A2B-COVID: A Tool for Rapidly Evaluating Potential SARS-CoV-2 Transmission Events.

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.

The rapid detection of respiratory pathogens in critically ill children.

PURPOSE: Respiratory infections are the most common reason for admission to paediatric intensive care units (PICU). Most patients with lower respiratory tract infection (LRTI) receive broad-spectrum antimicrobials, despite low rates of bacterial culture confirmation. Here, we evaluated a molecular diagnostic test for LRTI to inform the better use of antimicrobials. METHODS: The Rapid Assay for Sick Children with Acute Lung infection Study was a single-centre, prospective, observational cohort study of mechanically ventilated children (> 37/40 weeks corrected gestation to 18 years) with suspected community acquired or ventilator-associated LRTI. We evaluated the use of a 52-pathogen custom TaqMan Array Card (TAC) to identify pathogens in non-bronchoscopic bronchoalveolar lavage (mini-BAL) samples. TAC results were compared to routine microbiology testing. Primary study outcomes were sensitivity and specificity of TAC, and time to result. RESULTS: We enrolled 100 patients, all of whom were tested with TAC and 91 of whom had matching culture samples. TAC had a sensitivity of 89.5% (95% confidence interval (CI95) 66.9-98.7) and specificity of 97.9% (CI95 97.2-98.5) compared to routine bacterial and fungal culture. TAC took a median 25.8 h (IQR 9.1-29.8 h) from sample collection to result. Culture was significantly slower: median 110.4 h (IQR 85.2-141.6 h) for a positive result and median 69.4 h (IQR 52.8-78.6) for a negative result. CONCLUSIONS: TAC is a reliable and rapid adjunct diagnostic approach for LRTI in critically ill children, with the potential to aid early rationalisation of antimicrobial therapy.

Ventilator-associated pneumonia in critically ill patients with COVID-19.

BACKGROUND: Pandemic COVID-19 caused by the coronavirus SARS-CoV-2 has a high incidence of patients with severe acute respiratory syndrome (SARS). Many of these patients require admission to an intensive care unit (ICU) for invasive ventilation and are at significant risk of developing a secondary, ventilator-associated pneumonia (VAP). OBJECTIVES: To study the incidence of VAP and bacterial lung microbiome composition of ventilated COVID-19 and non-COVID-19 patients. METHODS: In this retrospective observational study, we compared the incidence of VAP and secondary infections using a combination of microbial culture and a TaqMan multi-pathogen array. In addition, we determined the lung microbiome composition using 16S RNA analysis in a subset of samples. The study involved 81 COVID-19 and 144 non-COVID-19 patients receiving invasive ventilation in a single University teaching hospital between March 15th 2020 and August 30th 2020. RESULTS: COVID-19 patients were significantly more likely to develop VAP than patients without COVID (Cox proportional hazard ratio 2.01 95% CI 1.14-3.54, p = 0.0015) with an incidence density of 28/1000 ventilator days versus 13/1000 for patients without COVID (p = 0.009). Although the distribution of organisms causing VAP was similar between the two groups, and the pulmonary microbiome was similar, we identified 3 cases of invasive aspergillosis amongst the patients with COVID-19 but none in the non-COVID-19 cohort. Herpesvirade activation was also numerically more frequent amongst patients with COVID-19. CONCLUSION: COVID-19 is associated with an increased risk of VAP, which is not fully explained by the prolonged duration of ventilation. The pulmonary dysbiosis caused by COVID-19, and the causative organisms of secondary pneumonia observed are similar to that seen in critically ill patients ventilated for other reasons.

Antibiotic resistance determination using Enterococcus faecium whole-genome sequences: a diagnostic accuracy study using genotypic and phenotypic data.

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.

Long-read sequencing reveals genomic diversity and associated plasmid movement of carbapenemase-producing bacteria in a UK hospital over 6 years.

Healthcare-associated infections (HCAIs) affect the most vulnerable people in society and are increasingly difficult to treat in the face of mounting antimicrobial resistance (AMR). Routine surveillance represents an effective way of understanding the circulation and burden of bacterial resistance and transmission in hospital settings. Here, we used whole-genome sequencing (WGS) to retrospectively analyse carbapenemase-producing Gram-negative bacteria from a single hospital in the UK over 6 years (n=165). We found that the vast majority of isolates were either hospital-onset (HAI) or HCAI. Most carbapenemase-producing organisms were carriage isolates, with 71 % isolated from screening (rectal) swabs. Using WGS, we identified 15 species, the most common being Escherichia coli and Klebsiella pneumoniae. Only one significant clonal outbreak occurred during the study period and involved a sequence type (ST)78 K. pneumoniae carrying bla NDM-1 on an IncFIB/IncHI1B plasmid. Contextualization with public data revealed little evidence of this ST outside of the study hospital, warranting ongoing surveillance. Carbapenemase genes were found on plasmids in 86 % of isolates, the most common types being bla NDM- and bla OXA-type alleles. Using long-read sequencing, we determined that approximately 30 % of isolates with carbapenemase genes on plasmids had acquired them via horizontal transmission. Overall, a national framework to collate more contextual genomic data, particularly for plasmids and resistant bacteria in the community, is needed to better understand how carbapenemase genes are transmitted in the UK.

Multiplex MinION sequencing suggests enteric adenovirus F41 genetic diversity comparable to pre-COVID-19 era.

Human adenovirus F41 causes acute gastroenteritis in children, and has recently been associated with an apparent increase in paediatric hepatitis of unknown aetiology in the UK, with further cases reported in multiple countries. Relatively little is known about the genetic diversity of adenovirus F41 in UK children; and it is unclear what, if any, impact the COVID-19 pandemic has had on viral diversity in the UK. Methods that allow F41 to be sequenced from clinical samples without the need for viral culture are required to provide the genomic data to address these questions. Therefore, we evaluated an overlapping-amplicon method of sequencing adenovirus genomes from clinical samples using Oxford Nanopore technology. We applied this method to a small sample of adenovirus-species-F-positive extracts collected as part of standard care in the East of England region in January-May 2022. This method produced genomes with >75 % coverage in 13/22 samples and >50 % coverage in 19/22 samples. We identified two F41 lineages present in paediatric patients in the East of England in 2022. Where F41 genomes from paediatric hepatitis cases were available (n=2), these genomes fell within the diversity of F41 from the UK and continental Europe sequenced before and after the 2020-2021 phase of the COVID-19 pandemic. Our analyses suggest that overlapping amplicon sequencing is an appropriate method for generating F41 genomic data from high-virus-load clinical samples, and currently circulating F41 viral lineages were present in the UK and Europe before the COVID-19 pandemic.

The clinical, genomic, and microbiological profile of invasive multi-drug resistant Escherichia coli in a major teaching hospital in the United Kingdom.

Escherichia coli is a ubiquitous component of the human gut microbiome, but is also a common pathogen, causing around 40, 000 bloodstream infections (BSI) in the United Kingdom (UK) annually. The number of E. coli BSI has increased over the last decade in the UK, and emerging antimicrobial resistance (AMR) profiles threaten treatment options. Here, we combined clinical, epidemiological, and whole genome sequencing data with high content imaging to characterise over 300 E. coli isolates associated with BSI in a large teaching hospital in the East of England. Overall, only a limited number of sequence types (ST) were responsible for the majority of organisms causing invasive disease. The most abundant (20 % of all isolates) was ST131, of which around 90 % comprised the pandemic O25b:H4 group. ST131-O25b:H4 isolates were frequently multi-drug resistant (MDR), with a high prevalence of extended spectrum ß-lactamases (ESBL) and fluoroquinolone resistance. There was no association between AMR phenotypes and the source of E. coli bacteraemia or whether the infection was healthcare-associated. Several clusters of ST131 were genetically similar, potentially suggesting a shared transmission network. However, there was no clear epidemiological associations between these cases, and they included organisms from both healthcare-associated and non-healthcare-associated origins. The majority of ST131 isolates exhibited strong binding with an anti-O25b antibody, raising the possibility of developing rapid diagnostics targeting this pathogen. In summary, our data suggest that a restricted set of MDR E. coli populations can be maintained and spread across both community and healthcare settings in this location, contributing disproportionately to invasive disease and AMR.

Evidence of widespread endemic populations of highly multidrug resistant Klebsiella pneumoniae in hospital settings in Hanoi, Vietnam: a prospective cohort study.

BACKGROUND: Patients with prolonged hospitalisation have a significant risk of carriage of and subsequent infection with extended spectrum ß-lactamase (ESBL)-producing and carbapenemase-producing Klebsiella pneumoniae. However, the distinctive roles of the community and hospital environments in the transmission of ESBL-producing or carbapenemase-producing K pneumoniae remain elusive. We aimed to investigate the prevalence and transmission of K pneumoniae within and between the two tertiary hospitals in Hanoi, Viet Nam, using whole-genome sequencing. METHODS: We did a prospective cohort study of 69 patients in intensive care units (ICUs) from two hospitals in Hanoi, Viet Nam. Patients were included if they were aged 18 years or older, admitted for longer than the mean length of stay in their ICU, and cultured K pneumoniae from their clinical samples. Longitudinally collected samples from patients (collected weekly) and the ICU environment (collected monthly) were cultured on selective media, and whole-genome sequences from K pneumoniae colonies analysed. We did phylogenetic analyses and correlated phenotypic antimicrobial susceptibility testing with genotypic features of K pneumoniae isolates. We constructed transmission networks of patient samples, relating ICU admission times and locations with genetic similarity of infecting K pneumoniae. FINDINGS: Between June 1, 2017, and Jan 31, 2018, 69 patients were in the ICUs and eligible for inclusion, and a total of 357 K pneumoniae isolates were cultured and successfully sequenced. 228 (64%) of K pneumoniae isolates carried between two and four different ESBL-encoding and carbapenemase-encoding genes, with 164 (46%) isolates carrying genes encoding both, with high minimum inhibitory concentrations. We found a novel co-occurrence of blaKPC-2 and blaNDM-1 in 46·6% of samples from the globally successful ST15 lineage. Despite being physically and clinically separated, the two hospitals shared closely related strains carrying the same array of antimicrobial resistance genes. INTERPRETATION: These results highlight the high prevalence of ESBL-positive carbapenem-resistant K pneumoniae in ICUs in Viet Nam. Through studying K pneumoniae ST15 in detail, we showed how important resistance genes are contained within these strains that are carried broadly by patients entering the two hospitals directly or through referral. FUNDING: Medical Research Council Newton Fund, Ministry of Science and Technology, Wellcome Trust, Academy of Medical Sciences, Health Foundation, and National Institute for Health and Care Research Cambridge Biomedical Research Centre.

Multiplex PCR assay to detect high risk lineages of Salmonella Typhi and Paratyphi A.

Enteric fever infections remain a significant public health issue, with up to 20 million infections per year. Increasing rates of antibiotic resistant strains have rendered many first-line antibiotics potentially ineffective. Genotype 4.3.1 (H58) is the main circulating lineage of S. Typhi in many South Asian countries and is associated with high levels of antibiotic resistance. The emergence and spread of extensively drug resistant (XDR) typhoid strains has increased the need for a rapid molecular test to identify and track these high-risk lineages for surveillance and vaccine prioritisation. Current methods require samples to be cultured for several days, followed by DNA extraction and sequencing to determine the specific lineage. We designed and evaluated the performance of a new multiplex PCR assay, targeting S. Paratyphi A as well as the H58 and XDR lineages of S. Typhi on a collection of bacterial strains. Our assay was 100% specific for the identification of lineage specific S. Typhi and S. Paratyphi A, when tested with a mix of non-Typhi Salmonella and non-Salmonella strains. With additional testing on clinical and environmental samples, this assay will allow rapid lineage level detection of typhoid of clinical significance, at a significantly lower cost to whole-genome sequencing. To our knowledge, this is the first report of a SNP-based multiplex PCR assay for the detection of lineage specific serovars of Salmonella Typhi.

Genomic characterisation of multidrug-resistant Escherichia coli, Klebsiella pneumoniae, and Acinetobacter baumannii in two intensive care units in Hanoi, Viet Nam: a prospective observational cohort study.

BACKGROUND: Viet Nam has high rates of antimicrobial resistance (AMR) but little capacity for genomic surveillance. This study used whole genome sequencing to examine the prevalence and transmission of three key AMR pathogens in two intensive care units (ICUs) in Hanoi, Viet Nam. METHODS: A prospective surveillance study of all adults admitted to ICUs at the National Hospital for Tropical Diseases and Bach Mai Hospital was done between June 19, 2017, and Jan 16, 2018. Clinical and environmental samples were cultured on selective media, characterised with MALDI TOF mass spectrometry, and sequenced with Illumina. Phylogenies based on the de-novo assemblies (SPAdes) were constructed with MAFFT (PARsnp), Gubbins, and RAxML. Resistance genes were detected with Abricate against the US National Center for Biotechnology Information database. FINDINGS: 3153 Escherichia coli, Klebsiella pneumoniae, and Acinetobacter baumannii isolates from 369 patients were analysed. Phylogenetic analysis revealed predominant lineages within A baumannii (global clone 2, sequence types ST2 and ST571) and K pneumoniae (ST15, ST16, ST656, ST11, and ST147) isolates. Isolation from stool was most common with E coli (87·0%) followed by K pneumoniae (62·5%). Of the E coli, 85·0% carried a blaCTX-M variant, while 81·8% of K pneumoniae isolates carried blaNDM (54·4%), or blaKPC (45·1%), or both. Transmission analysis with single nucleotide polymorphisms identified 167 clusters involving 251 (68%) of 369 patients, in some cases involving patients from both ICUs. There were no clear differences between the lineages or AMR genes recovered between the two ICUs. INTERPRETATION: This study represents the largest prospective surveillance study of key AMR pathogens in Vietnamese ICUs. Clusters of closely related isolates in patients across both ICUs suggests recent transmission before ICU admission in other health-care settings or in the community. FUNDING: UK Medical Research Council Newton Fund, Viet Nam Ministry of Science and Technology, Wellcome Trust, Academy of Medical Sciences, Health Foundation, and UK National Institute for Health and Care Research Cambridge Biomedical Research Centre.

Rapid Assay for Sick Children with Acute Lung infection Study (RASCALS): diagnostic cohort study protocol.

INTRODUCTION: Lower respiratory tract infection (LRTI) is the most commonly treated infection in critically ill children. Pathogens are infrequently identified on routine respiratory culture, and this is a time-consuming process. A syndromic approach to rapid molecular testing that includes a wide range of bacterial and fungal targets has the potential to aid clinical decision making and reduce unnecessary broad spectrum antimicrobial prescribing. Here, we describe a single-centre prospective cohort study investigating the use of a 52-pathogen TaqMan array card (TAC) for LRTI in the paediatric intensive care unit (PICU). METHODS AND ANALYSIS: Critically ill children with suspected LRTI will be enrolled to this 100 patient single-centre prospective observational study in a PICU in the East of England. Samples will be obtained via routine non-bronchoscopic bronchoalveolar lavage which will be sent for standard microbiology culture in addition to TAC. A blood draw will be obtained via any existing vascular access device. The primary outcomes of the study will be (1) concordance of TAC result with routine culture and 16S rRNA gene sequencing and (2) time of diagnostic result from TAC versus routine culture. Secondary outcomes will include impact of the test on total antimicrobial prescriptions, a description of the inflammatory profile of the lung and blood in response to pneumonia and a description of the clinical experience of medical and nursing staff using TAC. ETHICS AND DISSEMINATION: This study has been approved by the Yorkshire and the Humber-Bradford Leeds Research Ethics Committee (REC reference 20/YH/0089). Informed consent will be obtained from all participants. Results will be published in peer-reviewed publications and international conferences. TRIAL REGISTRATION NUMBER: NCT04233268.

Patterns of within-host genetic diversity in SARS-CoV-2.

Monitoring the spread of SARS-CoV-2 and reconstructing transmission chains has become a major public health focus for many governments around the world. The modest mutation rate and rapid transmission of SARS-CoV-2 prevents the reconstruction of transmission chains from consensus genome sequences, but within-host genetic diversity could theoretically help identify close contacts. Here we describe the patterns of within-host diversity in 1181 SARS-CoV-2 samples sequenced to high depth in duplicate. 95.1% of samples show within-host mutations at detectable allele frequencies. Analyses of the mutational spectra revealed strong strand asymmetries suggestive of damage or RNA editing of the plus strand, rather than replication errors, dominating the accumulation of mutations during the SARS-CoV-2 pandemic. Within- and between-host diversity show strong purifying selection, particularly against nonsense mutations. Recurrent within-host mutations, many of which coincide with known phylogenetic homoplasies, display a spectrum and patterns of purifying selection more suggestive of mutational hotspots than recombination or convergent evolution. While allele frequencies suggest that most samples result from infection by a single lineage, we identify multiple putative examples of co-infection. Integrating these results into an epidemiological inference framework, we find that while sharing of within-host variants between samples could help the reconstruction of transmission chains, mutational hotspots and rare cases of superinfection can confound these analyses.

The COVID-19 pandemic has had major health impacts across the globe. The scientific community has focused much attention on finding ways to monitor how the virus responsible for the pandemic, SARS-CoV-2, spreads. One option is to perform genetic tests, known as sequencing, on SARS-CoV-2 samples to determine the genetic code of the virus and to find any differences or mutations in the genes between the viral samples. Viruses mutate within their hosts and can develop into variants that are able to more easily transmit between hosts. Genetic sequencing can reveal how genetically similar two SARS-CoV-2 samples are. But tracking how SARS-CoV-2 moves from one person to the next through sequencing can be tricky. Even a sample of SARS-CoV-2 viruses from the same individual can display differences in their genetic material or within-host variants. Could genetic testing of within-host variants shed light on factors driving SARS-CoV-2 to evolve in humans? To get to the bottom of this, Tonkin-Hill, Martincorena et al. probed the genetics of SARS-CoV-2 within-host variants using 1,181 samples. The analyses revealed that 95.1% of samples contained within-host variants. A number of variants occurred frequently in many samples, which were consistent with mutational hotspots in the SARS-CoV-2 genome. In addition, within-host variants displayed mutation patterns that were similar to patterns found between infected individuals. The shared within-host variants between samples can help to reconstruct transmission chains. However, the observed mutational hotspots and the detection of multiple strains within an individual can make this challenging. These findings could be used to help predict how SARS-CoV-2 evolves in response to interventions such as vaccines. They also suggest that caution is needed when using information on within-host variants to determine transmission between individuals.

Superspreaders drive the largest outbreaks of hospital onset COVID-19 infections.

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.

The COVID-19 pandemic, caused by the SARS-CoV-2 virus, presents a global public health challenge. Hospitals have been at the forefront of this battle, treating large numbers of sick patients over several waves of infection. Finding ways to manage the spread of the virus in hospitals is key to protecting vulnerable patients and workers, while keeping hospitals running, but to generate effective infection control, researchers must understand how SARS-CoV-2 spreads. A range of factors make studying the transmission of SARS-CoV-2 in hospitals tricky. For instance, some people do not present any symptoms, and, amongst those who do, it can be difficult to determine whether they caught the virus in the hospital or somewhere else. However, comparing the genetic information of the SARS-CoV-2 virus from different people in a hospital could allow scientists to understand how it spreads. Samples of the genetic material of SARS-CoV-2 can be obtained by swabbing infected individuals. If the genetic sequences of two samples are very different, it is unlikely that the individuals who provided the samples transmitted the virus to one another. Illingworth, Hamilton et al. used this information, along with other data about how SARS-CoV-2 is transmitted, to develop an algorithm that can determine how the virus spreads from person to person in different hospital wards. To build their algorithm, Illingworth, Hamilton et al. collected SARS-CoV-2 genetic data from patients and staff in a hospital, and combined it with information about how SARS-CoV-2 spreads and how these people moved in the hospital . The algorithm showed that, for the most part, patients were infected by other patients (20 out of 22 cases), while staff were infected equally by patients and staff. By further probing these data, Illingworth, Hamilton et al. revealed that 80% of hospital-acquired infections were caused by a group of just 21% of individuals in the study, identifying a 'superspreader' pattern. These findings may help to inform SARS-CoV-2 infection control measures to reduce spread within hospitals, and could potentially be used to improve infection control in other contexts.

Genomic epidemiology of COVID-19 in care homes in the east of England.

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.

Rapid implementation of SARS-CoV-2 sequencing to investigate cases of health-care associated COVID-19: a prospective genomic surveillance study.

BACKGROUND: The burden and influence of health-care associated severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections is unknown. We aimed to examine the use of rapid SARS-CoV-2 sequencing combined with detailed epidemiological analysis to investigate health-care associated SARS-CoV-2 infections and inform infection control measures. METHODS: In this prospective surveillance study, we set up rapid SARS-CoV-2 nanopore sequencing from PCR-positive diagnostic samples collected from our hospital (Cambridge, UK) and a random selection from hospitals in the East of England, enabling sample-to-sequence in less than 24 h. We established a weekly review and reporting system with integration of genomic and epidemiological data to investigate suspected health-care associated COVID-19 cases. FINDINGS: Between March 13 and April 24, 2020, we collected clinical data and samples from 5613 patients with COVID-19 from across the East of England. We sequenced 1000 samples producing 747 high-quality genomes. We combined epidemiological and genomic analysis of the 299 patients from our hospital and identified 35 clusters of identical viruses involving 159 patients. 92 (58%) of 159 patients had strong epidemiological links and 32 (20%) patients had plausible epidemiological links. These results were fed back to clinical, infection control, and hospital management teams, leading to infection-control interventions and informing patient safety reporting. INTERPRETATION: We established real-time genomic surveillance of SARS-CoV-2 in a UK hospital and showed the benefit of combined genomic and epidemiological analysis for the investigation of health-care associated COVID-19. This approach enabled us to detect cryptic transmission events and identify opportunities to target infection-control interventions to further reduce health-care associated infections. Our findings have important implications for national public health policy as they enable rapid tracking and investigation of infections in hospital and community settings. FUNDING: COVID-19 Genomics UK funded by the Department of Health and Social Care, UK Research and Innovation, and the Wellcome Sanger Institute.