COVID-19 cluster surveillance using exposure data collected from routine contact tracing: The genomic validation of a novel informatics-based approach to outbreak detection in England.

Contact tracing was used globally to prevent onwards transmission of COVID-19. Tracing contacts alone is unlikely to be sufficient in controlling community transmission, due to the pre-symptomatic, overdispersed and airborne nature of COVID-19 transmission. We describe and demonstrate the validity of a national enhanced contact tracing programme for COVID-19 cluster surveillance in England. Data on cases occurring between October 2020 and September 2021 were extracted from the national contact tracing system. Exposure clusters were identified algorithmically by matching ≥2 cases attending the same event, identified by matching postcode and event category within a 7-day rolling window. Genetic validity was defined as exposure clusters with ≥2 cases from different households with identical viral sequences. Exposure clusters were fuzzy matched to the national incident management system (HPZone) by postcode and setting description. Multivariable logistic regression modelling was used to determine cluster characteristics associated with genetic validity. Over a quarter of a million (269,470) exposure clusters were identified. Of the eligible clusters, 25% (3,306/13,008) were genetically valid. 81% (2684/3306) of these were not recorded on HPZone and were identified on average of one day earlier than incidents recorded on HPZone. Multivariable analysis demonstrated that exposure clusters occurring in workplaces (aOR = 5·10, 95% CI 4·23-6·17) and education (aOR = 3·72, 95% CI 3·08-4·49) settings were those most strongly associated with genetic validity. Cluster surveillance using enhanced contact tracing in England was a timely, comprehensive and systematic approach to the detection of transmission events occurring in community settings. Cluster surveillance can provide intelligence to stakeholders to support the assessment and management of clusters of COVID-19 at a local, regional, and national level. Future systems should include predictive modelling and network analysis to support risk assessment of exposure clusters to improve the effectiveness of enhanced contract tracing for outbreak detection.

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 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.

Workplace exposures associated with COVID-19: evidence from a case-control study with multiple sampling periods in England, August-October 2020.

We investigated risk factors associated with COVID-19 by conducting a retrospective, frequency-matched case-control study, with three sampling periods (August-October 2020). We compared cases completing routine contact tracing to asymptomatic population controls. Multivariable analyses estimated adjusted odds ratios (aORs) for non-household community settings. Meta-analyses using random effects provided pooled odds ratios (pORs). Working in healthcare (pOR 2.87; aORs 2.72, 2.81, 3.08, for study periods 1-3 respectively), social care (pOR 4.15; aORs 2.46, 5.06, 5.41, for study periods 1-3 respectively) or hospitality (pOR 2.36; aORs 2.01, 2.54, 2.63, for study periods 1-3 respectively) were associated with increased odds of being a COVID-19 case. Additionally, working in bars, pubs and restaurants, warehouse settings, construction, educational settings were significantly associated. While definitively determining where transmission occurs is impossible, we provide evidence that in certain sectors, the impact of mitigation measures may only be partial and reinforcement of measures should be considered in these settings.

Genomic epidemiology of SARS-CoV-2 in a UK university identifies dynamics of transmission.

Understanding SARS-CoV-2 transmission in higher education settings is important to limit spread between students, and into at-risk populations. In this study, we sequenced 482 SARS-CoV-2 isolates from the University of Cambridge from 5 October to 6 December 2020. We perform a detailed phylogenetic comparison with 972 isolates from the surrounding community, complemented with epidemiological and contact tracing data, to determine transmission dynamics. We observe limited viral introductions into the university; the majority of student cases were linked to a single genetic cluster, likely following social gatherings at a venue outside the university. We identify considerable onward transmission associated with student accommodation and courses; this was effectively contained using local infection control measures and following a national lockdown. Transmission clusters were largely segregated within the university or the community. Our study highlights key determinants of SARS-CoV-2 transmission and effective interventions in a higher education setting that will inform public health policy during pandemics.

Penetration and impact of COVID-19 in long term care facilities in England: population surveillance study.

BACKGROUND: Long-term care facilities (LTCF) worldwide have suffered high rates of COVID-19, reflecting the vulnerability of the persons who live there and the institutional nature of care delivered. This study describes the impact of the pandemic on incidences and deaths in LTCF across England. METHODS: Laboratory-confirmed SARS-CoV-2 cases in England, notified to Public Health England from 01 Jan to 25 Dec 2020, were address-matched to an Ordnance Survey reference database to identify residential property classifications. Data were analysed to characterize cases and identify clusters. Associated deaths were defined as death within 60 days of diagnosis or certified as cause of death. RESULTS: Of 1 936 315 COVID-19 cases, 81 275 (4.2%) and 10 050 (0.52%) were identified as resident or staff in an LTCF, respectively, with 20 544 associated deaths in residents, accounting for 31.3% of all COVID-19 deaths. Cases were identified in 69.5% of all LTCFs in England, with 33.1% experiencing multiple outbreaks. Multivariable analysis showed a 67% increased odds of death in residents [adjusted odds ratio (aOR): 1.67, 95% confidence interval (CI): 1.63-1.72], compared with those not residing in LTCFs. A total of 10 321 outbreaks were identified at these facilities, of which 8.2% identified the first case as a staff member. CONCLUSIONS: Over two-thirds of LTCFs have experienced large and widespread outbreaks of COVID-19, and just under one-third of all COVID-19 deaths occurring in this setting in spite of early policies. A key implication of our findings is upsurges in community incidences seemingly leading to increased outbreaks in LTCFs; thus, identifying and shielding residents from key sources of infection are vital to reduce the number of future outbreaks.

National surveillance of bacterial and fungal coinfection and secondary infection in COVID-19 patients in England: lessons from the first wave.

OBJECTIVES: The impact of bacterial/fungal infections on the morbidity and mortality of persons with coronavirus disease 2019 (COVID-19) remains unclear. We have investigated the incidence and impact of key bacterial/fungal infections in persons with COVID-19 in England. METHODS: We extracted laboratory-confirmed cases of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (1st January 2020 to 2nd June 2020) and blood and lower-respiratory specimens positive for 24 genera/species of clinical relevance (1st January 2020 to 30th June 2020) from Public Health England's national laboratory surveillance system. We defined coinfection and secondary infection as a culture-positive key organism isolated within 1 day or 2-27 days, respectively, of the SARS-CoV-2-positive date. We described the incidence and timing of bacterial/fungal infections and compared characteristics of COVID-19 patients with and without bacterial/fungal infection. RESULTS: 1% of persons with COVID-19 (2279/223413) in England had coinfection/secondary infection, of which >65% were bloodstream infections. The most common causative organisms were Escherichia coli, Staphylococcus aureus and Klebsiella pneumoniae. Cases with coinfection/secondary infections were older than those without (median 70 years (IQR 58-81) versus 55 years (IQR 38-77)), and a higher percentage of cases with secondary infection were of Black or Asian ethnicity than cases without (6.7% versus 4.1%, and 9.9% versus 8.2%, respectively, p < 0.001). Age-sex-adjusted case fatality rates were higher in COVID-19 cases with a coinfection (23.0% (95%CI 18.8-27.6%)) or secondary infection (26.5% (95%CI 14.5-39.4%)) than in those without (7.6% (95%CI 7.5-7.7%)) (p < 0.005). CONCLUSIONS: Coinfection/secondary bacterial/fungal infections were rare in non-hospitalized and hospitalized persons with COVID-19, varied by ethnicity and age, and were associated with higher mortality. However, the inclusion of non-hospitalized persons with asymptomatic/mild COVID-19 likely underestimated the rate of secondary bacterial/fungal infections. This should inform diagnostic testing and antibiotic prescribing strategy.

Healthcare-associated COVID-19 in England: A national data linkage study.

OBJECTIVES: Nosocomial transmission was an important aspect of SARS-CoV-1 and MERS-CoV outbreaks. Healthcare-associated SARS-CoV-2 infection has been reported in single and multi-site hospital-based studies in England, but not nationally. METHODS: Admission records for all hospitals in England were linked to SARS-CoV-2 national test data for the period 01/03/2020 to 31/08/2020. Case definitions were: community-onset community-acquired, first positive test <14 days pre-admission, up to day 2 of admission; hospital-onset indeterminate healthcare-associated, first positive on day 3-7; hospital-onset probable healthcare-associated, first positive on day 8-14; hospital-onset definite healthcare-associated, first positive from day 15 of admission until discharge; community-onset possible healthcare-associated, first positive test ≤14 days post-discharge. RESULTS: One-third (34.4%, 100,859/293,204) of all laboratory-confirmed COVID-19 cases were linked to a hospital record. Hospital-onset probable and definite cases represented 5.3% (15,564/293,204) of all laboratory-confirmed cases and 15.4% (15,564/100,859) of laboratory-confirmed cases among hospital patients. Community-onset community-acquired and community-onset possible healthcare-associated cases represented 86.5% (253,582/293,204) and 5.1% (14,913/293,204) of all laboratory-confirmed cases, respectively. CONCLUSIONS: Up to 1 in 6 SARS-CoV-2 infections among hospitalised patients with COVID-19 in England during the first 6 months of the pandemic could be attributed to nosocomial transmission, but these represent less than 1% of the estimated 3 million COVID-19 cases in this period.

UK Renal Registry 18th Annual Report: Chapter 12 Epidemiology of Reported Infections amongst Patients Receiving Dialysis for Established Renal Failure in England 2013 to 2014: a Joint Report from Public Health England and the UK Renal Registry.

From 1st May 2013 to 30th April 2014 there were 35 episodes of Methicillin resistant Staphylococcus aureus (MRSA) bacteraemia in established renal failure patients on dialysis. This is now fairly stable year-on-year equating to a rate of 0.15 episodes per 100 dialysis patient years, following an initial decline in rates from 4.0 episodes per 100 dialysis patient years in 2005 when reporting began. Methicillin sensitive Staphylococcus aureus (MSSA) bacteraemia rates were slightly higher this year at 2.23 per 100 dialysis patient years (compared with 1.59 episodes per 100 dialysis patient years last year) with 526 episodes of blood stream infection reported. In 2005, the first year this was reported, there were 1,114 MSSA bacteraemias in 54 centres. There were 247 Clostridium difficile infection episodes with a rate of 1.05 per 100 dialysis patient years, slightly higher than last year at 0.55 episodes per 100 dialysis patient years. Escherichia coli infections occurred at a rate of 1.49 per 100 dialysis patient years, very similar to the rate reported last year (1.32 episodes per 100 dialysis patient years). This report has utilised a new methodology to identify cases, linking all established renal failure cases known to the UK Renal Registry (UKRR) with all infections reported to Public Health England and avoids the need for the local microbiology team to flag the patient as a renal patient. This may have increased the reliability of diagnosis at the UKRR level. In each infection for which access data were collected, the presence of a central venous catheter appeared to correlate with increased risk.