ABSTRACT
Objectives: Patients requiring haemodialysis are at increased risk of serious illness with SARS-CoV-2 infection. To improve the understanding of transmission risks in six Scottish renal dialysis units, we utilised the rapid whole-genome sequencing data generated by the COG-UK consortium. Methods: We combined geographical, temporal and genomic sequence data from the community and hospital to estimate the probability of infection originating from within the dialysis unit, the hospital or the community using Bayesian statistical modelling and compared these results to the details of epidemiological investigations. Results: Of 671 patients, 60 (8.9%) became infected with SARS-CoV-2, of whom 16 (27%) died. Within-unit and community transmission were both evident and an instance of transmission from the wider hospital setting was also demonstrated. Conclusions: Near-real-time SARS-CoV-2 sequencing data can facilitate tailored infection prevention and control measures, which can be targeted at reducing risk in these settings. Key words: SARS-CoV-2, COVID-19, haemodialysis, renal dialysis unit, infection control, rapid sequencing, outbreak, nosocomial Key words: SARS-CoV-2, COVID-19, haemodialysis, renal dialysis unit, infection control, rapid sequencing, outbreak, nosocomial
Subject(s)
COVID-19ABSTRACT
Background Shielding (extended self-isolation) of people judged, a priori, to be at high-risk from COVID-19 has been used by some countries to protect the individuals and reduce demand on health services. It is unclear how well this strategy works in either regard. Methods A general population study was conducted using linked primary care, prescribing, laboratory, hospital and death records up to end of May 2020. Poisson regression models and population attributable fractions were used to compare COVID-19 outcomes by overall risk category, and individual risk criteria: confirmed infection, hospitalisation, intensive care unit (ICU) admission, population mortality and case-fatality. Results Of the 1.3 million population, 32,533 (2.47%) had been advised to shield, a further 347,374 (26.41%) were classified as moderate risk. Testing for COVID-19 was more common in the shielded (6.75%) and moderate (1.99%) than low (0.72%) risk categories. Referent to low-risk, the shielded group had higher risk of confirmed infection (RR 7.91, 95% 7.01-8.92), case-fatality (RR 5.19, 95% CI 4.12-6.53) and population mortality (RR 48.64, 95% 37.23-63.56). The moderate risk had intermediate risk of confirmed infection (RR 4.11, 95% CI 3.82-4.42) and population mortality (RR 26.10, 95% CI 20.89-32.60), but had comparable case-fatality (RR 5.13, 95% CI 4.24-6.21) to the shielded, and accounted for a higher proportion of deaths (PAF 75.27% vs 13.38%). Age [≥]70 years made the largest contribution to deaths (49.53%) and was associated with an 8-fold risk of infection, 7-fold case-fatality and 74-fold mortality. Conclusions Shielding has not been effective at preventing deaths in those with highest risk. To be effective as a population strategy, shielding criteria would need to be widely expanded to include other criteria, such as the elderly.
Subject(s)
COVID-19ABSTRACT
BACKGROUNDIt is now well recognised that the risk of severe COVID-19 increases with some long-term conditions (LTCs). However, prior research primarily focuses on individual LTCs and there is a lack of data on the influence of multimorbidity ([≥]2 LTCs) on the risk of COVID-19. Given the high prevalence of multimorbidity, more detailed understanding of the associations with multimorbidity and COVID-19 would improve risk stratification and help protect those most vulnerable to severe COVID-19. Here we examine the relationships between multimorbidity, polypharmacy (a proxy of multimorbidity), and COVID-19; and how these differ by sociodemographic, lifestyle, and physiological prognostic factors. METHODS AND FINDINGSWe studied data from UK Biobank (428,199 participants; aged 37-73; recruited 2006-2010) on self-reported LTCs, medications, sociodemographic, lifestyle, and physiological measures which were linked to COVID-19 test data. Poisson regression models examined risk of COVID-19 by multimorbidity/polypharmacy and effect modification by COVID-19 prognostic factors (age/sex/ethnicity/socioeconomic status/smoking/physical activity/BMI/systolic blood pressure/renal function). 4,498 (1.05%) participants were tested; 1,324 (0.31%) tested positive for COVID-19. Compared with no LTCs, relative risk (RR) of COVID-19 in those with 1 LTC was no higher (RR 1.12 (CI 0.96-1.30)), whereas those with [≥]2 LTCs had 48% higher risk; RR 1.48 (1.28-1.71). Compared with no cardiometabolic LTCs, having 1 and [≥]2 cardiometabolic LTCs had a higher risk of COVID-19; RR 1.28 (1.12-1.46) and 1.77 (1.46-2.15), respectively. Polypharmacy was associated with a dose response increased risk of COVID-19. All prognostic factors were associated with a higher risk of COVID-19 infection in multimorbidity; being non-white, most socioeconomically deprived, BMI [≥]40 kg/m2, and reduced renal function were associated with the highest risk of COVID-19 infection: RR 2.81 (2.09-3.78); 2.79 (2.00-3.90); 2.66 (1.88-3.76); 2.13 (1.46-3.12), respectively. No multiplicative interaction between multimorbidity and prognostic factors was identified. Important limitations include the low proportion of UK Biobank participants with COVID-19 test data (1.05%) and UK Biobank participants being more affluent, healthier and less ethnically diverse than the general population. CONCLUSIONSIncreasing multimorbidity, especially cardiometabolic multimorbidity, and polypharmacy are associated with a higher risk of developing COVID-19. Those with multimorbidity and additional factors, such as non-white ethnicity, are at heightened risk of COVID-19. Author summaryO_ST_ABSWhy was this study done?C_ST_ABSO_LIMultimorbidity is a growing global challenge, but thus far LTC prognostic factors for severe COVID-19 primarily involve single conditions and there is a lack of data on the influence of multimorbidity on the risk of COVID-19. C_LIO_LIAs countries move from the lockdown phase of COVID-19, clinicians need more information about risk stratification to appropriately advise patients with multimorbidity about risk prevention steps. C_LI What did the researchers do and find?O_LIParticipants with multimorbidity ([≥]2 LTCs) had a 48% higher risk of a positive COVID-19 test, those with cardiometabolic multimorbidity had a 77% higher risk, than those without that type of multimorbidity. C_LIO_LIThose from non-white ethnicities with multimorbidity had nearly three times the risk of having COVID-19 infection compared to those of white ethnicity C_LIO_LIPeople with multimorbidity with the highest risk of COVID-19 infection were the most socioeconomically deprived, those with BMI [≥]40 kg/m2, and those with reduced renal function. C_LI What do these findings mean?O_LIIndividuals with [≥]2 LTCs, especially if these are cardiometabolic in nature, should be particularly stringent in adhering to preventive measures, such as physical distancing and hand hygiene. C_LIO_LIOur findings have implications for clinicians, occupational health and employers when considering work-place environments, appropriate advice for patients, and adaptations that might be required to protect such staff, identified here, as higher risk. C_LI