Spread of hospital-acquired infections: A comparison of healthcare networks

A Scoping Review of Multilevel Patient-Sharing Network Measures in Health Services Research

Social network analysis is the study of the structure of relationships between social entities. Access to health care administrative datasets has facilitated use of "patient-sharing networks" to infer relationships between health care providers based on the extent to which they have encounters with common patients. The structure and nature of patient-sharing relationships can reflect observed or latent aspects of health care delivery systems, such as collaboration and influence. We conducted a scoping review of peer-reviewed studies that derived patient-sharing network measure(s) in the analyses. There were 134 papers included in the full-text review. We identified and created a centralized resource of 118 measures and uncovered three major themes captured by them: Influential and Key Players, Care Coordination and Teamwork, and Network Structure and Access to Care. Researchers may use this review to inform their use of patient-sharing network measures and to guide the development of novel measures.

Impact of the SARS-CoV-2 pandemic on the hospital robustness to antibiotic-resistant bacteria spread in a large German university hospital

BACKGROUND

Patient transfers between hospital departments and wards frequently occur, and bring with them the risk of inter-department transmission of antibiotic-resistant bacteria (ARB). These bacteria form a risk to the patients already susceptible to colonisation and infection.

AIM

Goal of this study is to assess the impact of the SARS-CoV-2 pandemic on the intra-hospital network of a large German university hospital.

METHODS

Using data collected from the hospital between 2019 and 2023 we developed a model to represent an intra-hospital transfer network with all patient movements among all the wards, by creating a time-sliced temporal network for each month. We described the network and assessed its robustness against ARB spread by simulating outbreaks among wards.

FINDINGS

Over the years studied, we found that in April 2020, when many elective surgeries were cancelled due to the SARS-CoV-2 pandemic, the robustness of the network strongly increased in comparison to all other months. Despite the network being relatively stable over the study period, it was affected by an internal change of hospital structure due to a hospital merging event.

CONCLUSION

The intra-hospital transfer network was affected by external influences due to the pandemic, slowing down the potential spread of the nosocomial pathogens. The network was generally stable and quickly recovered, although an internal force affected the structure of the network. A better understanding of the influence of patient transfers will help to design intervention strategies against the spread of antimicrobial resistance within hospitals.

Healthcare as a driver, reservoir and amplifier of antimicrobial resistance: opportunities for interventions

Antimicrobial resistance (AMR) is a global health challenge that threatens humans, animals and the environment. Evidence is emerging for a role of healthcare infrastructure, environments and patient pathways in promoting and maintaining AMR via direct and indirect mechanisms. Advances in vaccination and monoclonal antibody therapies together with integrated surveillance, rapid diagnostics, targeted antimicrobial therapy and infection control measures offer opportunities to address healthcare-associated AMR risks more effectively. Additionally, innovations in artificial intelligence, data linkage and intelligent systems can be used to better predict and reduce AMR and improve healthcare resilience. In this Review, we examine the mechanisms by which healthcare functions as a driver, reservoir and amplifier of AMR, contextualized within a One Health framework. We also explore the opportunities and innovative solutions that can be used to combat AMR throughout the patient journey. We provide a perspective on the current evidence for the effectiveness of interventions designed to mitigate healthcare-associated AMR and promote healthcare resilience within high-income and resource-limited settings, as well as the challenges associated with their implementation.

Antimicrobial activity of cefepime-tazobactam combination against extended spectrum beta-lactamase and/or AmpC beta-lactamase- producing gram-negative bacilli

BACKGROUND

The problem of resistance to beta-lactam antibiotics, which is caused by ESBL and AmpC β-lactamases, is getting worse globally. Infections caused by bacterial isolates harboring these enzymes are difficult to treat with carbapenems being the sole effective treatment option for such infections. The objective of this study was to determine the frequency of ESBLs and AmpC-producing Gram-negative bacilli isolated from clinical specimens and to evaluate the sensitivity of cefepime-tazobactam combination against them.

METHODS

This is an observational cross-sectional study carried out on 100 Gram-negative bacilli at Theodor Bilharz Research Institute Hospital during the period from February 2015 to January 2016. ESBL production was screened by using the disc diffusion test followed by confirmation by the combined disc confirmatory test, the screening for AmpC production was conducted using the cefoxitin disc test, which was subsequently confirmed by the AmpC disc test. Isolates confirmed positive for ESBL and/ or AmpC production were investigated for their susceptibility to antibiotics.

RESULTS

Among 100 Gram-negative bacilli, 44 isolates were confirmed as ESBL producers by the combined disc confirmatory test out of 56 isolates that tested positive for ESBL production through the disc diffusion test. The presence of AmpC production was assessed using the cefoxitin disc test, 32 isolates were screened to be AmpC producers, and the AmpC disc test confirmed AmpC production in 9 isolates of them. Using the Mast® D68C set, 32 isolates were ESBL producers, 3 were AmpC producers, and 4 isolates were ESBL/AmpC co-producers. The highest sensitivity was to cefepime-tazobactam (91.48%) followed by the carbapenems.

CONCLUSION

Cefepime-tazobactam showed remarkable activity against ESBL and/or AmpC-producing Gram-negative bacilli and may be considered as a therapeutic alternative to carbapenems.

Antimicrobial utilization in Hajj 2022: An evaluation of quality indicators

BACKGROUND

The mass gathering in Hajj (Islamic pilgrimage) makes the spread of infectious diseases inevitable. Antibiotics are frequently prescribed during this season. We aimed to measure antimicrobial utilization during the 2022 Hajj and evaluate the practice using quality indicators.

METHODS

Antimicrobial utilization by Hajj medical facilities (77 primary clinics and 7 hospitals) was measured using the anatomic therapeutic classification defined daily dose (DDD) and DDD/1,000-inhabitant/day (DID), where inhabitants were the Hajj 2022 pilgrims (n = 899,353). Quality indicators included percentages of consumption of different antibiotic classes of the total consumption of antibacterials for systemic use in DID.

RESULTS

During Hajj, there was 87,173 outpatient visits and 740 hospitalizations (215 critically ill). Amoxicillin was the most prescribed antibiotic (DID=11.708) followed by azithromycin (DID=7.395). Penicillins fell in the second quartile (i.e., highly prescribed) with a quality indicator value (J01_CE%) of 48.149. The consumption of other antibacterials, including fluoroquinolones, fell in the first quartile (<25%). The overall ratio of broad- to narrow-spectrum antibiotic prescribing (J01_B/N) was 1.49.

CONCLUSION

Although the prescribing of β-lactams over fluoroquinolones indicates a good practice, clinicians should be reminded that most infections spreading in mass gatherings are viral; hence, do not require antibiotics. Implementation of antimicrobial stewardship is recommended to improve antimicrobial utilization.

Regional patient transfer patterns matter for the spread of hospital-acquired pathogens

Pathogens typically responsible for hospital-acquired infections (HAIs) constitute a major threat to healthcare systems worldwide. They spread via hospital (or hospital-community) networks by readmissions or patient transfers. Therefore, knowledge of these networks is essential to develop and test strategies to mitigate and control the HAI spread. Until now, no methods for comparing healthcare networks across different systems were proposed. Based on healthcare insurance data from four German federal states (Bavaria, Lower Saxony, Saxony and Thuringia), we constructed hospital networks and compared them in a systematic approach regarding population, hospital characteristics, and patient transfer patterns. Direct patient transfers between hospitals had only a limited impact on HAI spread. Whereas, with low colonization clearance rates, readmissions to the same hospitals posed the biggest transmission risk of all inter-hospital transfers. We then generated hospital-community networks, in which patients either stay in communities or in hospitals. We found that network characteristics affect the final prevalence and the time to reach it. However, depending on the characteristics of the pathogen (colonization clearance rate and transmission rate or even the relationship between transmission rate in hospitals and in the community), the studied networks performed differently. The differences were not large, but justify further studies.

Transmission of drug-resistant bacteria in a hospital-community model stratified by patient risk

A susceptible-infectious-susceptible (SIS) model for simulating healthcare-acquired infection spread within a hospital and associated community is proposed. The model accounts for the stratification of in-patients into two susceptibility-based risk groups. The model is formulated as a system of first-order ordinary differential equations (ODEs) with appropriate initial conditions. The mathematical analysis of this system is demonstrated. It is shown that the system has unique global solutions, which are bounded and non-negative. The basic reproduction number ([Formula: see text]) for the considered model is derived. The existence and the stability of the stationary solutions are analysed. The disease-free stationary solution is always present and is globally asymptotically stable for [Formula: see text], while for [Formula: see text] it is unstable. The presence of an endemic stationary solution depends on the model parameters and when it exists, it is globally asymptotically stable. The endemic state encompasses both risk groups. The endemic state within only one group only is not possible. In addition, for [Formula: see text] a forward bifurcation takes place. Numerical simulations, based on the anonymised insurance data, are also presented to illustrate theoretical results.

Biocidal activity of multifunctional cuprite-doped anion exchanger - Influence of bacteria type and medium composition

The study presents unconventional, bifunctional, heterogeneous antimicrobial agents - Cu2O-loaded anion exchangers. The synergetic effect of a cuprous oxide deposit and polymeric support with trimethyl ammonium groups was studied against the reference strains of Enterococcus faecalis ATCC 29212 and Pseudomonas aeruginosa ATCC 27853. Biological testing (minimum bactericidal concentration, MBC), time- and dose-dependent bactericidal effect (under different conditions - medium composition and static/dynamic culture) demonstrated promising antimicrobial activity and confirmed its multimode character. The standard values of MBC, for all studied hybrid polymers and bacteria, were similar (64-128 mg/mL). However, depending on the medium conditions, due to the copper release into the bulk solution, bacteria were actively killed even at much lower doses of the hybrid polymer (25 mg/mL) and low Cu(II) concentrations in solution (0.01 mg/L). Simultaneously, confocal microscopic studies confirmed the effective inhibition of bacterial adhesion and biofilm formation on their surface. The studies conducted under different conditions showed also the influence of the structure and physical properties of studied materials on the biocidal efficacy and an antimicrobial action mechanism was proposed that could be significantly affected by electrostatic interactions and copper release to the solution. Although the antibacterial activity was also dependent on various strategies of bacterial cell resistance to heavy metals present in the aqueous medium, the studied hybrid polymers are versatile and efficient biocidal agents against bacteria of both types, Gram-positive and Gram-negative. Therefore, they can be a convenient alternative for point-of-use water disinfection systems providing water quality in medical devices such as dental units, spa equipment, and aesthetic devices used in the cosmetic sector.

Physician Attitude toward Their Attires and Laundering Habit Changes during the COVID-19: A Cross-Sectional Survey in a Tertiary Care Center

Background  Patient safety is of utmost importance and every effort is to be made to reduce the risk of hospital-acquired infection. Contaminated attire is proposed as a mode of hospital infections spread. This study aims to assess the laundering habits, the perception of healthcare workers toward the contamination of their attire, and the effect of coronavirus disease 2019 (COVID-19) pandemic on their cleaning practices in non-operative settings. Methods  This is a cross-sectional study conducted using a self-administered questionnaire which was distributed among physicians at King Abdul-Aziz Medical city, Riyadh. The questionnaire queried the physicians about their laundering habits, knowledge toward their attire, and the difference in cleaning practices after the emergence of COVID-19. Results  Out of 220 questionnaires distributed, 192 physicians responded. Majority of physicians were male (54%) and were in the 20 to 30 age group. Female gender was significantly associated with the frequency of uniform washing ( p- value < 0.0001) and place of cleaning (home vs. outside home) ( p- value <0.0001). Physicians in intensive care were more likely to take off their uniforms daily before leaving the hospital compared to others ( p- value of 0.018). Most physicians did not prefer to use the hospital laundry system for cleaning their uniforms but consultants were the most to use it. COVID-19 pandemic led to changes in washing habits in 108 physicians (60%). Conclusion  Majority of physicians accepted washing their uniforms multiple times per week and their washing habits increased during the COVID-19 pandemic. Female gender and younger physician both were associated with increasing washing habits.

Innovation for infection prevention and control-revisiting Pasteur's vision

Louis Pasteur has long been heralded as one of the fathers of microbiology and immunology. Less known is Pasteur's vision on infection prevention and control (IPC) that drove current infection control, public health, and much of modern medicine and surgery. In this Review, we revisited Pasteur's pioneering works to assess progress and challenges in the process and technological innovation of IPC. We focused on Pasteur's far-sighted conceptualisation of the hospital as a reservoir of microorganisms and amplifier of transmission, aseptic technique in surgery, public health education, interdisciplinary working, and the protection of health services and patients. Examples from across the globe help inform future thinking for IPC innovation, adoption, scale up and sustained use.

Cross-site collaboration on infection prevention and control research—room for improvement? A 7-year comparative study in five European countries

Background

The spread of SARS-CoV-2, multidrug-resistant organisms and other healthcare-associated pathogens represents supra-regional challenges for infection prevention and control (IPC) specialists in every European country. To tackle these problems, cross-site research collaboration of IPC specialists is very important. This study assesses the extent and quality of national research collaborations of IPC departments of university hospitals located in Austria, England, France, Germany, and the Netherlands, identifies network gaps, and provides potential solutions.

Methods

Joint publications of IPC heads of all university hospitals of the included countries between 1st of June 2013 until 31st of May 2020 were collected by Pubmed/Medline search. Further, two factors, the journal impact factor and the type/position of authorship, were used to calculate the Scientific Collaboration Impact (SCI) for all included sites; nationwide network analysis was performed.

Results

In five European countries, 95 sites and 125 responsible leaders for IPC who had been in charge during the study period were identified. Some countries such as Austria have only limited national research cooperations, while the Netherlands has established a gapless network. Most effective collaborating university site of each country were Lille with an SCI of 1146, Rotterdam (408), Berlin (268), Sussex (204), and Vienna/Innsbruck (18).

Discussion

The present study indicates major differences and room for improvement in IPC research collaborations within each country and underlines the potential and importance of collaborating in IPC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13756-022-01176-x.

Efficacy and In Vitro Activity of Novel Antibiotics for Infections With Carbapenem-Resistant Gram-Negative Pathogens

Infections by Gram-negative multi-drug resistant (MDR) bacterial species are difficult to treat using available antibiotics. Overuse of carbapenems has contributed to widespread resistance to these antibiotics; as a result, carbapenem-resistant Enterobacterales (CRE), A. baumannii (CRAB), and P. aeruginosa (CRPA) have become common causes of healthcare-associated infections. Carbapenems, tigecycline, and colistin are the last resource antibiotics currently used; however, multiple reports of resistance to these antimicrobial agents have been documented worldwide. Recently, new antibiotics have been evaluated against Gram-negatives, including plazomicin (a new aminoglycoside) to treat CRE infection, eravacycline (a novel tetracycline) with in vitro activity against CRAB, and cefiderocol (a synthetic conjugate) for the treatment of nosocomial pneumonia by carbapenem-non-susceptible Gram-negative isolates. Furthermore, combinations of known β-lactams with recently developed β-lactam inhibitors, such as ceftazidime-avibactam, ceftolozane-tazobactam, ceftazidime-tazobactam, and meropenem-vaborbactam, has been suggested for the treatment of infections by extended-spectrum β-lactamases, carbapenemases, and AmpC producer bacteria. Nonetheless, they are not active against all carbapenemases, and there are reports of resistance to these combinations in clinical isolates.This review summarizes and discusses the in vitro and clinical evidence of the recently approved antibiotics, β-lactam inhibitors, and those in advanced phases of development for treating MDR infections caused by Gram-negative multi-drug resistant (MDR) bacterial species.

Making sense of the French public hospital system: a network-based approach to hospital clustering using unsupervised learning methods

BACKGROUND

Hospitals in the public and private sectors tend to join larger organizations to form hospital groups. This increasingly frequent mode of functioning raises the question of how countries should organize their health system, according to the interactions already present between their hospitals. The objective of this study was to identify distinctive profiles of French hospitals according to their characteristics and their role in the French hospital network.

METHODS

Data were extracted from the national hospital database for year 2016. The database was restricted to public hospitals that practiced medicine, surgery or obstetrics. Hospitals profiles were determined using the k-means method. The variables entered in the clustering algorithm were: the number of stays, the effective diversity of hospital activity, and a network-based mobility indicator (proportion of stays followed by another stay in a different hospital of the same Regional Hospital Group within 90 days).

RESULTS

Three hospital groups were identified by the clustering algorithm. The first group was constituted of 34 large hospitals (median 82,100 annual stays, interquartile range 69,004 - 117,774) with a very diverse activity. The second group contained medium-sized hospitals (with a median of 258 beds, interquartile range 164 - 377). The third group featured less diversity regarding the type of stay (with a mean of 8 effective activity domains, standard deviation 2.73), a smaller size and a higher proportion of patients that subsequently visited other hospitals (11%). The most frequent type of patient mobility occurred from the hospitals in group 2 to the hospitals in group 1 (29%). The reverse direction was less frequent (19%).

CONCLUSIONS

The French hospital network is organized around three categories of public hospitals, with an unbalanced and disassortative patient flow. This type of organization has implications for hospital planning and infectious diseases control.

Assessment of Hospital Characteristics and Interhospital Transfer Patterns of Adults With Emergency General Surgery Conditions

Importance

Although patients with emergency general surgery (EGS) conditions frequently undergo interhospital transfers, the transfer patterns and associated factors are not well understood.

Objective

To examine whether patients with EGS conditions are consistently directed to hospitals with more resources and better outcomes.

Design, Setting, and Participants

This cohort study performed a network analysis of interhospital transfers among adults with EGS conditions from January 1 to December 31, 2016. The analysis used all-payer claims data from the 2016 Healthcare Cost and Utilization Project state inpatient and emergency department databases in 8 states. A total of 728 hospitals involving 85 415 transfers of 80 307 patients were included. Patients were eligible for inclusion if they were 18 years or older and had an acute care hospital encounter with a diagnosis of an EGS condition as defined by the American Association for the Surgery of Trauma. Data were analyzed from January 1, 2020, to June 17, 2021.

Exposures

Hospital-level measures of size (total bed capacity), resources (intensive care unit [ICU] bed capacity, teaching status, trauma center designation, and presence of trauma and/or surgical critical care fellowships), EGS volume (annual EGS encounters), and EGS outcomes (risk-adjusted failure to rescue and in-hospital mortality).

Main Outcomes and Measures

The main outcome was hospital-level centrality ratio, defined as the normalized number of incoming transfers divided by the number of outgoing transfers. A higher centrality ratio indicated more incoming transfers per outgoing transfer. Multivariable regression analysis was used to test the hypothesis that a higher hospital centrality ratio would be associated with more resources, higher volume, and better outcomes.

Results

Among 80 307 total patients, the median age was 63 years (interquartile range [IQR], 50-75 years); 52.1% of patients were male and 78.8% were White. The median number of outgoing and incoming transfers per hospital were 106 (IQR, 61-157) and 36 (IQR, 8-137), respectively. A higher log-transformed centrality ratio was associated with more resources, such as higher ICU capacity (eg, >25 beds vs 0-10 beds: β = 1.67 [95% CI, 1.16-2.17]; P < .001), and higher EGS volume (eg, quartile 4 [highest] vs quartile 1 [lowest]: β = 0.78 [95% CI, 0-1.57]; P = .01). However, a higher log-transformed centrality ratio was not associated with better outcomes, such as lower in-hospital mortality (eg, quartile 4 [highest] vs quartile 1 [lowest]: β = 0.30 [95% CI, -0.09 to 0.68]; P = .83) and lower failure to rescue (eg, quartile 4 [highest] vs quartile 1 [lowest]: β = -0.50 [95% CI, -1.13 to 0.12]; P = .27).

Conclusions and Relevance

In this study, EGS transfers were directed to high-volume hospitals with more resources but were not necessarily directed to hospitals with better clinical outcomes. Optimizing transfer destination in the interhospital transfer network has the potential to improve EGS outcomes.

How does innovative technology impact nursing in infectious diseases and infection control? A scoping review

AIM

Considering the increasing number of emerging infectious diseases, innovative approaches are strongly in demand. Additionally, research in this field has expanded exponentially. Thus, faced with this diverse information, we aim to clarify key concepts and knowledge gaps of technology in nursing and the field of infectious diseases.

DESIGN

This scoping review followed the methodology of scoping review guidance from Arksey and O'Malley.

METHODS

Six databases were searched systematically (PubMed, Web of Science, IEEE Explore, EBSCOhost, Cochrane Library and Summon). After the removal of duplicates, 532 citations were retrieved and 77 were included in the analysis.

RESULTS

We identified five major trends in technology for nursing and infectious diseases: artificial intelligence, the Internet of things, information and communications technology, simulation technology and e-learning. Our findings indicate that the most promising trend is the IoT because of the many positive effects validated in most of the reviewed studies.

Effects of incomplete inter-hospital network data on the assessment of transmission dynamics of hospital-acquired infections

In the year 2020, there were 105 different statutory insurance companies in Germany with heterogeneous regional coverage. Obtaining data from all insurance companies is challenging, so that it is likely that projects will have to rely on data not covering the whole population. Consequently, the study of epidemic spread in hospital referral networks using data-driven models may be biased. We studied this bias using data from three German regional insurance companies covering four federal states: AOK (historically “general local health insurance company”, but currently only the abbreviation is used) Lower Saxony (in Federal State of Lower Saxony), AOK Bavaria (in Bavaria), and AOK PLUS (in Thuringia and Saxony). To understand how incomplete data influence network characteristics and related epidemic simulations, we created sampled datasets by randomly dropping a proportion of patients from the full datasets and replacing them with random copies of the remaining patients to obtain scale-up datasets to the original size. For the sampled and scale-up datasets, we calculated several commonly used network measures, and compared them to those derived from the original data. We found that the network measures (degree, strength and closeness) were rather sensitive to incompleteness. Infection prevalence as an outcome from the applied susceptible-infectious-susceptible (SIS) model was fairly robust against incompleteness. At incompleteness levels as high as 90% of the original datasets the prevalence estimation bias was below 5% in scale-up datasets. Consequently, a coverage as low as 10% of the local population of the federal state population was sufficient to maintain the relative bias in prevalence below 10% for a wide range of transmission parameters as encountered in clinical settings. Our findings are reassuring that despite incomplete coverage of the population, German health insurance data can be used to study effects of patient traffic between institutions on the spread of pathogens within healthcare networks.

Patterns of patients’ transfer between different hospitals contribute crucially to the risk of hospital-acquired infections (HAIs) in the health care system. To quantify this risk, network models can be applied. The estimated risk can be inaccurate in the case of incomplete data on hospital admissions, which can be a consequence of the multiplicity of insurance companies as it is the case in Germany. To develop a better understanding of how incompleteness of data affects network measures and the simulated spread of HAI, we compared those measures derived from sampled, scale-up and original data, based on hospitalization data from three AOK insurance companies. We found that common network measures were affected by incompleteness, but the simulated prevalence as a measure of epidemic spread in the network was robust over a large range of incompleteness proportions. Epidemics and the transition of the infectious diseases may be modelled on hospital data with a coverage as low as 10% of the local population, whilst maintaining accuracy to within 10% of the true population prevalence.

Relevance of intra-hospital patient movements for the spread of healthcare-associated infections within hospitals - a mathematical modeling study

The aim of this study is to analyze patient movement patterns between hospital departments to derive the underlying intra-hospital movement network, and to assess if movement patterns differ between patients at high or low risk of colonization. For that purpose, we analyzed patient electronic medical record data from five hospitals to extract information on risk stratification and patient intra-hospital movements. Movement patterns were visualized as networks, and network centrality measures were calculated. Next, using an agent-based model where agents represent patients and intra-hospital patient movements were explicitly modeled, we simulated the spread of multidrug resistant enterobacteriacae (MDR-E) inside a hospital. Risk stratification of patients according to certain ICD-10 codes revealed that length of stay, patient age, and mean number of movements per admission were higher in the high-risk groups. Movement networks in all hospitals displayed a high variability among departments concerning their network centrality and connectedness with a few highly connected departments and many weakly connected peripheral departments. Simulating the spread of a pathogen in one hospital network showed positive correlation between department prevalence and network centrality measures. This study highlights the importance of intra-hospital patient movements and their possible impact on pathogen spread. Targeting interventions to departments of higher (weighted) degree may help to control the spread of MDR-E. Moreover, when the colonization status of patients coming from different departments is unknown, a ranking system based on department centralities may be used to design more effective interventions that mitigate pathogen spread.

Pathogens including multidrug resistant enterobacteriacae (MDR-E) inside hospital settings are associated with higher morbidity, mortality, and healthcare costs. Better understanding of the transmission routes of these pathogens is required to develop targeted and efficient measures to contain the spread of MDR-E in a hospital. We analyzed datasets from five hospitals in different countries to explore patient movement patterns between departments of these hospitals (intra-hospital movements). We assessed whether movement patterns differ between patients at high or low risk of colonization. Our results show that in every intra-hospital network, there exist a few departments which are strongly connected and many peripheral departments which are loosely connected. High-risk patients stay on average longer in the hospital, and move more frequently between departments than low-risk patients. Targeting interventions to strongly connected departments may help to reduce pathogen spread inside the hospital. To explore this, we simulated the spread of MDR-E inside one hospital using an agent-based model that includes patient movements. In the simulations, we found positive correlations between departments’ prevalence and network characteristics such as degree and weighted degree, thus highlighting the importance of targeting interventions to departments of higher (weighted) degree to control the spread of MDR-E.

Interfacility patient sharing and Clostridioides difficile infection incidence in the Ontario hospital system: A 13-year cohort study

OBJECTIVE

Interfacility patient movement plays an important role in the dissemination of antimicrobial-resistant organisms throughout healthcare systems. We evaluated how 3 alternative measures of interfacility patient sharing were associated with C. difficile infection incidence in Ontario acute-care facilities.

DESIGN

The cohort included adult acute-care facility stays of ≥3 days between April 2003 and March 2016. We measured 3 facility-level metrics of patient sharing: general patient importation, incidence-weighted patient importation, and C. difficile case importation. Each of the 3 patient-sharing metrics were examined against the incidence of C. difficile infection in the facility per 1,000 stays, using Poisson regression models.

RESULTS

The analyzed cohort included 6.70 million stays at risk of C. difficile infection across 120 facilities. Over the 13-year period, we included 62,189 new cases of healthcare-associated CDI (incidence, 9.3 per 1,000 stays). After adjustment for facility characteristics, general importation was not strongly associated with C. difficile infection incidence (risk ratio [RR] per doubling, 1.10; 95% confidence interval [CI], 0.97-1.24; proportional change in variance [PCV], -2.0%). Incidence-weighted (RR per doubling, 1.18; 95% CI, 1.06-1.30; PCV, -8.4%) and C. difficile case importation (RR per doubling, 1.43; 95% CI, 1.29-1.58; PCV, -30.1%) were strongly associated with C. difficile infection incidence.

CONCLUSIONS

In this 13-year study of acute-care facilities in Ontario, interfacility variation in C. difficile infection incidence was associated with importation of patients from other high-incidence acute-care facilities or specifically of patients with a recent history of C. difficile infection. Regional infection control strategies should consider the potential impact of importation of patients at high risk of C. difficile shedding from outside facilities.

Modelling pathogen spread in a healthcare network: Indirect patient movements

Inter-hospital patient transfers (direct transfers) between healthcare facilities have been shown to contribute to the spread of pathogens in a healthcare network. However, the impact of indirect transfers (patients re-admitted from the community to the same or different hospital) is not well studied. This work aims to study the contribution of indirect transfers to the spread of pathogens in a healthcare network. To address this aim, a hybrid network–deterministic model to simulate the spread of multiresistant pathogens in a healthcare system was developed for the region of Lower Saxony (Germany). The model accounts for both, direct and indirect transfers of patients. Intra-hospital pathogen transmission is governed by a SIS model expressed by a system of ordinary differential equations. Our results show that the proposed model reproduces the basic properties of healthcare-associated pathogen spread. They also show the importance of indirect transfers: restricting the pathogen spread to direct transfers only leads to 4.2% system wide prevalence. However, adding indirect transfers leads to an increase in the overall prevalence by a factor of 4 (18%). In addition, we demonstrated that the final prevalence in the individual healthcare facilities depends on average length of stay in a way described by a non-linear concave function. Moreover, we demonstrate that the network parameters of the model may be derived from administrative admission/discharge records. In particular, they are sufficient to obtain inter-hospital transfer probabilities, and to express the patients’ transfers as a Markov process. Using the proposed model, we show that indirect transfers of patients are equally or even more important as direct transfers for the spread of pathogens in a healthcare network.

Direct patient transfers between hospitals have been shown to play an important role in the spread of pathogens in a healthcare network. However, readmission of patients from the community (indirect transfers) to the same or a different hospital is not well studied, and its role for the spread of pathogens in a healthcare network is not quantified. In this work, we developed a network model of a healthcare system to study the impact of indirect transfers on the prevalence in the individual hospitals as well as in the overall healthcare system. The model includes both, direct and indirect transfers of patients between the healthcare facilities due to transferring as well as readmission of infectious (colonized or infected) patients. Our results show that the readmission of patients (indirect transfers), either to the same or different facility, is an important potential channel of pathogen transmission. Such indirect transfers are of no less importance than direct patient transfers in controlling the spread of pathogens in a healthcare network.

Modelling how antimicrobial resistance spreads between wards

Moving patients between wards and prescribing high levels of antibiotics increases the spread of bacterial infections that are resistant to treatment in hospitals.

Impact of inter-hospital transfers on the prevalence of resistant pathogens in a hospital-community system

The spread of resistant bacteria in hospitals is an increasing problem worldwide. Transfers of patients, who may be colonized with resistant bacteria, are considered to be an important driver of promoting resistance. Even though transmission rates within a hospital are often low, readmissions of patients who were colonized during an earlier hospital stay lead to repeated introductions of resistant bacteria into hospitals. We developed a mathematical model that combines a deterministic model for within-hospital spread of pathogens, discharge to the community and readmission, with a hospital-community network simulation of patient transfers between hospitals. Model parameters used to create the hospital-community network are obtained from two health insurance datasets from Germany. For parameter values representing transmission of resistant Enterobacteriaceae, we compute estimates for the single admission reproduction numbers R_A and the basic reproduction numbers R₀ per hospital-community pair. We simulate the spread of colonization through the network of hospitals, and investigate how increasing connectedness of hospitals through the network influences the prevalence in the hospital-community pairs. We find that the prevalence in hospitals is determined by their R_A and R₀ values. Increasing transfer rates between network nodes tend to lower the overall prevalence in the network by diluting the high prevalence of hospitals with high R₀ to hospitals where persistent spread is not possible. We conclude that hospitals with high reproduction numbers represent a continuous source of risk for importing resistant pathogens for hospitals with otherwise low levels of transmission. Moreover, high risk hospital-community nodes act as reservoirs of pathogens in a densely connected network.

Assessing the role of inter-facility patient transfer in the spread of carbapenemase-producing Enterobacteriaceae: the case of France between 2012 and 2015

The spread of carbapenemase-producing Enterobacteriaceae (CPE) in healthcare settings is a major public health threat that has been associated with cross-border and local patient transfers between healthcare facilities. Since the impact of transfers on spread may vary, our study aimed to assess the contribution of a patient transfer network on CPE incidence and spread at a countrywide level, with a case study of France from 2012 to 2015. Our results suggest a transition in 2013 from a CPE epidemic sustained by internationally imported episodes to an epidemic sustained by local transmission events through patient transfers. Incident episodes tend to occur within close spatial distance of their potential infector. We also observe an increasing frequency of multiple spreading events, originating from a limited number of regional hubs. Consequently, coordinated prevention and infection control strategies should focus on transfers of carriers of CPE to reduce regional and inter-regional transmission.

Candida auris Bloodstream Infections in Russia

Candida auris-a fungus (yeast) that can cause hospital outbreaks was first recognized in 2009. The authors report data on 38 cases of C. auris bloodstream infections in multidisciplinary hospitals situated in two distantly located regions of Russia, considering predisposing factors, antifungal susceptibility of isolates, treatment, and outcomes. Interhospital transfers of patients and labor migration contributed to the spread of C. auris. The South Asian lineage of the studied strains was indicated by K143R substitution in ERG11 gene and phylogenetic analysis of internal transcribed spacer and D1-D2 domain. All isolates from C. auris candidemia cases were susceptible to echinocandins. High-level resistance to fluconazole and resistance to amphotericin B were present in the majority of strains. The overall all-cause mortality rate in C. auris bloodstream infections was 55.3% and the 30-day all-cause mortality rate 39.5%. The attributable mortality was 0%. Eradication of C. auris from blood was associated with the favourable outcomes in patients. It was achieved irrespective of whether antifungal preparations within or outside the susceptibility range were administered. Further international surveillance and studies providing consensus guidelines for the management of C. auris infections are needed.

Simulating transmission of ESKAPE pathogens plus C. difficile in relevant clinical scenarios

BACKGROUND

The prevalence of healthcare-acquired infections (HAI) and rising levels of antimicrobial resistance places significant economic and public health burdens on modern healthcare systems. A group of highly drug resistant pathogens known as the ESKAPE pathogens, along with C. difficile, are the leading causes of HAIs. Interactions between patients, healthcare workers, and environmental conditions impact disease transmission. Studying pathogen transfer under varying contact scenarios in a controlled manner is critical for understanding transmission and disinfectant strategies. In lieu of human subject research, this method has the potential to contribute to modeling the routes of pathogen transmission in healthcare settings.

METHODS

To overcome these challenges, we have developed a method that utilizes a synthetic skin surrogate to model both direct (skin-to-skin) and indirect (skin-to fomite-to skin) pathogen transfer between infected patients and healthy healthcare workers. This surrogate material includes a background microbiome community simulating typical human skin flora to more accurately mimic the effects of natural flora during transmission events.

RESULTS

We demonstrate the ability to modulate individual bacterial concentrations within this microbial community to mimic bacterial concentrations previously reported on the hands of human subjects. We also explore the effect of various decontamination approaches on pathogen transfer between human subjects, such as the use of handwashing or surface disinfectants. Using this method, we identify a potential outlier, S. aureus, that may persist and retain viability in specific transfer conditions better than the overall microbial community during decontamination events.

CONCLUSIONS

Our work describes the development of an in vitro method that uses a synthetic skin surrogate with a defined background microbiota to simulate skin-to-skin and skin-to fomite-to skin contact scenarios. These results illustrate the value of simulating a holistic microbial community for transfer studies by elucidating differences in different pathogen transmission rates and resistance to common decontamination practices. We believe this method will contribute to improvements in pathogen transmission modeling in healthcare settings and increase our ability to assess the risk associated with HAIs, although additional research is required to establish the degree of correlation of pathogen transmission by skin or synthetic alternatives.

Spread of Carbapenem-Resistant Klebsiella pneumoniae in Hub and Spoke Connected Health-Care Networks: A Case Study from Italy

The study describes the spread of carbapenem-resistant Klebsiella pneumoniae (CRKP) in a regional healthcare network in Italy. The project included several stages: (1) Establishment of a laboratory-based regional surveillance network, including all the acute care hospitals of the Marches Region (n = 20). (2) Adoption of a shared protocol for the surveillance of Multi-Drug Resistant Organisms (MDROs). Only the first CRKP isolate for each patient has been included in the surveillance in each hospital. The anonymous tracking of patients, and their subsequent microbial records within the hospital network, allowed detection of networks of inter-hospital exchange of CRKP and its comparison with transfer of patients within the hospital network. Pulsed-Field Gel Electrophoresis (PFGE) analysis has been used to study selected isolates belonging to different hospitals. 371,037 admitted patients have been included in the surveillance system. CRKP has shown an overall incidence rate of 41.0 per 100,000 days of stay (95% confidence interval, CI 38.5–43.5/100,000 DOS), a CRKP incidence rate of isolation in blood of 2.46/100,000 days of stay (95% CI 1.89–3.17/100,000 days of stay (DOS) has been registered; significant variability has been registered in facilities providing different levels of care. The network of CRKP patients’ exchange was correlated to that of the healthcare organization, with some inequalities and the identification of bridges in CRKP transfers. More than 73% of isolates were closely related. Patients’ exchange was an important route of spread of antimicrobial resistance, highlighting the pivotal role played by the hub, and selected institution to be used in prioritizing infection control efforts.

Using hospital network-based surveillance for antimicrobial resistance as a more robust alternative to self-reporting

Hospital performance is often measured using self-reported statistics, such as the incidence of hospital-transmitted micro-organisms or those exhibiting antimicrobial resistance (AMR), encouraging hospitals with high levels to improve their performance. However, hospitals that increase screening efforts will appear to have a higher incidence and perform poorly, undermining comparison between hospitals and disincentivising testing, thus hampering infection control. We propose a surveillance system in which hospitals test patients previously discharged from other hospitals and report observed cases. Using English National Health Service (NHS) Hospital Episode Statistics data, we analysed patient movements across England and assessed the number of hospitals required to participate in such a reporting scheme to deliver robust estimates of incidence. With over 1.2 million admissions to English hospitals previously discharged from other hospitals annually, even when only a fraction of hospitals (41/155) participate (each screening at least 1000 of these admissions), the proposed surveillance system can estimate incidence across all hospitals. By reporting on other hospitals, the reporting of incidence is separated from the task of improving own performance. Therefore the incentives for increasing performance can be aligned to increase (rather than decrease) screening efforts, thus delivering both more comparable figures on the AMR problems across hospitals and improving infection control efforts.

Host contact dynamics shapes richness and dominance of pathogen strains

The interaction among multiple microbial strains affects the spread of infectious diseases and the efficacy of interventions. Genomic tools have made it increasingly easy to observe pathogenic strains diversity, but the best interpretation of such diversity has remained difficult because of relationships with host and environmental factors. Here, we focus on host-to-host contact behavior and study how it changes populations of pathogens in a minimal model of multi-strain interaction. We simulated a population of identical strains competing by mutual exclusion and spreading on a dynamical network of hosts according to a stochastic susceptible-infectious-susceptible model. We computed ecological indicators of diversity and dominance in strain populations for a collection of networks illustrating various properties found in real-world examples. Heterogeneities in the number of contacts among hosts were found to reduce diversity and increase dominance by making the repartition of strains among infected hosts more uneven, while strong community structure among hosts increased strain diversity. We found that the introduction of strains associated with hosts entering and leaving the system led to the highest pathogenic richness at intermediate turnover levels. These results were finally illustrated using the spread of Staphylococcus aureus in a long-term health-care facility where close proximity interactions and strain carriage were collected simultaneously. We found that network structural and temporal properties could account for a large part of the variability observed in strain diversity. These results show how stochasticity and network structure affect the population ecology of pathogens and warn against interpreting observations as unambiguous evidence of epidemiological differences between strains.

Highly drug-resistant bacteria: Is intra- and inter-hospital communication optimal?

OBJECTIVES

Communication represents a key component of the control of highly drug-resistant bacteria (HDRB) in healthcare settings. This survey assessed communication strategies developed and adopted in a large hospital network.

METHODS

An online survey was sent to 83 infection control specialists working in hospitals of the Pays de la Loire region, France, in June 2016. Internal and external systems of identification and communication of HDRB status (colonized and contact patients) were assessed at the following steps of the hospital pathway: patient admission, during the stay, at discharge, and at readmission.

RESULTS

Sixty-one hospitals (73%) participated in the survey: 31 (51%) had recently managed colonized patients and 51 (93%) had recently managed contact patients. At patient admission, 28 (46%) hospitals had an identification system for repatriated patients. During hospital stay, the colonized or contact status was informed in computerized patient records for 47/57 (82%) and 43 (75%) hospitals, respectively. At patient discharge, 56/61 (92%) hospitals declared transmitting the HDRB status to the downstream ward. Twenty-six and 25/60 (43% and 42%) hospitals had an automated alert system at readmission of colonized or contact patients, respectively. This strategy met the expectations of 15/61 (26%) infection control specialists.

CONCLUSION

Efforts are still required in terms of communication for HDRB control. Sharing experiences and tools developed by hospitals may be beneficial for the entire hospital network.

Intensive Patient Treatment

Intensive care units (ICUs) are treating hospital’s poorest patients that need medical assistance during the most extreme period of their life. Intensive patients are treated with extensive invasive procedures, which may cause a risk of hospital infections in 10–30% of the cases. More than half of these infections can be prevented. The patients are often admitted directly from outside the hospital or from abroad with trauma after accidents, serious heart and lung conditions, sepsis and other life-threatening diseases. Infection or carrier state of microbes is often unknown on arrival and poses a risk of transmission to other patients, personnel and the environment. Patients that are transferred between different healthcare levels and institutions with unknown infection may be a particular risk for other patients. In spite of the serious state of the patients, many ICUs have few resources and are overcrowded and understaffed, with a lack of competent personnel. ICU should have a large enough area and be designed, furnished and staffed for a good, safe and effective infection control. The following chapter is focused on practical measures to reduce the incidence of infections among ICU patients.

Inference and control of the nosocomial transmission of methicillin-resistant Staphylococcus aureus

Methicillin-resistant Staphylococcus aureus (MRSA) is a continued threat to human health in both community and healthcare settings. In hospitals, control efforts would benefit from accurate estimation of asymptomatic colonization and infection importation rates from the community. However, developing such estimates remains challenging due to limited observation of colonization and complicated transmission dynamics within hospitals and the community. Here, we develop an inference framework that can estimate these key quantities by combining statistical filtering techniques, an agent-based model, and real-world patient-to-patient contact networks, and use this framework to infer nosocomial transmission and infection importation over an outbreak spanning 6 years in 66 Swedish hospitals. In particular, we identify a small number of patients with disproportionately high risk of colonization. In retrospective control experiments, interventions targeted to these individuals yield a substantial improvement over heuristic strategies informed by number of contacts, length of stay and contact tracing.

Evaluation of the Inter- and Intrahospital Spread of Multidrug Resistant Gram-Negative Bacteria in Lithuanian Hospitals

Spread of multidrug-resistant pathogenic bacteria became one of the greatest threats in healthcare worldwide. It is generally accepted that both inter- and intrahospital transmissions of these bacteria contribute significantly to this problem. The purpose of the current study was the evaluation of the inter- and intrahospital spread of multidrug resistant Gram-negative pathogenic bacteria in Lithuania. Clinical isolates of Acinetobacter sp., Escherichia coli, Klebsiella pneumoniae, and Pseudomonas aeruginosa were subjected for the screening for extended spectrum β-lactamase, carbapenemase, as well as plasmid-mediated AmpC β-lactamase genes. BOX-PCR genotyping was used for the genotyping of these isolates. Our results show that all four pathogens are involved in the intra- and/or interhospital dissemination between the Lithuanian healthcare institutions. The level of transmissions differed between pathogens, and the worst situation was detected for Acinetobacter sp. followed by E. coli. In almost all cases, transmissible strains had at least one gene conferring β-lactam resistance, thereby contributing to the dissemination of the resistance determinants in and between Lithuanian hospitals. Our study clearly demonstrated that immediate actions, more effective strategy, and surveillance are needed to confine and prevent further spread of multidrug resistant Gram-negative pathogenic bacteria in Lithuanian healthcare institutions.