Using Spatial and Temporal Mapping to Identify Nosocomial Disease Transmission of Clostridium difficile

Integrated Genomic and Social Network Analyses of SARS-CoV-2 Transmission in the Healthcare Setting

BACKGROUND

Infection prevention (IP) measures are designed to mitigate the transmission of pathogens in healthcare. Using large-scale viral genomic and social network analyses, we determined if IP measures used during the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic were adequate in protecting healthcare workers (HCWs) and patients from acquiring SARS-CoV-2.

METHODS

We performed retrospective cross-sectional analyses of viral genomics from all available SARS-CoV-2 viral samples collected at UC San Diego Health and social network analysis using the electronic medical record to derive temporospatial overlap of infections among related viromes and supplemented with contact tracing data. The outcome measure was any instance of healthcare transmission, defined as cases with closely related viral genomes and epidemiological connection within the healthcare setting during the infection window. Between November 2020 through January 2022, 12 933 viral genomes were obtained from 35 666 patients and HCWs.

RESULTS

Among 5112 SARS-CoV-2 viral samples sequenced from the second and third waves of SARS-CoV-2 (pre-Omicron), 291 pairs were derived from persons with a plausible healthcare overlap. Of these, 34 pairs (12%) were phylogenetically linked: 19 attributable to household and 14 to healthcare transmission. During the Omicron wave, 2106 contact pairs among 7821 sequences resulted in 120 (6%) related pairs among 32 clusters, of which 10 were consistent with healthcare transmission. Transmission was more likely to occur in shared spaces in the older hospital compared with the newer hospital (2.54 vs 0.63 transmission events per 1000 admissions, P < .001).

CONCLUSIONS

IP strategies were effective at identifying and preventing healthcare SARS-CoV-2 transmission.

Pathogenicity and virulence of Clostridioides difficile

Clostridioides difficile is the most common cause of nosocomial antibiotic-associated diarrhea, and is responsible for a spectrum of diseases characterized by high levels of recurrence, morbidity, and mortality. Treatment is complex, since antibiotics constitute both the main treatment and the major risk factor for infection. Worryingly, resistance to multiple antibiotics is becoming increasingly widespread, leading to the classification of this pathogen as an urgent threat to global health. As a consummate opportunist, C. difficile is well equipped for promoting disease, owing to its arsenal of virulence factors: transmission of this anaerobe is highly efficient due to the formation of robust endospores, and an array of adhesins promote gut colonization. C. difficile produces multiple toxins acting upon gut epithelia, resulting in manifestations typical of diarrheal disease, and severe inflammation in a subset of patients. This review focuses on such virulence factors, as well as the importance of antimicrobial resistance and genome plasticity in enabling pathogenesis and persistence of this important pathogen.

Screening for Clostridioides difficile colonization at admission to the hospital: a multi-centre study

OBJECTIVE

This study aimed to assess the value of C. difficile colonization (CDC) screening at hospital admission in an endemic setting.

METHODS

A multi-centre study was performed in 4 hospitals located across the Netherlands. Newly admitted patients were screened for CDC. The risk to develop C. difficile infection (CDI) during admission and one-year follow-up was assessed for colonized and non-colonized patients. C. difficile isolates from colonized patients were compared with isolates from incident CDI cases using core genome multi locus sequence typing (cgMLST) to determine if onwards transmission had occurred.

RESULTS

CDC was present in 108/2211 admissions (4.9%), while colonization with a toxigenic strain (tCDC) was present in 68/2211 (3.1%) of admissions. Among these 108 colonized patients, diverse PCR ribotypes were found and no 'hypervirulent' RT027 was detected ((95% CI, 0- 0.028). None of the colonized patients developed CDI during admission (0/49, 95% CI 0-0.073) or one-year follow-up (0/38, 95% CI 0-0.93). Core genome MLST identified 6 clusters with genetically related isolates from tCDC and CDI patients, but in these clusters only one possible transmission event from a tCDC to a CDI patient was identified by epidemiological data.

CONCLUSION

In this endemic setting with a low prevalence of 'hypervirulent' strains screening on CDC at admission did not detect any CDC patient who progressed to symptomatic CDI and only one possible transmission event from a colonized patient to a CDI patient. Thus, screening on CDC at admission is not useful in this setting.

Investigating healthcare worker mobility and patient contacts within a UK hospital during the COVID-19 pandemic

BACKGROUND

Insights into behaviours relevant to the transmission of infections are extremely valuable for epidemiological investigations. Healthcare worker (HCW) mobility and patient contacts within the hospital can contribute to nosocomial outbreaks, yet data on these behaviours are often limited.

METHODS

Using electronic medical records and door access logs from a London teaching hospital during the COVID-19 pandemic, we derive indicators for HCW mobility and patient contacts at an aggregate level. We assess the spatial-temporal variations in HCW behaviour and, to demonstrate the utility of these behavioural markers, investigate changes in the indirect connectivity of patients (resulting from shared contacts with HCWs) and spatial connectivity of floors (owing to the movements of HCWs).

RESULTS

Fluctuations in HCW mobility and patient contacts were identified during the pandemic, with the most prominent changes in behaviour on floors handling the majority of COVID-19 patients. The connectivity between floors was disrupted by the pandemic and, while this stabilised after the first wave, the interconnectivity of COVID-19 and non-COVID-19 wards always featured. Daily rates of indirect contact between patients provided evidence for reactive staff cohorting in response to the number of COVID-19 patients in the hospital.

CONCLUSIONS

Routinely collected electronic records in the healthcare environment provide a means to rapidly assess and investigate behaviour change in the HCW population, and can support evidence based infection prevention and control activities. Integrating frameworks like ours into routine practice will empower decision makers and improve pandemic preparedness by providing tools to help curtail nosocomial outbreaks of communicable diseases.

Can Emergency Department Wait Times Predict Rates of Hospital-Acquired Clostridioides difficile Infection? A Study of Acute Care Facilities in New York State

OBJECTIVE

Clostridioides difficile is the most common hospital-acquired pathogen and persists in the environment for extended periods. As a common entry point for patients with diarrhea, and a setting providing fast-paced, high-volume care, emergency departments (EDs) are often sites of C. difficile contamination. This study examined the relationship between average patient wait times in the ED before admission and overall hospital-acquired C. difficile infection (HA-CDI) rates in New York State acute care hospitals.

METHODS

A random-effects regression analysis compared each facility's annual average ED wait time for admitted patients with that facility's average (HA-CDI) rates for patients entering through the ED. This model controlled for known clinical and nonclinical predictors of HA-CDI: average length of stay; case mix index; total discharges, a measure of hospital size; and percent Medicare discharges, a proxy for advanced age.

RESULTS

Emergency department wait times had a significant and positive relationship with HA-CDI rates. Facilities experience an additional 0.002 cases of HA-CDI per 1000 patient discharges with every additional minute patients spend in the ED (P = 0.003), on average. Emergency department wait times also had the largest effect size (0.210), indicating that they explain more of the variance in HA-CDI rates for patients entering through the ED than some of the best-known predictors of HA-CDI.

CONCLUSIONS

The relationship between ED wait times and eventual HA-CDI warrants further exploration. These findings suggest efforts to reduce ED wait times for admitted patients or more rigorous environmental cleanliness strategies in the ED, as possible avenues for HA-CDI prevention.

A passive monitoring tool using hospital administrative data enables earlier specific detection of healthcare-acquired infections

BACKGROUND

Healthcare-associated infections impose a significant burden on the healthcare system. Current methods for detecting these infections are constrained by combinations of high cost, long processing times and imperfect accuracy, reducing their effectiveness.

METHODS

This study examined whether the amount of time a patient spends on a ward with other patients clinically suspected of infection, termed 'co-presence', can be used as a tool to predict subsequent healthcare-associated infection. Compared with contact tracing, this leverages passively collected electronic data rather than manually collected data, allowing for improved monitoring. All 133,304 inpatient records between 2011 and 2015 were abstracted from a healthcare system in the UK. The area under the receiver-operator curve (AUROC) for each of five pathogens was calculated based on co-presence time, sensitivity and specificity of the test, and how much earlier co-presence would have predicted infection for the true-positive cases.

FINDINGS

For the five pathogens, AUROC ranged from 0.92 to 0.99, and was 0.52 for the negative control. Optimal cut-points of co-presence ranged from 25 to 59 h, and would have led to detection of true-positive cases up to an average of 1 day earlier.

INTERPRETATION

These findings show that co-presence time would help to predict healthcare-acquired infection, and would do so earlier than the current standard of care. Using this measure prospectively in hospitals based on real-time data could limit the consequences of infection, both by being able to treat individual infected patients earlier, and by preventing potential secondary infections stemming from the original infected patient.

Impact of the coronavirus disease 2019 (COVID-19) pandemic on nosocomial Clostridioides difficile infection

OBJECTIVES

The coronavirus disease 2019 (COVID-19) pandemic has induced a reinforcement of infection control measures in the hospital setting. Here, we assess the impact of the COVID-19 pandemic on the incidence of nosocomial Clostridioides difficile infection (CDI).

METHODS

We retrospectively compared the incidence density (cases per 10,000 patient days) of healthcare-facility-associated (HCFA) CDI in a tertiary-care hospital in Madrid, Spain, during the maximum incidence of COVID-19 (March 11 to May 11, 2020) with the same period of the previous year (control period). We also assessed the aggregate in-hospital antibiotic use (ie, defined daily doses [DDD] per 100 occupied bed days [BD]) and incidence density (ie, movements per 1,000 patient days) of patient mobility during both periods.

RESULTS

In total, 2,337 patients with reverse transcription-polymerase chain reaction-confirmed COVID-19 were admitted to the hospital during the COVID-19 period. Also, 12 HCFA CDI cases were reported at this time (incidence density, 2.68 per 10,000 patient days), whereas 34 HCFA CDI cases were identified during the control period (incidence density, 8.54 per 10,000 patient days) (P = .000257). Antibiotic consumption was slightly higher during the COVID-19 period (89.73 DDD per 100 BD) than during the control period (79.16 DDD per 100 BD). The incidence density of patient movements was 587.61 per 1,000 patient days during the control period and was significantly lower during the COVID-19 period (300.86 per 1,000 patient days) (P < .0001).

CONCLUSIONS

The observed reduction of ~70% in the incidence density of HCFA CDI in a context of no reduction in antibiotic use supports the importance of reducing nosocomial transmission by healthcare workers and asymptomatic colonized patients, reinforcing cleaning procedures and reducing patient mobility in the epidemiological control of CDI.

Modest Clostridiodes difficile infection prediction using machine learning models in a tertiary care hospital

Previous studies have shown promising results of machine learning (ML) models for predicting health outcomes. We develop and test ML models for predicting Clostridioides difficile infection (CDI) in hospitalized patients. This is a retrospective cohort study conducted during 2015-2017. All inpatients tested for C. difficile were included. CDI was defined as having a positive glutamate dehydrogenase and toxin results. We restricted analyses to the first record of C. difficile testing per patient. Of 3514 patients tested, 136 (4%) had CDI. Age and antibiotic use within 90 days before C. difficile testing were associated with CDI (P < 0.01). We tested 10 ML methods with and without resampling. Logistic regression, random forest and naïve Bayes models yielded the highest AUC ROC performance: 0.6. Predicting CDI was difficult in our cohort of patients tested for CDI. Multiple ML models yielded only modest results in a real-world population of hospitalized patients tested for CDI.

From one species to another: A review on the interaction between chemistry and microbiology in relation to cleaning in the built environment

Since the advent of soap, personal hygiene practices have revolved around removal, sterilization, and disinfection-both of visible soil and microscopic organisms-for a myriad of cultural, aesthetic, or health-related reasons. Cleaning methods and products vary widely in their recommended use, effectiveness, risk to users or building occupants, environmental sustainability, and ecological impact. Advancements in science and technology have facilitated in-depth analyses of the indoor microbiome, and studies in this field suggest that the traditional "scorched-earth cleaning" mentality-that surfaces must be completely sterilized and prevent microbial establishment-may contribute to long-term human health consequences. Moreover, the materials, products, activities, and microbial communities indoors all contribute to, or remove, chemical species to the indoor environment. This review examines the effects of cleaning with respect to the interaction of chemistry, indoor microbiology, and human health.

Repurposing Geographic Information Systems for Routine Hospital Infection Control

This chapter discusses the potential role of geographic information systems (GIS) for infection control within the hospital system. The chapter provides a brief overview of the role of GIS in public health and reviews current work applying these methods to the hospital setting. Finally, it outlines the potential opportunities and challenges for adapting GIS for use in the hospital setting for infection prevention. A targeted literature review is used to illustrate current use of GIS in the hospital setting. The discussion of complexity was compiled using the nonadoption, abandonment, scale-up, spread, and sustainability (NASSS) framework. Challenges and opportunities were then extracted from this exercise by the authors. There are multiple challenges to implementation of a Hospital GIS for infection prevention, mainly involving the domains of technology, organization, and adaptation. Use of a transdisciplinary approach can address many of these challenges. More research, specifically prospective, reproducible clinical trials, needs to be done to better assess the potential impact and effectiveness of a Hospital GIS in real-world settings. This chapter highlights a powerful but rarely used tool for infection prevention within the hospital. Given the importance of reducing hospital-acquired infection rates, it is vital to identify relevant methods from other fields that could be translated into the field of hospital epidemiology.

Novel Visualization of Clostridium difficile Infections in Intensive Care Units

BACKGROUND

Accurate and timely surveillance and diagnosis of healthcare-facility onset Clostridium difficile infection (HO-CDI) is vital to controlling infections within the hospital, but there are limited tools to assist with timely outbreak investigations.

OBJECTIVES

To integrate spatiotemporal factors with HO-CDI cases and develop a map-based dashboard to support infection preventionists (IPs) in performing surveillance and outbreak investigations for HO-CDI.

METHODS

Clinical laboratory results and Admit-Transfer-Discharge data for admitted patients over two years were extracted from the Information Warehouse of a large academic medical center and processed according to Center for Disease Control (CDC) National Healthcare Safety Network (NHSN) definitions to classify Clostridium difficile infection (CDI) cases by onset date. Results were validated against the internal infection surveillance database maintained by IPs in Clinical Epidemiology of this Academic Medical Center (AMC). Hospital floor plans were combined with HO-CDI case data, to create a dashboard of intensive care units. Usability testing was performed with a think-aloud session and a survey.

RESULTS

The simple classification algorithm identified all 265 HO-CDI cases from 1/1/15-11/30/15 with a positive predictive value (PPV) of 96.3%. When applied to data from 2014, the PPV was 94.6% All users "strongly agreed" that the dashboard would be a positive addition to Clinical Epidemiology and would enable them to present Hospital Acquired Infection (HAI) information to others more efficiently.

CONCLUSIONS

The CDI dashboard demonstrates the feasibility of mapping clinical data to hospital patient care units for more efficient surveillance and potential outbreak investigations.

Decontamination devices in health care facilities: Practical issues and emerging applications

"No-touch" decontamination devices are increasingly used as an adjunct to standard cleaning and disinfection in health care facilities. Although there is evidence that these devices are effective in reducing contamination, there are several areas of controversy regarding their use. This review addresses some of the questions frequently posed by infection prevention and environmental services personnel about decontamination devices.

Whole-genome sequencing reveals nosocomial Clostridioides difficile transmission and a previously unsuspected epidemic scenario

To trace the routes and frequencies of transmission of Clostridioides difficile in a tertiary-care hospital in Madrid (Spain), we sequenced the genomes from all C. difficile isolates collected over 36 months (2014-2016) that were indistinguishable from any other isolate by PCR ribotyping. From a total of 589 C. difficile infection cases, we cultivated and PCR-ribotyped 367 C. difficile isolates (62%), of which 265 were genome-sequenced. Based on close relatedness of successively collected isolates (≤2 SNPs difference in their genomes), whole-genome sequencing revealed a total of 17 independent, putative transmission clusters, caused by various C. difficile strains and each containing 2 to 18 cases, none of which had been detected previously by standard epidemiological surveillance. Proportions of linked isolates varied widely among PCR ribotypes, from 3% (1/36) for ribotype 014/020 to 60% (12/20) for ribotype 027, suggesting differential aptitudes for nosocomial spread. Remarkably, only a minority (17%) of transmission recipients had direct ward contact to their presumed donors and specific C. difficile genome types frequently went undetectable for several months before re-emerging later, suggesting reservoirs for the pathogen outside of symptomatic patients. Taken together, our analysis based on genome sequencing suggested considerable within-hospital epidemic spread of C. difficile, even though epidemiological data initially had been inconspicuous.

Spores on wheels: Wheelchairs are a potential vector for dissemination ofpathogens in healthcare facilities

In a hospital and affiliated long-term care facility, we found that shared wheelchairs were frequently contaminatedwith healthcare-associated pathogens, including Clostridium difficile spores. A network graph of 851 wheelchair transports over 3days demonstrated frequent movement between inpatient wards andoutpatient clinics, radiology, and physical therapy. These results highlight the potential for shared wheelchairs to serve as a vector for pathogen transmission.

A comparison of the efficacy of multiple ultraviolet light room decontamination devices in a radiology procedure room

Objective

To evaluate the efficacy of multiple ultraviolet (UV) light decontamination devices in a radiology procedure room.

Design

Laboratory evaluation.

Methods

We compared the efficacy of 8 UV decontamination devices with a 4-minute UV exposure time in reducing recovery of methicillin-resistant Staphylococcus aureus (MRSA), vancomycin-resistant Enterococcus (VRE), and Clostridium difficile spores on steel disk carriers placed at 5 sites on a computed tomography patient table. Analysis of variance was used to compare reductions for the different devices. A spectrometer was used to obtain irradiance measurements for the devices.

Results

Four standard vertical tower low-pressure mercury devices achieved 2 log10CFU or greater reductions in VRE and MRSA and ~1 log10CFU reductions in C. difficile spores, whereas a pulsed-xenon device resulted in less reduction in the pathogens (P<.001). In comparison to the vertical tower low-pressure mercury devices, equal or greater reductions in the pathogens were achieved by 3 nonstandard low-pressure mercury devices that included either adjustable bulbs that could be oriented directly over the exam table, a robotic base allowing movement along the side of the table during operation, or 3 vertical towers operated simultaneously. The low-pressure mercury devices produced primarily UV-C light, whereas the pulsed-xenon device produced primarily UV-A and UV-B light. The time required to move the devices from the corner of the room and set up for operation varied from 18 to 59 seconds.

Conclusions

Many currently available UV devices could provide an effective and efficient adjunct to manual cleaning and disinfection in radiology procedure rooms.

Sharing is not always a good thing: Use of a DNA marker to investigate the potential for ward-to-ward dissemination of healthcare-associated pathogens

A DNA marker inoculated onto portable equipment on a medical ward was disseminated to other wards when equipment was shared and to a physician work room and the hospital cafeteria by personnel. These results demonstrate the plausibility of pathogen transmission in healthcare facilities in the absence of shared ward exposure.