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BACKGROUND: Community-acquired (CA), community-onset methicillin-resistant Staphylococcus aureus (CO-MRSA) infection presents a significant public health challenge, even where MRSA rates are historically lower. Despite successes in reducing hospital-onset MRSA, CO-MRSA rates are increasing globally, with a need to understand this trend, and the potential risk factors for re-emergence. OBJECTIVES: This review aims to explore the characteristics of outbreaks of community-acquired community-onset methicillin-resistant Staphylococcus aureus in low-prevalence areas, to understand the factors involved in its rise, and to translate this knowledge into public health policy and further research needs. SOURCES: PubMed, EMBASE, and Google Scholar were searched using combinations of the terms 'transmission', 'acquisition', 'community-acquired', 'MRSA', 'CA-MRSA', 'low prevalence', 'genomic', 'outbreak', 'colonisation', and 'carriage'. Wherever evidence was limited, additional articles were sought specifically, via PubMed searches. Papers where materials were not available in English were excluded. CONTENT: Challenges in defining low-prevalence areas and the significance of exposure to various risk factors for community acquisition, such as healthcare settings, travel, livestock, and environmental factors, are discussed. The importance of genomic surveillance in identifying outbreak strains and understanding the transmission dynamics is highlighted, along with the need for robust public health policies and control measures. IMPLICATIONS: The findings emphasise the complexity of CO-MRSA transmission and the necessity of a multifaceted approach in low-prevalence areas. This includes integrated and systematic surveillance of hospital-onset-, CO-, and livestock-associated MRSA, as has been effective in some Northern European countries. The evolution of CO-MRSA underscores the need for global collaboration, routine genomic surveillance, and comprehensive antimicrobial stewardship to mitigate the rise of CO-MRSA and address the broader challenge of antimicrobial resistance. These efforts are crucial for maintaining low MRSA prevalence and managing the increasing burden of CO-MRSA in both low and higher prevalence regions.
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Genomic epidemiology enhances the ability to detect and refute methicillin-resistant Staphylococcus aureus (MRSA) outbreaks in healthcare settings, but its routine introduction requires further evidence of benefits for patients and resource utilization. We performed a 12 month prospective study at Cambridge University Hospitals NHS Foundation Trust in the UK to capture its impact on hospital infection prevention and control (IPC) decisions. MRSA-positive samples were identified via the hospital microbiology laboratory between November 2018 and November 2019. We included samples from in-patients, clinic out-patients, people reviewed in the Emergency Department and healthcare workers screened by Occupational Health. We sequenced the first MRSA isolate from 823 consecutive individuals, defined their pairwise genetic relatedness, and sought epidemiological links in the hospital and community. Genomic analysis of 823 MRSA isolates identified 72 genetic clusters of two or more isolates containing 339/823 (41â%) of the cases. Epidemiological links were identified between two or more cases for 190 (23â%) individuals in 34/72 clusters. Weekly genomic epidemiology updates were shared with the IPC team, culminating in 49 face-to-face meetings and 21 written communications. Seventeen clusters were identified that were consistent with hospital MRSA transmission, discussion of which led to additional IPC actions in 14 of these. Two outbreaks were also identified where transmission had occurred in the community prior to hospital presentation; these were escalated to relevant IPC teams. We identified 38 instances where two or more in-patients shared a ward location on overlapping dates but carried unrelated MRSA isolates (pseudo-outbreaks); research data led to de-escalation of investigations in six of these. Our findings provide further support for the routine use of genomic epidemiology to enhance and target IPC resources.
Assuntos
Infecção Hospitalar , Staphylococcus aureus Resistente à Meticilina , Infecções Estafilocócicas , Humanos , Staphylococcus aureus Resistente à Meticilina/genética , Infecção Hospitalar/microbiologia , Infecções Estafilocócicas/microbiologia , Estudos Prospectivos , GenômicaRESUMO
BACKGROUND: DNA sequencing could become an alternative to in vitro antibiotic susceptibility testing (AST) methods for determining antibiotic resistance by detecting genetic determinants associated with decreased antibiotic susceptibility. Here, we aimed to assess and improve the accuracy of antibiotic resistance determination from Enterococcus faecium genomes for diagnosis and surveillance purposes. METHODS: In this retrospective diagnostic accuracy study, we first conducted a literature search in PubMed on Jan 14, 2021, to compile a catalogue of genes and mutations predictive of antibiotic resistance in E faecium. We then evaluated the diagnostic accuracy of this database to determine susceptibility to 12 different, clinically relevant antibiotics using a diverse population of 4382 E faecium isolates with available whole-genome sequences and in vitro culture-based AST phenotypes. Isolates were obtained from various sources in 11 countries worldwide between 2000 and 2018. We included isolates tested with broth microdilution, Vitek 2, and disc diffusion, and antibiotics with at least 50 susceptible and 50 resistant isolates. Phenotypic resistance was derived from raw minimum inhibitory concentrations and measured inhibition diameters, and harmonised primarily using the breakpoints set by the European Committee on Antimicrobial Susceptibility Testing. A bioinformatics pipeline was developed to process raw sequencing reads, identify antibiotic resistance genetic determinants, and report genotypic resistance. We used our curated database, as well as ResFinder, AMRFinderPlus, and LRE-Finder, to assess the accuracy of genotypic predictions against phenotypic resistance. FINDINGS: We curated a catalogue of 228 genetic markers involved in resistance to 12 antibiotics in E faecium. Very accurate genotypic predictions were obtained for ampicillin (sensitivity 99·7% [95% CI 99·5-99·9] and specificity 97·9% [95·8-99·0]), ciprofloxacin (98·0% [96·4-98·9] and 98·8% [95·9-99·7]), vancomycin (98·8% [98·3-99·2] and 98·8% [98·0-99·3]), and linezolid resistance (after re-testing false negatives: 100·0% [90·8-100·0] and 98·3% [97·8-98·7]). High sensitivity was obtained for tetracycline (99·5% [99·1-99·7]), teicoplanin (98·9% [98·4-99·3]), and high-level resistance to aminoglycosides (97·7% [96·6-98·4] for streptomycin and 96·8% [95·8-97·5] for gentamicin), although at lower specificity (60-90%). Sensitivity was expectedly low for daptomycin (73·6% [65·1-80·6]) and tigecycline (38·3% [27·1-51·0]), for which the genetic basis of resistance is not fully characterised. Compared with other antibiotic resistance databases and bioinformatic tools, our curated database was similarly accurate at detecting resistance to ciprofloxacin and linezolid and high-level resistance to streptomycin and gentamicin, but had better sensitivity for detecting resistance to ampicillin, tigecycline, daptomycin, and quinupristin-dalfopristin, and better specificity for ampicillin, vancomycin, teicoplanin, and tetracycline resistance. In a validation dataset of 382 isolates, similar or improved diagnostic accuracies were also achieved. INTERPRETATION: To our knowledge, this work represents the largest published evaluation to date of the accuracy of antibiotic susceptibility predictions from E faecium genomes. The results and resources will facilitate the adoption of whole-genome sequencing as a tool for the diagnosis and surveillance of antimicrobial resistance in E faecium. A complete characterisation of the genetic basis of resistance to last-line antibiotics, and the mechanisms mediating antibiotic resistance silencing, are needed to close the remaining sensitivity and specificity gaps in genotypic predictions. FUNDING: Wellcome Trust, UK Department of Health, British Society for Antimicrobial Chemotherapy, Academy of Medical Sciences and the Health Foundation, Medical Research Council Newton Fund, Vietnamese Ministry of Science and Technology, and European Society of Clinical Microbiology and Infectious Disease.