hospital, South India, from January 2012 to December 2014. Stool samples were collected consecutively from 563 inpatients from various wards. The prevalence of toxigenic C. difficile was determined by toxigenic culture and a two-step algorithm. The clinical spectrum of these patients was also analysed. Associated pathogens were identified using standard procedures. Statistical analysis was done by frequency, percentage, Chi-square test and z-test.

Results

Out of the 563 stool samples analysed, the prevalence of toxigenic C. difficile was 12.79% and that of non-toxigenic C. difficile was 10.83%. The prevalence of toxigenic C. difficile among oncology patients was highly significant (HS). Antibiotic treatment, prolonged hospital stay and underlying diseases/conditions were the risk factors which were HS, and fever was the significant clinical feature among the patients. Escherichia coli was the predominant associated pathogen isolated (18.47%).

Conclusion

The presence of toxigenic C. difficile in our locality is a matter of concern. Constant supervision, appropriate treatment and preventive measures are crucial in controlling C. difficile infection.

Seasonality and community interventions in a mathematical model of Clostridium difficile transmission

BACKGROUND

Clostridium difficile infection (CDI) is the leading cause of antibiotic-associated diarrhoea with peak incidence in late winter or early autumn. Although CDI is commonly associated with hospitals, community transmission is important.

AIM

To explore potential drivers of CDI seasonality and the effect of community-based interventions to reduce transmission.

METHODS

A mechanistic compartmental model of C. difficile transmission in a hospital and surrounding community was used to determine the effect of reducing transmission or antibiotic prescriptions in these settings. The model was extended to allow for seasonal antibiotic prescriptions and seasonal transmission.

FINDINGS

Modelling antibiotic seasonality reproduced the seasonality of CDI, including approximate magnitude (13.9-15.1% above annual mean) and timing of peaks (0.7-1.0 months after peak antibiotics). Halving seasonal excess prescriptions reduced the incidence of CDI by 6-18%. Seasonal transmission produced larger seasonal peaks in the prevalence of community colonization (14.8-22.1% above mean) than seasonal antibiotic prescriptions (0.2-1.7% above mean). Reducing transmission from symptomatic or hospitalized patients had little effect on community-acquired CDI, but reducing transmission in the community by ≥7% or transmission from infants by ≥30% eliminated the pathogen. Reducing antibiotic prescription rates led to approximately proportional reductions in infections, but limited reductions in the prevalence of colonization.

CONCLUSION

Seasonal variation in antibiotic prescription rates can account for the observed magnitude and timing of C. difficile seasonality. Even complete prevention of transmission from hospitalized patients or symptomatic patients cannot eliminate the pathogen, but interventions to reduce transmission from community residents or infants could have a large impact on both hospital- and community-acquired infections.

Modeling Clostridium difficile in a hospital setting: control and admissions of colonized and symptomatic patients

BACKGROUND

Clostridium difficile (C. difficile) infection is an important cause of healthcare-associated diarrhea. Several factors such as admission of colonized patients, levels of serum antibodies in patients, and control strategies may involve in determining the prevalence and the persistence of C. difficile in a hospital unit.

METHODS

We develop mathematical models based on deterministic and stochastic frameworks to investigate the effects of control strategies for colonized and symptomatic patients and admissions of colonized and symptomatic patients on the prevalence and the persistence of C. difficile.

RESULTS

Our findings suggest that control strategies and admissions of colonized and symptomatic patients play important roles in determining the prevalence and the persistence of C. difficile. Improving control of C. difficile in colonized and symptomatic patients may generally help reduce the prevalence and the persistence of C. difficile. However, if admission rates of colonized and symptomatic patients are high, the prevalence of C. difficile may remain high in a patient population even though strict control policies are applied.

CONCLUSION

Control strategies and admissions of colonized and symptomatic patients are important determinants of the prevalence and the persistence of C. difficile.

Economic evaluation of interventions designed to reduce Clostridium difficile infection

INTRODUCTION

Healthcare decision-makers are increasingly expected to balance increasing demand for health services with a finite budget. The role of economic evaluation in healthcare is increasing and this research provides decision-makers with new information about the management of Clostridium difficile infection, from an economic perspective.

METHODS

A model-based economic evaluation was undertaken to identify the most cost-effective healthcare intervention relating to the reduction of Clostridium difficile transmission. Efficacy evidence was synthesised from the literature and was used to inform the effectiveness of both bundled approaches and stand-alone interventions, where appropriate intervention combinations were coupled together. Changes in health outcomes were estimated by combining information about intervention effectiveness and its subsequent impact on quality of life.

RESULTS

A bundled approach of improving hand hygiene and environmental cleaning produces the best combination of increased health benefits and cost-savings. It has the highest mean net monetary benefit when compared to all other interventions. This intervention remains the optimal decision under different clinical circumstances, such as when mortality rate and patient length of stay are increased. Bundled interventions offered the best opportunity for health improvements.

CONCLUSION

These findings provide healthcare decision-makers with novel information about the allocation of scarce resources relating to Clostridium difficile. If investments are not made in interventions that clearly yield gains in health outcomes, the allocation and use of scarce healthcare resources is inappropriate and improvements in health outcomes will be forgone.

Healthcare-Associated Clostridium difficile Infections are Sustained by Disease from the Community

Clostridium difficile infections (CDIs) are some of the most common hospital-associated infections worldwide. Approximately 5% of the general population is colonised with the pathogen, but most are protected from disease by normal intestinal flora or immune responses to toxins. We developed a stochastic compartmental model of CDI in hospitals that captures the condition of the host's gut flora and the role of adaptive immune responses. A novel, derivative-based method for sensitivity analysis of individual-level outcomes was developed and applied to the model. The model reproduced the observed incidence and recurrence rates for hospitals with high and moderate incidence of hospital-acquired CDI. In both scenarios, the reproduction number for within-hospital transmission was less than 1 (0.67 and 0.44, respectively), but the proportion colonised with C. difficile at discharge (7.3 and 6.1%, respectively) exceeded the proportion colonised at admission (5%). The transmission and prevalence of CDI were most sensitive to the average length of stay and the transmission rate of the pathogen. Recurrent infections were most strongly affected by the treatment success rate and the immune profile of patients. Transmission within hospitals is substantial and leads to a net export of colonised individuals to the broader community. However, within-hospital transmission alone is insufficient to sustain endemic conditions in hospitals without the constant importation of colonised individuals. Improved hygiene practices to reduce transmission from symptomatic and asymptomatic individuals and reduced length of stay are most likely to reduce within-hospital transmission and infections; however, these interventions are likely to have a smaller effect on the probability of recurrence. Immunising inpatients against the toxins produced by C. difficile will reduce the incidence of CDI but may increase transmission.

Assessing the effect of patient screening and isolation on curtailing Clostridium difficile infection in hospital settings

BACKGROUND

Patient screening at the time of hospital admission is not recommended as a routine practice, but may be an important strategy for containment of Clostridium difficile infection (CDI) in hospital settings. We sought to investigate the effect of patient screening in the presence of asymptomatic carriers and in the context of imperfect patient isolation.

METHODS

We developed and parameterized a stochastic simulation model for the transmission dynamics of CDI in a hospital ward.

RESULTS

We found that the transmission of CDI in the hospital, either through asymptomatic carriers or as a results of ineffective implementation of infection control practices, at the time of hospital admission. The results show that, for a sufficiently high reproduction number of CDI, the disease can persist within a hospital setting in the presence of in-ward transmission, even when there are no asymptomatically colonized patients at the time of hospital admission.

CONCLUSIONS

Our findings have significant public health and clinical implications, especially in light of the emergence and community spread of hypervirulent CDI strains with enhanced transmission rates and toxin production. Rapid detection of colonized patients remains an important component of CDI control, especially in the context of asymptomatic transmission. Screening of in-hospital patients with potential exposure to colonized patients or contaminated environment and equipment can help reduce the rates of silent transmission of CDI through asymptomatic carriers.

Comparison of Clostridium difficile Ribotypes Circulating in Australian Hospitals and Communities

Clostridium difficile infection (CDI) is becoming less exclusively a health care-associated CDI (HA-CDI). The incidence of community-associated CDI (CA-CDI) has increased over the past few decades. It has been postulated that asymptomatic toxigenic C. difficile (TCD)-colonized patients may play a role in the transfer of C. difficile between the hospital setting and the community. Thus, to investigate the relatedness of C. difficile across the hospital and community settings, we compared the characteristics of symptomatic and asymptomatic host patients and the pathogens from these patients in these two settings over a 3-year period. Two studies were simultaneously conducted; the first study enrolled symptomatic CDI patients from two tertiary care hospitals and the community in two Australian states, while the second study enrolled asymptomatic TCD-colonized patients from the same tertiary care hospitals. A total of 324 patients (96 with HA-CDI, 152 with CA-CDI, and 76 colonized with TCD) were enrolled. The predominant C. difficile ribotypes isolated in the hospital setting corresponded with those isolated in the community, as it was found that for 79% of the C. difficile isolates from hospitals, an isolate with a matching ribotype was isolated in the community, suggesting that transmission between these two settings is occurring. The toxigenic C. difficile strains causing symptomatic infection were similar to those causing asymptomatic infection, and patients exposed to antimicrobials prior to admission were more likely to develop a symptomatic infection (odds ratio, 2.94; 95% confidence interval, 1.20 to 7.14). Our findings suggest that the development of CDI symptoms in a setting without establishment of hospital epidemics with binary toxin-producing C. difficile strains may be driven mainly by host susceptibility and exposure to antimicrobials, rather than by C. difficile strain characteristics.

Quantifying Transmission of Clostridium difficile within and outside Healthcare Settings

To quantify the effect of hospital and community-based transmission and control measures on Clostridium difficile infection (CDI), we constructed a transmission model within and between hospital, community, and long-term care-facility settings. By parameterizing the model from national databases and calibrating it to C. difficile prevalence and CDI incidence, we found that hospitalized patients with CDI transmit C. difficile at a rate 15 (95% CI 7.2-32) times that of asymptomatic patients. Long-term care facility residents transmit at a rate of 27% (95% CI 13%-51%) that of hospitalized patients, and persons in the community at a rate of 0.1% (95% CI 0.062%-0.2%) that of hospitalized patients. Despite lower transmission rates for asymptomatic carriers and community sources, these transmission routes have a substantial effect on hospital-onset CDI because of the larger reservoir of hospitalized carriers and persons in the community. Asymptomatic carriers and community sources should be accounted for when designing and evaluating control interventions.

Mathematical Modeling of the Transmission Dynamics of Clostridium difficile Infection and Colonization in Healthcare Settings: A Systematic Review

BACKGROUND

We 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.

METHODS

We 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.

RESULTS

Nine 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%.

CONCLUSIONS

Although 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.

Isolation of C. difficile Carriers Alone and as Part of a Bundle Approach for the Prevention of Clostridium difficile Infection (CDI): A Mathematical Model Based on Clinical Study Data

Clostridium difficile infection is the most common hospital-acquired infection. Besides infected patients, carriers have emerged as a key player in C. difficile epidemiology. In this study, we evaluated the impact of identifying and isolating carriers upon hospital admission on the incidence of CDI incidence and hospital-acquired C. difficile colonization, as a single policy and as part of bundle approaches. We simulated C. difficile transmission using a stochastic mathematical approach, considering the contribution of carriers based on published literature. In the baseline scenario, CDI incidence was 6.18/1,000 admissions (95% CI, 5.72–6.65), simulating reported estimates from U.S. hospital discharges. The acquisition rate of C. difficile carriage was 9.72/1,000 admissions (95% CI, 9.15–10.31). Screening and isolation of colonized patients on admission to the hospital decreased CDI incidence to 4.99/1,000 admissions (95% CI, 4.59–5.42; relative reduction (RR) = 19.1%) and led to 36.2% reduction in the rate of hospital-acquired colonization. Simulating an antimicrobial stewardship program reduced CDI rate to 2.35/1,000 admissions (95% CI, 2.07–2.65). In sensitivity analysis, CDI incidence was less than 2.32/1,000 admissions (RR = 62.4%) in 95% of 1,000 simulations. The combined bundle, focusing on reducing C. difficile transmission from colonized patients and the individual risk of these patients to develop CDI, decreased significantly the incidence of both CDI and hospital-acquired colonization. Implementation of this bundle to current practice is expected to have an important impact in containing CDI.

Fecal microbiota transplantation for Clostridium difficile infection: back to the future

INTRODUCTION

Clostridium difficile infection (CDI) is a leading cause of diarrhea in the industrialized world. The estimated costs of this infection are impressive: over 3.2 billion dollars annually in the US. The introduction of fecal microbiota transplantation (FMT) to clinical practice can be considered a Copernican Revolution. The rationale of this approach consists of correcting the imbalance of the organisms dwelling in the gut by reintroducing a normal flora.

AREAS COVERED

This review focuses on the indication for FMT in CDI; it examines in-depth the most relevant aspects of the techniques used, and the safety and efficacy of this new 'old' therapy.

EXPERT OPINION

Authoritative guidelines about the management of CDI strongly recommend FMT for multiple recurrent episodes of infection by C. difficile unresponsive to repeated antibiotic treatment. The cure rates are about 90%, with no serious adverse events having been reported. The main concerns are the long-term outcomes, lack of a standardized procedure for the delivery of donor material, and a cultural barrier to the transplantation of fecal microbiota. A promising solution to some of these problems could be the use of a more acceptable administration route of fecal material, namely, oral capsules.

Asymptomatic Clostridium difficile colonization: epidemiology and clinical implications

BACKGROUND

The epidemiology of Clostridium difficile infection (CDI) has changed over the past decades with the emergence of highly virulent strains. The role of asymptomatic C. difficile colonization as part of the clinical spectrum of CDI is complex because many risk factors are common to both disease and asymptomatic states. In this article, we review the role of asymptomatic C. difficile colonization in the progression to symptomatic CDI, describe the epidemiology of asymptomatic C. difficile colonization, assess the effectiveness of screening and intensive infection control practices for patients at risk of asymptomatic C. difficile colonization, and discuss the implications for clinical practice.

METHODS

A narrative review was performed in PubMed for articles published from January 1980 to February 2015 using search terms 'Clostridium difficile' and 'colonization' or 'colonisation' or 'carriage'.

RESULTS

There is no clear definition for asymptomatic CDI and the terms carriage and colonization are often used interchangeably. The prevalence of asymptomatic C. difficile colonization varies depending on a number of host, pathogen, and environmental factors; current estimates of asymptomatic colonization may be underestimated as stool culture is not practical in a clinical setting.

CONCLUSIONS

Asymptomatic C. difficile colonization presents challenging concepts in the overall picture of this disease and its management. Individuals who are colonized by the organism may acquire protection from progression to disease, however they also have the potential to contribute to transmission in healthcare settings.

Modeling the impact of interventions against Acinetobacter baumannii transmission in intensive care units

The efficacy of infection control interventions against Acinetobacter baumannii remains unclear, despite such information being critical for effective prevention of the transmission of this pathogen. Mathematical modeling offers an alternative to clinical trials, which may be prohibitively expensive, unfeasible or unethical, in predicting the impact of interventions. Furthermore, it allows the ability to ask key “what if” questions to evaluate which interventions have the most impact. We constructed a transmission dynamic model to quantify the effects of interventions on reducing A. baumannii prevalence and the basic reproduction ratio (R₀) in intensive care units (ICUs). We distinguished between colonization and infection, and incorporated antibiotic exposure and transmission from free-living bacteria in the environment. Under the assumptions and parameterization in our model, 25% and 18% of patients are colonized and infected with A. baumannii, respectively; and R₀ is 1.4. Improved compliance with hand hygiene (≥87%), enhanced environmental cleaning, reduced length of ICU stay of colonized patients (≤ 10 days), shorter durations of antibiotic treatment of A. baumannii (≤6 days), and isolation of infected patients combined with cleaning of isolation rooms are effective, reducing R₀ to below unity. In contrast, expediting the recovery of the intestinal microbiota (e.g. use of probiotics) is not effective. This study represents a biologically realistic model of the transmission dynamics of A. baumannii, and the most comprehensive analysis of the effectiveness of interventions against this pathogen. Our study provides important data for designing effective infection control interventions.

Mechanisms of hypervirulent Clostridium difficile ribotype 027 displacement of endemic strains: an epidemiological model

Following rapid, global clonal dominance of hypervirulent ribotypes, Clostridium difficile now constitutes the primary infectious cause of nosocomial diarrhoea. Evidence indicates at least three possible mechanisms of hypervirulence that facilitates the successful invasion of these atypical strains: 1) increased infectiousness relative to endemic strains; 2) increased symptomatic disease rate relative to endemic strains; and 3) an ability to outcompete endemic strains in the host’s gut. Stochastic simulations of an infection transmission model demonstrate clear differences between the invasion potentials of C. difficile strains utilising the alternative hypervirulence mechanisms, and provide new evidence that favours certain mechanisms (1 and 2) more than others (3). Additionally, simulations illustrate that direct competition between strains (inside the host’s gut) is not a prerequisite for the sudden switching that has been observed in prevailing ribotypes; previously dominant C. difficile strains can be excluded by hypervirulent ribotypes through indirect (exploitative) competition.

Clostridium difficile infection seasonality: patterns across hemispheres and continents - a systematic review

Background

Studies have demonstrated seasonal variability in rates of Clostridium difficile infection (CDI). Synthesising all available information on seasonality is a necessary step in identifying large-scale epidemiological patterns and elucidating underlying causes.

Methods

Three medical and life sciences publication databases were searched from inception to October 2014 for longitudinal epidemiological studies written in English, Spanish or Portuguese that reported the incidence of CDI. The monthly frequency of CDI were extracted, standardized and weighted according to the number of follow-up months. Cross correlation coefficients (XCORR) were calculated to examine the correlation and lag between the year-month frequencies of reported CDI across hemispheres and continents.

Results

The search identified 13, 5 and 2 studies from North America, Europe, and Oceania, respectively that met the inclusion criteria. CDI had a similar seasonal pattern in the Northern and Southern Hemisphere characterized by a peak in spring and lower frequencies of CDI in summer/autumn with a lag of 8 months (XCORR = 0.60) between hemispheres. There was no difference between the seasonal patterns across European and North American countries.

Conclusion

CDI demonstrates a distinct seasonal pattern that is consistent across North America, Europe and Oceania. Further studies are required to identify the driving factors of the observed seasonality.

Clostridium difficile infection in the elderly

Clostridium difficile-associated illness is an increasingly prevalent and morbid condition. The elderly population is at a disproportionate risk of developing symptomatic disease and associated complications, including progression to severe or fulminant disease, and development of recurrent infections. This article analyzes the factors that influence C difficile disease propensity and severity, with particular attention directed toward features relevant to the rapidly aging population.

A population-based spatio-temporal analysis of Clostridium difficile infection in Queensland, Australia over a 10-year period

OBJECTIVES

To identify the spatio-temporal patterns and environmental factors associated with Clostridium difficile infection (CDI) in Queensland, Australia.

METHODS

Data from patients tested for CDI were collected from 392 postcodes across Queensland between May 2003 and December 2012. A binomial logistic regression model, with CDI status as the outcome, was built in a Bayesian framework, incorporating fixed effects for sex, age, source of the sample (healthcare facility or community), elevation, rainfall, land surface temperature, seasons of the year, time in months and spatially unstructured random effects at the postcode level.

RESULTS

C. difficile was identified in 13.1% of the samples, the proportion significantly increased over the study period from 5.9% in 2003 to 18.8% in 2012. CDI peaked in summer (14.6%) and was at its lowest in autumn (10.1%). Other factors significantly associated with CDI included female sex (OR: 1.08; 95%CI: 1.01-1.14), community source samples (OR: 1.12; 95%CI: 1.05-1.20), and higher rainfall (OR: 1.09; 95%CI: 1.02-1.17). There was no significant spatial variation in CDI after accounting for the fixed effects in the model.

CONCLUSIONS

There was an increasing annual trend in CDI in Queensland from 2003 to 2012. Peaks of CDI were found in summer (December-February), which is at odds with the current epidemiological pattern described for northern hemisphere countries. Epidemiologically plausible explanations for this disparity require further investigation.

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

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.

Microbiome data distinguish patients with Clostridium difficile infection and non-C. difficile-associated diarrhea from healthy controls

Antibiotic usage is the most commonly cited risk factor for hospital-acquired Clostridium difficile infections (CDI). The increased risk is due to disruption of the indigenous microbiome and a subsequent decrease in colonization resistance by the perturbed bacterial community; however, the specific changes in the microbiome that lead to increased risk are poorly understood. We developed statistical models that incorporated microbiome data with clinical and demographic data to better understand why individuals develop CDI. The 16S rRNA genes were sequenced from the feces of 338 individuals, including cases, diarrheal controls, and nondiarrheal controls. We modeled CDI and diarrheal status using multiple clinical variables, including age, antibiotic use, antacid use, and other known risk factors using logit regression. This base model was compared to models that incorporated microbiome data, using diversity metrics, community types, or specific bacterial populations, to identify characteristics of the microbiome associated with CDI susceptibility or resistance. The addition of microbiome data significantly improved our ability to distinguish CDI status when comparing cases or diarrheal controls to nondiarrheal controls. However, only when we assigned samples to community types was it possible to differentiate cases from diarrheal controls. Several bacterial species within the Ruminococcaceae, Lachnospiraceae, Bacteroides, and Porphyromonadaceae were largely absent in cases and highly associated with nondiarrheal controls. The improved discriminatory ability of our microbiome-based models confirms the theory that factors affecting the microbiome influence CDI.

The gut microbiome, composed of the trillions of bacteria residing in the gastrointestinal tract, is responsible for a number of critical functions within the host. These include digestion, immune system stimulation, and colonization resistance. The microbiome’s role in colonization resistance, which is the ability to prevent and limit pathogen colonization and growth, is key for protection against Clostridium difficile infections. However, the bacteria that are important for colonization resistance have not yet been elucidated. Using statistical modeling techniques and different representations of the microbiome, we demonstrated that several community types and the loss of several bacterial populations, including Bacteroides, Lachnospiraceae, and Ruminococcaceae, are associated with CDI. Our results emphasize the importance of considering the microbiome in mediating colonization resistance and may also direct the design of future multispecies probiotic therapies.

Microbiome data distinguish patients with Clostridium difficile infection and non-C. difficile-associated diarrhea from healthy controls

Antibiotic usage is the most commonly cited risk factor for hospital-acquired Clostridium difficile infections (CDI). The increased risk is due to disruption of the indigenous microbiome and a subsequent decrease in colonization resistance by the perturbed bacterial community; however, the specific changes in the microbiome that lead to increased risk are poorly understood. We developed statistical models that incorporated microbiome data with clinical and demographic data to better understand why individuals develop CDI. The 16S rRNA genes were sequenced from the feces of 338 individuals, including cases, diarrheal controls, and nondiarrheal controls. We modeled CDI and diarrheal status using multiple clinical variables, including age, antibiotic use, antacid use, and other known risk factors using logit regression. This base model was compared to models that incorporated microbiome data, using diversity metrics, community types, or specific bacterial populations, to identify characteristics of the microbiome associated with CDI susceptibility or resistance. The addition of microbiome data significantly improved our ability to distinguish CDI status when comparing cases or diarrheal controls to nondiarrheal controls. However, only when we assigned samples to community types was it possible to differentiate cases from diarrheal controls. Several bacterial species within the Ruminococcaceae, Lachnospiraceae, Bacteroides, and Porphyromonadaceae were largely absent in cases and highly associated with nondiarrheal controls. The improved discriminatory ability of our microbiome-based models confirms the theory that factors affecting the microbiome influence CDI. IMPORTANCE The gut microbiome, composed of the trillions of bacteria residing in the gastrointestinal tract, is responsible for a number of critical functions within the host. These include digestion, immune system stimulation, and colonization resistance. The microbiome's role in colonization resistance, which is the ability to prevent and limit pathogen colonization and growth, is key for protection against Clostridium difficile infections. However, the bacteria that are important for colonization resistance have not yet been elucidated. Using statistical modeling techniques and different representations of the microbiome, we demonstrated that several community types and the loss of several bacterial populations, including Bacteroides, Lachnospiraceae, and Ruminococcaceae, are associated with CDI. Our results emphasize the importance of considering the microbiome in mediating colonization resistance and may also direct the design of future multispecies probiotic therapies.