The major human bacterial pathogenPseudomonas aeruginosacauses multidrug-resistant infections in people with underlying immunodeficiencies or structural lung diseases such as cystic fibrosis (CF). We show that a few environmental isolates, driven by horizontal gene acquisition, have become dominant epidemic clones that have sequentially emerged and spread through global transmission networks over the past 200 years. These clones demonstrate varying intrinsic propensities for infecting CF or non-CF individuals (linked to specific transcriptional changes enabling survival within macrophages); have undergone multiple rounds of convergent, host-specific adaptation; and have eventually lost their ability to transmit between different patient groups. Our findings thus explain the pathogenic evolution ofP. aeruginosaand highlight the importance of global surveillance and cross-infection prevention in averting the emergence of future epidemic clones.

SARS-CoV-2 is notable both for its rapid spread, and for the heterogeneity of its patterns of transmission, with multiple published incidences of superspreading behaviour. Here, we applied a novel network reconstruction algorithm to infer patterns of viral transmission occurring between patients and health care workers (HCWs) in the largest clusters of COVID-19 infection identified during the first wave of the epidemic at Cambridge University Hospitals NHS Foundation Trust, UK. Based upon dates of individuals reporting symptoms, recorded individual locations, and viral genome sequence data, we show an uneven pattern of transmission between individuals, with patients being much more likely to be infected by other patients than by HCWs. Further, the data were consistent with a pattern of superspreading, whereby 21% of individuals caused 80% of transmission events. Our study provides a detailed retrospective analysis of nosocomial SARS-CoV-2 transmission, and sheds light on the need for intensive and pervasive infection control procedures.

Identifying linked cases of infection is a critical component of the public health response to viral infectious diseases. In a clinical context, there is a need to make rapid assessments of whether cases of infection have arrived independently onto a ward, or are potentially linked via direct transmission. Viral genome sequence data are of great value in making these assessments, but are often not the only form of data available. Here, we describe A2B-COVID, a method for the rapid identification of potentially linked cases of COVID-19 infection designed for clinical settings. Our method combines knowledge about infection dynamics, data describing the movements of individuals, and evolutionary analysis of genome sequences to assess whether data collected from cases of infection are consistent or inconsistent with linkage via direct transmission. A retrospective analysis of data from two wards at Cambridge University Hospitals NHS Foundation Trust during the first wave of the pandemic showed qualitatively different patterns of linkage between cases on designated COVID-19 and non-COVID-19 wards. The subsequent real-time application of our method to data from the second epidemic wave highlights its value for monitoring cases of infection in a clinical context.

Infections with carbapenemase-producing Enterobacteriaceae (CPE) and vancomycin-resistant enterococci (VRE) are associated with increased morbidity and mortality, but the carriage rates of CRE and VRE among hospital inpatients are unknown. A point-prevalence survey was conducted to determine CPE and VRE carriage rates in hospitalized adults. Eight hundred and eighteen of 960 (85.2%) adult inpatients were invited to participate in the study. Of these, 595 patients (72.7%) consented and provided specimens. Of 540 samples tested, none were positive for CPE. One hundred and thirty of 540 (24.1%) samples were VRE positive, and 34 of 40 (85%) of wards had cases. Universal screening for CPE may not be cost-effective in low-prevalence settings, but targeted screening of high-risk patients should continue. The optimal screening strategy for VRE remains to be determined, as universal screening and isolation is not feasible in the study setting.

COVID-19 poses a major challenge to care homes, as SARS-CoV-2 is readily transmitted and causes disproportionately severe disease in older people. Here, 1167 residents from 337 care homes were identified from a dataset of 6600 COVID-19 cases from the East of England. Older age and being a care home resident were associated with increased mortality. SARS-CoV-2 genomes were available for 700 residents from 292 care homes. By integrating genomic and temporal data, 409 viral clusters within the 292 homes were identified, indicating two different patterns – outbreaks among care home residents and independent introductions with limited onward transmission. Approximately 70% of residents in the genomic analysis were admitted to hospital during the study, providing extensive opportunities for transmission between care homes and hospitals. Limiting viral transmission within care homes should be a key target for infection control to reduce COVID-19 mortality in this population.

To determine the prevalence of 16S rRNA methyltransferase- (16S RMTase-) producing Gram-negative bacteria in patients in the UK and to identify potential risk factors for their acquisition. A 6 month prospective surveillance study was conducted from 1 May to 31 October 2016, wherein 14 hospital laboratories submitted Acinetobacter baumannii, Enterobacterales and Pseudomonas aeruginosa isolates that displayed high-level amikacin resistance according to their testing methods, e.g. no zone of inhibition with amikacin discs. Isolates were linked to patient travel history, medical care abroad, and previous antibiotic exposure using a surveillance questionnaire. In the reference laboratory, isolates confirmed to grow on Mueller-Hinton agar supplemented with 256 mg/L amikacin were screened by PCR for 16S RMTase genes armA, rmtA–rmtH and npmA, and carbapenemase genes (bla_KPC, bla_NDM, bla_OXA-48-like and bla_VIM). STs and total antibiotic resistance gene complement were determined via WGS. Prevalence was determined using denominators for each bacterial species provided by participating hospital laboratories. Eighty-four isolates (44.7%), among 188 submitted isolates, exhibited high-level amikacin resistance (MIC >256 mg/L), and 79 (94.0%) of these harboured 16S RMTase genes. armA (54.4%, 43/79) was the most common, followed by rmtB (17.7%, 14/79), rmtF (13.9%, 11/79), rmtC (12.7%, 10/79) and armA + rmtF (1.3%, 1/79). The overall period prevalence of 16S RMTase-producing Gram-negative bacteria was 0.1% (79/71 063). Potential risk factors identified through multivariate statistical analysis included being male and polymyxin use. The UK prevalence of 16S RMTase-producing Gram-negative bacteria is low, but continued surveillance is needed to monitor their spread and inform intervention strategies.