White Paper: Bridging the gap between surveillance data and antimicrobial stewardship in long-term care facilities-practical guidance from the JPIAMR ARCH and COMBACTE-MAGNET EPI-Net networks.

BACKGROUND: In long-term care facilities (LTCFs) residents often receive inappropriate antibiotic treatment and infection prevention and control practices are frequently inadequate, thus favouring acquisition of MDR organisms. There is increasing evidence in the literature describing antimicrobial stewardship (AMS) activities in LTCFs, but practical guidance on how surveillance data should be linked with AMS activities in this setting is lacking. To bridge this gap, the JPIAMR ARCH and COMBACTE-MAGNET EPI-Net networks joined their efforts to provide practical guidance for linking surveillance data with AMS activities. MATERIALS AND METHODS: Considering the three main topics [AMS leadership and accountability, antimicrobial usage (AMU) and AMS, and antimicrobial resistance (AMR) and AMS], a literature review was performed and a list of target actions was developed. Consensus on target actions was reached through a RAND-modified Delphi process involving 40 experts from 18 countries and different professional backgrounds adopting a One Health approach. RESULTS: From the 25 documents identified, 25 target actions were retrieved and proposed for expert evaluation. The consensus process produced a practical checklist including 23 target actions, differentiating between essential and desirable targets according to clinical relevance and feasibility. Flexible proposals for AMS team composition and leadership were provided, with a strong emphasis on the need for well-defined and adequately supported roles and responsibilities. Specific antimicrobial classes, AMU metrics, pathogens and resistance patterns to be monitored are addressed. Effective reporting strategies are described. CONCLUSIONS: The proposed checklist represents a practical tool to support local AMS teams across a wide range of care delivery organization and availability of resources.

White Paper: Bridging the gap between surveillance data and antimicrobial stewardship in the outpatient sector-practical guidance from the JPIAMR ARCH and COMBACTE-MAGNET EPI-Net networks.

BACKGROUND: The outpatient setting is a key scenario for the implementation of antimicrobial stewardship (AMS) activities, considering that overconsumption of antibiotics occurs mainly outside hospitals. This publication is the result of a joint initiative by the JPIAMR ARCH and COMBACTE-MAGNET EPI-Net networks, which is aimed at formulating a set of target actions for linking surveillance data with AMS activities in the outpatient setting. METHODS: A scoping review of the literature was carried out in three research areas: AMS leadership and accountability; antimicrobial usage and AMS; antimicrobial resistance and AMS. Consensus on the actions was reached through a RAND-modified Delphi process involving over 40 experts in infectious diseases, clinical microbiology, AMS, veterinary medicine or public health, from 18 low-, middle- and high-income countries. RESULTS: Evidence was retrieved from 38 documents, and an initial 25 target actions were proposed, differentiating between essential or desirable targets according to clinical relevance, feasibility and applicability to settings and resources. In the first consultation round, preliminary agreement was reached for all targets. Further to a second review, 6 statements were re-considered and 3 were deleted, leading to a final list of 22 target actions in the form of a practical checklist. CONCLUSIONS: This White Paper is a pragmatic and flexible tool to guide the development of calibrated surveillance-based AMS interventions specific to the outpatient setting, which is characterized by substantial inter- and intra-country variability in the organization of healthcare structures, maintaining a global perspective and taking into account the feasibility of the target actions in low-resource settings.

Linking antimicrobial resistance surveillance to antibiotic policy in healthcare settings: the COMBACTE-Magnet EPI-Net COACH project.

OBJECTIVES: To systematically summarize the evidence on how to collect, analyse and report antimicrobial resistance (AMR) surveillance data to inform antimicrobial stewardship (AMS) teams providing guidance on empirical antibiotic treatment in healthcare settings. METHODS: The research group identified 10 key questions about the link between AMR surveillance and AMS using a checklist of 9 elements for good practice in health research priority settings and a modified 3D combined approach matrix, and conducted a systematic review of published original studies and guidelines on the link between AMR surveillance and AMS. RESULTS: The questions identified focused on AMS team composition; minimum infrastructure requirements for AMR surveillance; organisms, samples and susceptibility patterns to report; data stratification strategies; reporting frequency; resistance thresholds to drive empirical therapy; surveillance in high-risk hospital units, long-term care, outpatient and veterinary settings; and surveillance data from other countries. Twenty guidelines and seven original studies on the implementation of AMR surveillance as part of an AMS programme were included in the literature review. CONCLUSIONS: The evidence summarized in this review provides a useful basis for a more integrated process of developing procedures to report AMR surveillance data to drive AMS interventions. These procedures should be extended to settings outside the acute-care institutions, such as long-term care, outpatient and veterinary. Without proper AMR surveillance, implementation of AMS policies cannot contribute effectively to the fight against MDR pathogens and may even worsen the burden of adverse events from such interventions.

White Paper: Bridging the gap between human and animal surveillance data, antibiotic policy and stewardship in the hospital sector-practical guidance from the JPIAMR ARCH and COMBACTE-MAGNET EPI-Net networks.

BACKGROUND: Antimicrobial surveillance and antimicrobial stewardship (AMS) are essential pillars in the fight against antimicrobial resistance (AMR), but practical guidance on how surveillance data should be linked to AMS activities is lacking. This issue is particularly complex in the hospital setting due to structural heterogeneity of hospital facilities and services. The JPIAMR ARCH and COMBACTE-MAGNET EPI-Net networks have joined efforts to formulate a set of target actions for linking surveillance data with AMS activities. METHODS: A scoping review of the literature was carried out addressing research questions on three areas: (i) AMS leadership and accountability; (ii) antimicrobial usage and AMS; (iii) AMR and AMS. Consensus on the target actions was reached through a RAND-modified Delphi process involving over 40 experts in different fields from 18 countries. RESULTS: Evidence was retrieved from 51 documents. Initially 38 targets were proposed, differentiated as essential or desirable according to clinical relevance, feasibility and applicability to settings and resources. In the first consultation round, preliminary agreement was reached for 32 targets. Following a second consultation, 27 targets were approved, 11 were deleted and 4 were suggested for rephrasing, leading to a final approved list of 34 target actions in the form of a practical checklist. CONCLUSIONS: This White Paper provides a pragmatic and flexible tool to guide the development of calibrated hospital-surveillance-based AMS interventions. The strength of this tool is that it is a comprehensive perspective that takes into account the hospital patient case-mix and the related epidemiology, which ultimately drives antimicrobial usage, and the feasibility in low-resource settings.

Frequency of bloodstream infections caused by six key antibiotic-resistant pathogens for prioritization of research and discovery of new therapies in Europe: a systematic review.

BACKGROUND: To prioritize healthcare investments, ranking of infections caused by antibiotic-resistant bacteria should be based on accurate incidence data. OBJECTIVES: We performed a systematic review to estimate frequency measures of antimicrobial resistance for six key bacteria causing bloodstream infections (BSI) in European countries. DATA SOURCES: We searched PubMed, Web of Science, Embase databases, and the ECRAID-Base Epidemiological-Network platform. STUDY ELIGIBILITY CRITERIA: We included studies and surveillance systems assessing resistance-percentage, prevalence, or incidence-density of BSI because of carbapenem-resistant Pseudomonas aeruginosa, Acinetobacter baumannii, Klebsiella pneumoniae, and Escherichia coli, third-generation cephalosporins-resistant E. coli and K. pneumoniae, vancomycin-resistant Enterococcus faecium, and methicillin-resistant Staphylococcus aureus. METHODS: Reviewers independently assessed published data and evaluated study quality with the modified Joanna Briggs Institute critical appraisal tool. Pooled estimates were determined using random effects meta-analysis. Consistency of data was assessed using random effects meta-regression (Wald test, p > 0.05). RESULTS: We identified 271 studies and 52 surveillance systems from 32 European countries. Forty-five studies (16%) reported on BSI, including 180 frequency measures most commonly as resistance-percentage (88, 48.9%). Among 309 frequency measures extracted from 24 (46%) surveillance systems, 278 (89%) were resistance-percentages. Frequency measures of methicillin-resistant S. aureus and vancomycin-resistant E. faecium BSI were more frequently reported from Southern Europe and Western Europe (80%), whereas carbapenem-resistant P. aeruginosa BSI from Northern Europe and Western Europe (88%). Highest resistance-percentages were detected for carbapenem-resistant A. baumannii (66% in Central Eastern Europe) and carbapenem-resistant K. pneumoniae (62.8% in Southern Europe). Pooled estimates showed lower resistance-percentages in community versus healthcare-associated infections and in children versus adults. Estimates from studies and surveillance systems were mostly consistent among European regions. The included data was of medium quality. DISCUSSION: Pathogen-specific frequency measures of antimicrobial resistance in BSI are insufficient to inform antibiotic stewardship and research and development strategies. Improving data collection and standardization of frequency measures is urgently needed.

Modelling antimicrobial resistance transmission to guide personalized antimicrobial stewardship interventions and infection control policies in healthcare setting: a pilot study.

Infection control programs and antimicrobial stewardship have been proven effective in reducing the burden of diseases due to multidrug-resistant organisms, but quantifying the effect of each intervention is an open issue. For this aim, we propose a model to characterize the effect of interventions at single ward level. We adapted the Ross-Macdonald model to describe hospital cross-transmission dynamics of carbapenem resistant Klebsiella pneumoniae (CRKP), considering healthcare workers as the vectors transmitting susceptible and resistant pathogens among admitted patients. The model parameters were estimated from a literature review, further adjusted to reproduce observed clinical outcomes, and validated using real life data from a 2-year study in a university hospital. The model has been further explored through extensive sensitivity analysis, in order to assess the relevance of single interventions as well as their synergistic effects. Our model has been shown to be an effective tool to describe and predict the impact of interventions in reducing the prevalence of CRKP colonisation and infection, and can be extended to other specific hospital and pathological scenarios to produce tailored estimates of the most effective strategies.

EPI-Net One Health reporting guideline for antimicrobial consumption and resistance surveillance data: a Delphi approach.

Strategic and standardised approaches to analysis and reporting of surveillance data are essential to inform antimicrobial resistance (AMR) mitigation measures, including antibiotic policies. Targeted guidance on linking full-scale AMR and antimicrobial consumption (AMC)/antimicrobial residues (AR) surveillance data from the human, animal, and environmental sectors is currently needed. This paper describes the initiative whereby a multidisciplinary panel of experts (56 from 20 countries-52 high income, 4 upper middle or lower income), representing all three sectors, elaborated proposals for structuring and reporting full-scale AMR and AMC/AR surveillance data across the three sectors. An evidence-supported, modified Delphi approach was adopted to reach consensus among the experts for dissemination frequency, language, and overall structure of reporting; core elements and metrics for AMC/AR data; core elements and metrics for AMR data. The recommendations can support multisectoral national and regional plans on antimicrobials policy to reduce resistance rates applying a One Health approach.

Surveillance of Antifungal Resistance in Candidemia Fails to Inform Antifungal Stewardship in European Countries.

BACKGROUND: The increasing burden of candidemia and the emergence of resistance, especially among non-Candida albicans strains, represent a new threat for public health. We aimed to assess the status of surveillance and to identify publicly accessible resistance data in Candida spp. blood isolates from surveillance systems and epidemiological studies in 28 European and 4 European Free Trade Association member states. METHODS: A systematic review of national and international surveillance networks, from 2015 to 2020, and peer-reviewed epidemiological surveillance studies, from 2005 to 2020, lasting for at least 12 consecutive months and with at least two centers involved, was completed to assess reporting of resistance to amphotericin B, azoles, and echinocandins in C. albicans, C. glabrata, C. parapsilosis, C. tropicalis, C. krusei, and C. auris. RESULTS: Only 5 (Austria, Italy, Norway, Spain, and United Kingdom) of 32 countries provided resistance data for Candida spp blood isolates. Among 322 surveillance studies identified, 19 were included from Belgium, Denmark, Iceland, Italy, Portugal, Spain, Sweden, Switzerland, and United Kingdom. C. albicans and C. glabrata were the most monitored species, followed by C. parapsilosis and C. tropicalis. C. krusei was not included in any national surveillance system; 13 studies assessed resistance. No surveillance system or study reported resistance for C. auris. Fluconazole, voriconazole, caspofungin, and amphotericin B resistance in C. albicans, C. glabrata, and C. parapsilosis were the most common drug-species combination monitored. Quality of surveillance data was poor, with only two surveillance systems reporting microbiological methods and clinical data. High heterogeneity was observed in modalities of reporting, data collection, and definitions. CONCLUSION: Surveillance of antifungal resistance in Candida spp blood-isolates is fragmented and heterogeneous, delaying the application of a translational approach to the threat of antifungal resistance and the identification of proper targets for antifungal stewardship activities. International efforts are needed to implement antifungal resistance surveillance programs in order to adequately monitor antifungal resistance.

The antimicrobial resistance travel tool, an interactive evidence-based educational tool to limit antimicrobial resistance spread.

BACKGROUND: International travel has been recognized as a risk factor contributing to the spread of antimicrobial resistance (AMR). However, tools focused on AMR in the context of international travel and designed to guide decision-making are limited. We aimed at developing an evidence-based educational tool targeting both healthcare professionals (HCPs) and international travellers to help prevent the spread of AMR. METHODS: A literature review on 12 antimicrobial-resistant bacteria (ARB) listed as critical and high tiers in the WHO Pathogen Priority List covering four key areas was carried out: AMR surveillance data; epidemiological studies reporting ARB prevalence data on carriage in returning travellers; guidance documents reporting indications on screening for ARB in returning travellers and recommendations for ARB prevention for the public. The evidence, catalogued at country-level, provided the content for a series of visualizations that allow assessment of the risk of AMR acquisition through travel. RESULTS: Up to January 2021, the database includes data on: (i) AMR surveillance for 2.018.241 isolates from 86 countries; (ii) ARB prevalence of carriage from 11.679 international travellers and (iii) 15 guidance documents published by major public health agencies. The evidence allowed the development of a consultation scheme for the evaluation of risk factors, prevalence of carriage, proportion and recommendations for screening of AMR. For the public, pre-travel practical measures to minimize the risk of transmission were framed. CONCLUSIONS: This easy-to-use, annually updated, freely accessible AMR travel tool (https://epi-net.eu/travel-tool/overview/), is the first of its kind to be developed. For HCPs, it can provide a valuable resource for teaching and a repository that facilitates a stepwise assessment of the risk of AMR spread and strengthen implementation of optimized infection control measures. Similarly, for travellers, the tool has the potential to raise awareness of AMR and outlines preventive measures that reduce the risk of AMR acquisition and spread.

Usefulness and Limitations of Anti-S IgG Assay in Detecting Previous SARS-CoV-2 Breakthrough Infection in Fully Vaccinated Healthcare Workers.

Introduction: The anti-spike (S) IgG assay is the most widely used method to assess the immunological response to COVID-19 vaccination. Several studies showed that subjects with perivaccination infection have higher anti-S IgG titers. However, a cut-off has not yet been identified so far for distinguishing infected subjects after vaccination. This study thus evaluates the performance of the anti-S IgG assay in identifying subjects with breakthrough infections (BIs) and its potential usefulness for screening healthcare workers (HCWs). Methods: Out of 6400 HCWs of the University Hospital of Verona vaccinated with two doses of BNT162b2, 4462 never infected before subjects who had completed primary vaccination were tested for IgG anti-S 6 to 9 months after the second dose. Of these, 59 (1.3%) had a BI. The discriminant power of IgG anti-S in detecting previous breakthrough infection was tested by constructing receiver operating characteristic (ROC) curves. Results: The discriminant power for BI was rather good (area under the curve (AUC), 0.78) and increased with decreasing time elapsed between antibody titer assessment and previous SARS-CoV-2 infection. Accuracy (AUC) sensitivity increased from 0.78 (95% CI 0.70−0.85) for BI in the previous six months to 0.83 (95% CI 0.67−0.99) for those in the previous two months, and from 0.68 to 0.80, respectively. The specificity (0.86) and optimal cut-off (935 BAU/mL) remained unchanged. However, BI were rather rare (1.3%), so the positive predictive value (PPV) was low. Only 40 of the 664 HCWs with antibody titer > 935 BAU/mL had previously confirmed BI, yielding a PPV of only 6.0%. When adopting as cut-off the 90th percentile (1180 BAU/mL), PPV increased to 7.9% (35/441). Conclusions: The anti-S IgG assay displayed good sensitivity and specificity in discriminating subjects with BI, especially in recent periods. However, BIs were rare among HCWs, so that the anti-S IgG assay may have low PPV in this setting, thus limiting the usefulness of this test as a screening tool for HCWs. Further studies are needed to identify more effective markers of a previous infection in vaccinated subjects.