Klebsiella pneumoniae sequence type 147: a high-risk clone increasingly associated with plasmids carrying both resistance and virulence elements.

Introduction. The first hybrid resistance/virulence plasmid, combining elements from virulence plasmids described in hypervirulent types of Klebsiella pneumoniae with those from conjugative resistance plasmids, was described in an isolate of sequence type (ST) 147 from 2016. Subsequently, this type has been increasingly associated with these plasmids.Hypothesis or gap statement. The extent of carriage of hybrid virulence/resistance plasmids in nosocomial isolates of K. pneumoniae requires further investigation.Aim. To describe the occurrence of virulence/resistance plasmids among isolates of K. pneumoniae received by the UK reference laboratory, particularly among representatives of ST147, and to compare their sequences.Methodology. Isolates received by the laboratory during 2022 and the first half of 2023 (n=1278) were screened for virulence plasmids by PCR detection of rmpA/rmpA2 and typed by variable-number tandem repeat analysis. Twenty-nine representatives of ST147 (including a single-locus variant) from seven hospital laboratories were subjected to long-read nanopore sequencing using high-accuracy q20 chemistry to provide complete assemblies.Results. rmpA/rmpA2 were detected in 110 isolates, of which 59 belonged to hypervirulent K1-ST23, K2-ST86 and K2-ST65/375. Of the remainder, representatives of ST147 formed the largest group, with 22 rmpA/rmpA2-positive representatives (out of 47 isolates). Representatives were from 19 hospital laboratories, with rmpA/rmpA2-positive isolates from 10. Nanopore sequencing of 29 representatives of ST147 divided them into those with no virulence plasmid (n=12), those with non-New Delhi metallo-ß-lactamase (NDM) virulence plasmids (n=6) and those carrying bla NDM-5 (n=9) or bla NDM-1 (n=2) virulence plasmids. These plasmids were of IncFIB(pNDM-Mar)/IncHI1B(pNDM-MAR) replicon types. Most of the non-NDM virulence plasmids were highly similar to the originally described KpvST147L_NDM plasmid. Those carrying bla NDM-5 were highly similar to one another and to previously described plasmids in ST383 and carried an extensive array of resistance genes. Comparison of the fully assembled chromosomes indicated multiple introductions of ST147 in UK hospitals.Conclusion. This study highlights the high proportion of representatives of ST147 that carry IncFIB(pNDM-Mar)/IncHI1B(pNDM-MAR) hybrid resistance virulence plasmids. It is important to be aware of the high probability that representatives of this type carry these plasmids combining resistance and virulence determinants and of the consequent increased risk to patients.

Model-based evaluation of admission screening strategies for the detection and control of carbapenemase-producing Enterobacterales in the English hospital setting.

BACKGROUND: Globally, detections of carbapenemase-producing Enterobacterales (CPE) colonisations and infections are increasing. The spread of these highly resistant bacteria poses a serious threat to public health. However, understanding of CPE transmission and evidence on effectiveness of control measures is severely lacking. This paper provides evidence to inform effective admission screening protocols, which could be important in controlling nosocomial CPE transmission. METHODS: CPE transmission within an English hospital setting was simulated with a data-driven individual-based mathematical model. This model was used to evaluate the ability of the 2016 England CPE screening recommendations, and of potential alternative protocols, to identify patients with CPE-colonisation on admission (including those colonised during previous stays or from elsewhere). The model included nosocomial transmission from colonised and infected patients, as well as environmental contamination. Model parameters were estimated using primary data where possible, including estimation of transmission using detailed epidemiological data within a Bayesian framework. Separate models were parameterised to represent hospitals in English areas with low and high CPE risk (based on prevalence). RESULTS: The proportion of truly colonised admissions which met the 2016 screening criteria was 43% in low-prevalence and 54% in high-prevalence areas respectively. Selection of CPE carriers for screening was improved in low-prevalence areas by adding readmission as a screening criterion, which doubled how many colonised admissions were selected. A minority of CPE carriers were confirmed as CPE positive during their hospital stay (10 and 14% in low- and high-prevalence areas); switching to a faster screening test pathway with a single-swab test (rather than three swab regimen) increased the overall positive predictive value with negligible reduction in negative predictive value. CONCLUSIONS: Using a novel within-hospital CPE transmission model, this study assesses CPE admission screening protocols, across the range of CPE prevalence observed in England. It identifies protocol changes-adding readmissions to screening criteria and a single-swab test pathway-which could detect similar numbers of CPE carriers (or twice as many in low CPE prevalence areas), but faster, and hence with lower demand on pre-emptive infection-control resources. Study findings can inform interventions to control this emerging threat, although further work is required to understand within-hospital transmission sources.

Vaccine effectiveness against hospitalisation estimated using a test-negative case-control study design, and comparative odds of hospital admission and severe outcomes with COVID-19 sub-lineages BQ.1, CH.1.1. and XBB.1.5 in England.

Background: Since the first emergence of Omicron BA.1 in England in November 2021, numerous sub-lineages have evolved. In September 2022, BA.5 dominated. The prevalence of BQ.1 increased from October, while the prevalence of CH.1.1 and XBB.1.5 increased from December 2022 and January 2023, respectively. Little is known about the effectiveness of the vaccines against hospitalisation with these sub-lineages, nor the relative severity, so we here used national-level electronic health records from England to estimate vaccine effectiveness and variant severity. Methods: The study period for tests contributing to all analyses was from 5th December 2022 to 2nd April 2023, when the variants of interest were co-circulating. A test-negative case-control study was used to estimate the incremental effectiveness of the bivalent BA.1 booster vaccines against hospitalisation, relative to those with waned immunity where the last dose was at least 6 months prior. The odds of hospital admission for those testing PCR positive on the day of an attendance to accident and emergency departments and the odds of intensive care unit admission or death amongst COVID-19 admissions were compared between variants. Additionally, a Cox proportional hazards survival regression was used to investigate length of stay amongst hospitalised cases by variant. Findings: Our vaccine effectiveness study included 191,229 eligible tests with 1647 BQ.1 cases, 877 CH.1.1 cases, 1357 XBB.1.5 cases and 187,348 test negative controls. There was no difference in incremental vaccine effectiveness against hospitalisation with BQ.1, CH.1.1 or XBB.1.5, nor was there a difference in the severity of these variants. Effectiveness against hospitalisation was 48.0% (95% C.I.; 38.5-56.0%), 29.7% (95% C.I.; 7.5-46.6%) and 52.7% (95% C.I.; 24.6-70.4%) against BQ.1, CH.1.1 and XBB.1.5, respectively, at 5-9 weeks post booster vaccination. Compared to BQ.1, the odds of hospital admission were 0.87 (95% C.I.; 0.77-0.99) and 0.88 (95% C.I.; 0.75-1.02) for CH.1.1 and XBB.1.5 cases attending accident and emergency departments, respectively. There was no significant difference in the odds of admission to intensive care units or death for those with CH.1.1 (OR 0.96, 95% C.I.; 0.71-1.30) or XBB.1.5 (OR 0.67, 95% C.I.; 0.44-1.02) compared to BQ.1. There was also no significant difference in the length of hospital stay by variant. Interpretation: Together, these results provide reassuring evidence that the bivalent BA.1 booster vaccines provide similar protection against hospitalisation with BQ.1, CH.1.1 and XBB.1.5, and that the emergent CH.1.1 and XBB.1.5 sub-lineages do not cause more severe disease than BQ.1. Funding: None.

Evaluating the impact of testing strategies for the detection of nosocomial COVID-19 in English hospitals through data-driven modeling.

Introduction: During the first wave of the COVID-19 pandemic 293,204 inpatients in England tested positive for SARS-CoV-2. It is estimated that 1% of these cases were hospital-associated using European centre for disease prevention and control (ECDC) and Public Health England (PHE) definitions. Guidelines for preventing the spread of SARS-CoV-2 in hospitals have developed over time but the effectiveness and efficiency of testing strategies for preventing nosocomial transmission has not been explored. Methods: Using an individual-based model, parameterised using multiple datasets, we simulated the transmission of SARS-CoV-2 to patients and healthcare workers between March and August 2020 and evaluated the efficacy of different testing strategies. These strategies were: 0) Testing only symptomatic patients on admission; 1) Testing all patients on admission; 2) Testing all patients on admission and again between days 5 and 7, and 3) Testing all patients on admission, and again at days 3, and 5-7. In addition to admissions testing, patients that develop a symptomatic infection while in hospital were tested under all strategies. We evaluated the impact of testing strategy, test characteristics and hospital-related factors on the number of nosocomial patient infections. Results: Modelling suggests that 84.6% (95% CI: 84.3, 84.7) of community-acquired and 40.8% (40.3, 41.3) of hospital-associated SARS-CoV-2 infections are detectable before a patient is discharged from hospital. Testing all patients on admission and retesting after 3 or 5 days increases the proportion of nosocomial cases detected by 9.2%. Adding discharge testing increases detection by a further 1.5% (relative increase). Increasing occupancy rates, number of beds per bay, or the proportion of admissions wrongly suspected of having COVID-19 on admission and therefore incorrectly cohorted with COVID-19 patients, increases the rate of nosocomial transmission. Over 30,000 patients in England could have been discharged while incubating a non-detected SARS-CoV-2 infection during the first wave of the COVID-19 pandemic, of which 3.3% could have been identified by discharge screening. There was no significant difference in the rates of nosocomial transmission between testing strategies or when the turnaround time of the test was increased. Discussion: This study provides insight into the efficacy of testing strategies in a period unbiased by vaccines and variants. The findings are relevant as testing programs for SARS-CoV-2 are scaled back, and possibly if a new vaccine escaping variant emerges.

Attribution of nosocomial seeding to long-term care facility COVID-19 outbreaks.

Residents of long-term care facilities (LTCFs) were disproportionately affected by the COVID-19 pandemic. We assessed the extent to which hospital-associated infections contributed to COVID-19 LTCF outbreaks in England. We matched addresses of cases between March 2020 and June 2021 to reference databases to identify LTCF residents. Linkage to health service records identified hospital-associated infections, with the number of days spent in hospital before positive specimen date used to classify these as definite or probable. Of 149,129 cases in LTCF residents during the study period, 3,748 (2.5%) were definite or probable hospital-associated and discharged to an LTCF. Overall, 431 (0.3%) were identified as index cases of potentially nosocomial-seeded outbreaks (2.7% (431/15,797) of all identified LTCF outbreaks). These outbreaks involved 4,521 resident cases and 1,335 deaths, representing 3.0% and 3.6% of all cases and deaths in LTCF residents, respectively. The proportion of outbreaks that were potentially nosocomial-seeded peaked in late June 2020, early December 2020, mid-January 2021, and mid-April 2021. Nosocomial seeding contributed to COVID-19 LTCF outbreaks but is unlikely to have accounted for a substantial proportion. The continued identification of such outbreaks after the implementation of preventative policies highlights the challenges of preventing their occurrence.

Risk of severe outcomes among Omicron sub-lineages BA.4.6, BA.2.75, and BQ.1 compared to BA.5 in England.

Since the emergence of Omicron variant of SARS-CoV-2 in late 2021, a number of sub-lineages have arisen and circulated internationally. Little is known about the relative severity of Omicron sub-lineages BA.2.75, BA.4.6, and BQ.1. We undertook a case-control analysis to determine the clinical severity of these lineages relative to BA.5, using whole genome sequenced, PCR-confirmed infections, between 1 August 2022 and 27 November 2022, among those who presented to emergency care in England 14 days after and up to one day prior to the positive specimen. A total of 10,375 episodes were included in the analysis; of which, 5,207 (50.2%) were admitted to the hospital or died. Multivariable conditional regression analyses found no evidence of greater odds of hospital admission or death among those with BA.2.75 (odds ratio (OR) = 0.96, 95% confidence interval (CI): 0.84-1.09) and BA.4.6 (OR = 1.02, 95% CI: 0.88- 1.17) or BQ.1 (OR = 1.03, 95% CI: 0.94-1.13) compared to BA.5. Future lineages may not follow the same trend and there remains a need for continued surveillance of COVID-19 variants and their clinical outcomes to inform the public health response.

Reporting England's progress towards the ambitions in the UK action plan for antimicrobial resistance: the English surveillance programme for antimicrobial utilisation and resistance (ESPAUR).

The plans for a new antimicrobial utilization and resistance national surveillance programme, alongside the development of quality measures and methods to monitor unintended outcomes of antimicrobial stewardship and both public and professional behaviour interventions were published in 2013. Since then, England has published an annual surveillance report including outlining progress against the ambitions of the UK national action plans on antimicrobial resistance (2013 to 2018 and 2019 to 2024). A decade later we provide a brief update on progress so far, with a focus on key highlights from the latest report published in November 2022. We also provide our recommendations for areas of focus as we move into the next decade. From an initial focus on antibiotic consumption and resistance, the report now includes surveillance data for antifungals, antivirals (including novel agents, such as those targeting SARS-CoV-2) and antimalarials. Evaluation of key stewardship interventions including professional and public engagement initiatives are also reported, as well as progress against NHS England's (NHSE's) improvement measures.

Trends in coagulase-negative staphylococci (CoNS), England, 2010-2021.

Objective: To review the epidemiology of coagulase-negative staphylococci (CoNS) in England over the recent 12 year period. Methods: Laboratory-confirmed CoNS reported from sterile sites in patients in England to the UK Health Security Agency (UKHSA) between 2010 and 2021 were extracted from the national laboratory database and analysed. Results: Overall, 668 857 episodes of CoNS were reported. Unspeciated CoNS accounted for 56 % (374 228) of episodes, followed by Staphylococcus epidermidis (26 %; 174 050), S. hominis (6.5 %; 43 501) and S. capitis (3.9 %; 25 773). Unspeciated CoNS increased by 8.2 % (95 % CI, 7.1-9.3) annually between 2010 and 2016, then decreased annually by 6.4 % (95 % CI: -4.8 to -7.9) until 2021. Speciated CoNS increased by 47.6 % (95 % CI, 44.5-50.9) annually between 2010 and 2016 and increased annually by 8.9 % (95 % CI: 5.1 to 12.8) until 2021. Antimicrobial susceptibility profiles differed by species. Conclusions: Reports of CoNS from normally sterile body sites in patients in England increased between 2010 and 2016 and remained stable between 2017 and 2021. There has been a striking improvement in species-level identification of CoNS in recent years. Monitoring trends in CoNS epidemiology is crucial for development of observational and clinical intervention studies on individual species.

Incidence of infant Gram-negative invasive bacterial infections in England, 2011-2019: an observational study using population-wide surveillance data.

OBJECTIVE: Invasive bacterial infections account for an estimated 15% of infant deaths worldwide. We aimed to estimate the incidence and trends in invasive bacterial infections in infants caused by Gram-negative pathogens in England during 2011-2019. METHODS: Laboratory-confirmed invasive bacterial infections in infants (<1 year old) were identified in the UK Health Security Agency national laboratory surveillance data from April 2011 to March 2019. Polymicrobial infections were defined as two or more bacterial species from the same normally sterile sample site. Early-onset infections were defined as <7 days from birth and late-onset as ≥7 days (neonates 7-28 days; infants ≥29 days). Trend analyses were carried out using Poisson (for episodes/incidence) and beta (for proportions) regression. RESULTS: The annual incidence of invasive bacterial infections increased by 35.9%, from 189.8 to 258.0 cases per 100 000 live births (p<0.001). Late-onset infections in both neonates and infants increased substantially over the study period (p<0.001), whereas early-onset infections increased slightly (p=0.002). Escherichia coli was the most common Gram-negative pathogen isolated and accounted for 27.2% of the overall rise in Gram-negative infant disease incidence. Polymicrobial infections almost doubled, increasing from 29.2 to 57.7 per 100 000 live births (p<0.001), and mostly involved two species (81.3%, 1604/1974 episodes). CONCLUSIONS: The incidence of Gram-negative invasive bacterial infections in infants increased between 2011/2012 and 2018/2019 in England, driven mainly by an increase in late-onset infections. Further work is required to elucidate the risk factors and drivers of this increased incidence so that opportunities for prevention can be identified.

Comparison of the risk of hospitalisation among BA.1 and BA.2 COVID-19 cases treated with sotrovimab in the community in England.

There are concerns that sotrovimab has reduced efficacy at reducing hospitalisation risk against the BA.2 sub-lineage of the Omicron SARS-CoV-2 variant. We performed a retrospective cohort (n = 8850) study of individuals treated with sotrovimab in the community, with the objective of assessing whether there were any differences in risk of hospitalisation of BA.2 cases compared with BA.1. We estimated that the hazard ratio of hospital admission with a length of stay of 2 days or more was 1.17 for BA.2 compared with BA.1 (95%CI 0.74-1.86). These results suggest that the risk of hospital admission was similar between the two sub-lineages.

Is Panton-Valentine leucocidin (PVL) toxin associated with poor clinical outcomes in patients with community-acquired Staphylococcus aureus bacteraemia?

Introduction. Panton-Valentine leucocidin (PVL) toxin is a potential determinant of virulence associated with S. aureus infection.Gap Statement. The contribution of PVL to S. aureus pathogenicity remains unclear.Aim. To compare clinical outcomes in hospitalized patients with PVL-positive and PVL-negative community-acquired (CA) S. aureus bacteraemia.Methods. Three national datasets were combined to provide clinical and mortality data for patients with CA S. aureus blood culture isolates sent to the UK reference laboratory for PVL testing, August 2018 to August 2021. Multivariable logistic regression models were built for the effect of PVL positivity on 30 day all-cause mortality and 90 day readmission.Results. In 2191 cases of CA S. aureus bacteraemia, there was no association between PVL and mortality (adjusted odds ratio, aOR: 0·90, 95 % confidence interval, CI: 0·50-1·35, P=0·602) and no difference in median LOS (14 versus 15 days, P=0.169). PVL-positive cases had lower odds of readmission (aOR 0·74, CI 0·55-0.98, P=0·038). There was no evidence that MRSA status modified this effect (P=0·207).Conclusions. In patients with CA S. aureus bacteraemia PVL toxin detection was not associated with worse outcomes.

Impact of testing on Clostridioides difficile infection in hospitals across Europe: a mathematical model.

OBJECTIVES: The prevalence of Clostridioides difficile infection (CDI) has been shown to vary markedly between European countries, both in hospitals and in the community. Determining the true prevalence has proven challenging. Without systematic testing in hospitals, the unchecked transmission of CDI can lead to large outbreaks in more susceptible cohorts. We investigate the success of CDI surveillance and control measures across Europe, by examining the dynamics of disease spread from the community into a hospital setting. We focus on national differences, such as variability in testing and sampling, disease prevalence in communities and hospitals, and antimicrobial usage. METHODS: We developed a stochastic, compartmental, dynamic mathematical model parameterized using sampling and testing rate data from COMBACTE-CDI, a multicountry study in which all diarrhoeal stool samples (N = 3163) from European laboratories were tested for CDI, and data for antimicrobial usage and incidence of hospital cases sourced from the European Centre for Disease Prevention and Control. RESULTS: The framework estimates the prevalence of CDI among hospital patients across European countries and explores how national differences impact the dynamics, transmission, and relative incidence of CDI within the hospital setting. The model illustrates the mechanisms influencing these national differences, namely, antimicrobial usage rates, national sampling and testing rates, and community prevalence of CDI. DISCUSSION: Differential costs for testing and practicalities of scaling up testing mean every country needs to consider balancing CDI testing costs against the costs of treatment and care of patients with CDI.

Estimation of the impact of hospital-onset SARS-CoV-2 infections on length of stay in English hospitals using causal inference.

BACKGROUND: From March 2020 through August 2021, 97,762 hospital-onset SARS-CoV-2 infections were detected in English hospitals. Resulting excess length of stay (LoS) created a potentially substantial health and economic burden for patients and the NHS, but we are currently unaware of any published studies estimating this excess. METHODS: We implemented appropriate causal inference methods to determine the extent to which observed additional hospital stay is attributable to the infection rather than the characteristics of the patients. Hospital admissions records were linked to SARS-CoV-2 test data to establish the study population (7.5 million) of all non-COVID-19 admissions to English hospitals from 1st March 2020 to 31st August 2021 with a stay of at least two days. The excess LoS due to hospital-onset SARS-CoV-2 infection was estimated as the difference between the mean LoS observed and in the counterfactual where infections do not occur. We used inverse probability weighted Kaplan-Meier curves to estimate the mean survival time if all hospital-onset SARS-CoV-2 infections were to be prevented, the weights being based on the daily probability of acquiring an infection. The analysis was carried out for four time periods, reflecting phases of the pandemic differing with respect to overall case numbers, testing policies, vaccine rollout and prevalence of variants. RESULTS: The observed mean LoS of hospital-onset cases was higher than for non-COVID-19 hospital patients by 16, 20, 13 and 19 days over the four phases, respectively. However, when the causal inference approach was used to appropriately adjust for time to infection and confounding, the estimated mean excess LoS caused by hospital-onset SARS-CoV-2 was: 2.0 [95% confidence interval 1.8-2.2] days (Mar-Jun 2020), 1.4 [1.2-1.6] days (Sep-Dec 2020); 0.9 [0.7-1.1] days (Jan-Apr 2021); 1.5 [1.1-1.9] days (May-Aug 2021). CONCLUSIONS: Hospital-onset SARS-CoV-2 is associated with a small but notable excess LoS, equivalent to 130,000 bed days. The comparatively high LoS observed for hospital-onset COVID-19 patients is mostly explained by the timing of their infections relative to admission. Failing to account for confounding and time to infection leads to overestimates of additional length of stay and therefore overestimates costs of infections, leading to inaccurate evaluations of control strategies.

Trends in COVID-19 hospital outcomes in England before and after vaccine introduction, a cohort study.

Widespread vaccination campaigns have changed the landscape for COVID-19, vastly altering symptoms and reducing morbidity and mortality. We estimate trends in mortality by month of admission and vaccination status among those hospitalised with COVID-19 in England between March 2020 to September 2021, controlling for demographic factors and hospital load. Among 259,727 hospitalised COVID-19 cases, 51,948 (20.0%) experienced mortality in hospital. Hospitalised fatality risk ranged from 40.3% (95% confidence interval 39.4-41.3%) in March 2020 to 8.1% (7.2-9.0%) in June 2021. Older individuals and those with multiple co-morbidities were more likely to die or else experienced longer stays prior to discharge. Compared to unvaccinated people, the hazard of hospitalised mortality was 0.71 (0.67-0.77) with a first vaccine dose, and 0.56 (0.52-0.61) with a second vaccine dose. Compared to hospital load at 0-20% of the busiest week, the hazard of hospitalised mortality during periods of peak load (90-100%), was 1.23 (1.12-1.34). The prognosis for people hospitalised with COVID-19 in England has varied substantially throughout the pandemic and according to case-mix, vaccination, and hospital load. Our estimates provide an indication for demands on hospital resources, and the relationship between hospital burden and outcomes.

Burden of SARS-CoV-2 infection in healthcare workers during second wave in England and impact of vaccines: prospective multicentre cohort study (SIREN) and mathematical model.

OBJECTIVE: To describe the incidence of, risk factors for, and impact of vaccines on primary SARS-CoV-2 infection during the second wave of the covid-19 pandemic in susceptible hospital healthcare workers in England. DESIGN: Multicentre prospective cohort study. SETTING: National Health Service secondary care health organisations (trusts) in England between 1 September 2020 and 30 April 2021. PARTICIPANTS: Clinical, support, and administrative staff enrolled in the SARS-CoV-2 Immunity and Reinfection Evaluation (SIREN) study with no evidence of previous infection. Vaccination status was obtained from national covid-19 vaccination registries and self-reported. MAIN OUTCOME MEASURE: SARS-CoV-2 infection confirmed by polymerase chain reaction. Mixed effects logistic regression was conducted to determine demographic and occupational risk factors for infection, and an individual based mathematical model was used to predict how large the burden could have been if vaccines had not been available from 8 December 2020 . RESULTS: During England's second wave, 12.9% (2353/18 284) of susceptible SIREN participants became infected with SARS-CoV-2. Infections peaked in late December 2020 and decreased from January 2021, concurrent with the cohort's rapid vaccination coverage and a national lockdown. In multivariable analysis, factors increasing the likelihood of infection in the second wave were being under 25 years old (20.3% (132/651); adjusted odds ratio 1.35, 95% confidence interval 1.07 to 1.69), living in a large household (15.8% (282/1781); 1.54, 1.23 to 1.94, for participants from households of five or more people), having frequent exposure to patients with covid-19 (19.2% (723/3762); 1.79, 1.56 to 2.06, for participants with exposure every shift), working in an emergency department or inpatient ward setting (20.8% (386/1855); 1.76, 1.45 to 2.14), and being a healthcare assistant (18.1% (267/1479); 1.43, 1.16 to 1.77). Time to first vaccination emerged as being strongly associated with infection (P<0.001), with each additional day multiplying a participant's adjusted odds ratio by 1.02. Mathematical model simulations indicated that an additional 9.9% of all patient facing hospital healthcare workers would have been infected were it not for the rapid vaccination coverage. CONCLUSIONS: The rapid covid-19 vaccine rollout from December 2020 averted infection in a large proportion of hospital healthcare workers in England: without vaccines, second wave infections could have been 69% higher. With booster vaccinations being needed for adequate protection from the omicron variant, and perhaps the need for further boosters for future variants, ensuring equitable delivery to healthcare workers is essential. The findings also highlight occupational risk factors that persisted in healthcare workers despite vaccine rollout; a greater understanding of the transmission dynamics responsible for these is needed to help to optimise the infection prevention and control policies that protect healthcare workers from infection and therefore to support staffing levels and maintain healthcare provision. TRIAL REGISTRATION: ISRCTN registry ISRCTN11041050.

Incidence and aetiology of infant Gram-negative bacteraemia and meningitis: systematic review and meta-analysis.

BACKGROUND: One in six infant deaths worldwide are caused by invasive bacterial infections, of which a substantial but unquantified proportion are caused by Gram-negative bacteria. METHODS: We conducted a systematic review of studies published from 31 May 2010 to 1 June 2020 indexed in MEDLINE, Embase and Global Health databases. We performed meta-analyses of the incidence of Gram-negative bacteraemia and of individual Gram-negative species as proportions of all infant bacteraemia, stratified by onset (early vs late) and country income (low/middle vs high). RESULTS: 152 studies from 54 countries were included, 60 in high-income countries (HIC) and 92 in low-income/middle-income countries (LMIC). Gram-negatives represented a higher proportion (53%, 95% CI 49% to 57%) of all infant bacteraemia in LMIC compared with HIC (28%, 95% CI 25% to 32%). Incidence of infant Gram-negative bacteraemia was 2.01 (95% CI 1.15 to 3.51) per 1000 live births; it was five times higher in LMIC (4.35, 95% CI 2.94 to 6.43) compared with HIC (0.73, 95% CI 0.39 to 7.5). In HIC, Escherichia coli was the leading Gram-negative pathogen, representing 19.2% (95% CI 15.6% to 23.4%) of early and 7.3% (95% CI 5.3% to 10.1%) of all late-onset bacteraemia; Klebsiella spp were the next most common cause (5.3%) of late-onset bacteraemia. In LMIC, Klebsiella spp caused 16.4% (95% CI 11.5% to 22.7%) of early and 15.0% (95% CI 10.1% to 21.8%) of late-onset bacteraemia, followed by E. coli (early-onset 7.50%, 95% CI 4.98% to 11.1%; late-onset 6.53%, 95% CI 4.50% to 9.39%) and Pseudomonas spp (early-onset 3.93%, 95% CI 2.04% to 7.44%; late-onset 2.81%, 95% CI 1.99% to 3.95%). CONCLUSION: E. coli, Klebsiella and Pseudomonas spp cause 20%-28% of early-onset infant bacteraemia and 14% cases of infant meningitis worldwide. Implementation of preventive measures could reduce the high incidence of Gram-negative bacteraemia in LMIC. PROSPERO REGISTRATION NUMBER: CRD42020191618.

The contribution of hospital-acquired infections to the COVID-19 epidemic in England in the first half of 2020.

BACKGROUND: SARS-CoV-2 is known to transmit in hospital settings, but the contribution of infections acquired in hospitals to the epidemic at a national scale is unknown. METHODS: We used comprehensive national English datasets to determine the number of COVID-19 patients with identified hospital-acquired infections (with symptom onset > 7 days after admission and before discharge) in acute English hospitals up to August 2020. As patients may leave the hospital prior to detection of infection or have rapid symptom onset, we combined measures of the length of stay and the incubation period distribution to estimate how many hospital-acquired infections may have been missed. We used simulations to estimate the total number (identified and unidentified) of symptomatic hospital-acquired infections, as well as infections due to onward community transmission from missed hospital-acquired infections, to 31st July 2020. RESULTS: In our dataset of hospitalised COVID-19 patients in acute English hospitals with a recorded symptom onset date (n = 65,028), 7% were classified as hospital-acquired. We estimated that only 30% (range across weeks and 200 simulations: 20-41%) of symptomatic hospital-acquired infections would be identified, with up to 15% (mean, 95% range over 200 simulations: 14.1-15.8%) of cases currently classified as community-acquired COVID-19 potentially linked to hospital transmission. We estimated that 26,600 (25,900 to 27,700) individuals acquired a symptomatic SARS-CoV-2 infection in an acute Trust in England before 31st July 2020, resulting in 15,900 (15,200-16,400) or 20.1% (19.2-20.7%) of all identified hospitalised COVID-19 cases. CONCLUSIONS: Transmission of SARS-CoV-2 to hospitalised patients likely caused approximately a fifth of identified cases of hospitalised COVID-19 in the "first wave" in England, but less than 1% of all infections in England. Using time to symptom onset from admission for inpatients as a detection method likely misses a substantial proportion (> 60%) of hospital-acquired infections.

Assessment of mortality and hospital admissions associated with confirmed infection with SARS-CoV-2 Alpha variant: a matched cohort and time-to-event analysis, England, October to December 2020.

BackgroundThe emergence of the SARS-CoV-2 Alpha variant in England coincided with a rapid increase in the number of PCR-confirmed COVID-19 cases in areas where the variant was concentrated.AimOur aim was to assess whether infection with Alpha was associated with more severe clinical outcomes than the wild type.MethodsLaboratory-confirmed infections with genomically sequenced SARS-CoV-2 Alpha and wild type between October and December 2020 were linked to routine healthcare and surveillance datasets. We conducted two statistical analyses to compare the risk of hospital admission and death within 28 days of testing between Alpha and wild-type infections: a matched cohort study and an adjusted Cox proportional hazards model. We assessed differences in disease severity by comparing hospital admission and mortality, including length of hospitalisation and time to death.ResultsOf 63,609 COVID-19 cases sequenced in England between October and December 2020, 6,038 had the Alpha variant. In the matched cohort analysis, we matched 2,821 cases with Alpha to 2,821 to cases with wild type. In the time-to-event analysis, we observed a 34% increased risk in hospitalisation associated with Alpha compared with wild type, but no significant difference in the risk of mortality.ConclusionWe found evidence of increased risk of hospitalisation after adjusting for key confounders, suggesting increased infection severity associated with the Alpha variant. Rapid assessments of the relative morbidity in terms of clinical outcomes and mortality associated with emerging SARS-CoV-2 variants compared with dominant variants are required to assess overall impact of SARS-CoV-2 mutations.

The contribution of hospital-acquired infections to the COVID-19 epidemic in England in the first half of 2020.

Background SARS-CoV-2 is known to transmit in hospital settings, but the contribution of infections acquired in hospitals to the epidemic at a national scale is unknown. Methods We used comprehensive national English datasets to determine the number of COVID-19 patients with identified hospital-acquired infections (with symptom onset >7 days after admission and before discharge) in acute English hospitals up to August 2020. As patients may leave the hospital prior to detection of infection or have rapid symptom onset, we combined measures of the length of stay and the incubation period distribution to estimate how many hospital-acquired infections may have been missed. We used simulations to estimate the total number (identified and unidentified) of symptomatic hospital-acquired infections, as well as infections due to onward community transmission from missed hospital-acquired infections, to 31 st July 2020. Results In our dataset of hospitalised COVID-19 patients in acute English hospitals with a recorded symptom onset date (n = 65,028), 7% were classified as hospital-acquired. We estimated that only 30% (range across weeks and 200 simulations: 20-41%) of symptomatic hospital-acquired infections would be identified, with up to 15% (mean, 95% range over 200 simulations: 14.1%-15.8%) of cases currently classified as community-acquired COVID-19 potentially linked to hospital transmission. We estimated that 26,600 (25,900 to 27,700) individuals acquired a symptomatic SARS-CoV-2 infection in an acute Trust in England before 31st July 2020, resulting in 15,900 (15,200-16,400) or 20.1% (19.2%-20.7%) of all identified hospitalised COVID-19 cases. Conclusions Transmission of SARS-CoV-2 to hospitalised patients likely caused approximately a fifth of identified cases of hospitalised COVID-19 in the "first wave" in England, but less than 1% of all infections in England. Using time to symptom onset from admission for inpatients as a detection method likely misses a substantial proportion (>60%) of hospital-acquired infections.