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Objectives: To quantify the risk of death among people with rare autoimmune rheumatic diseases (RAIRD) during the UK 2020 COVID-19 pandemic compared with the general population, and compared with their pre-COVID risk., Methods: We conducted a cohort study in Hospital Episode Statistics for England from 2003 onwards, and linked data from the NHS Personal Demographics Service. We used ONS published data for general population mortality rates., Results: We included 168 691 people with a recorded diagnosis of RAIRD alive on 1 March 2020. Their median age was 61.7 (IQR 41.5-75.4) years, and 118 379 (70.2%) were female. Our case ascertainment methods had a positive predictive value of 85%. A total of 1815 (1.1%) participants died during March and April 2020. The age-standardized mortality rate (ASMR) among people with RAIRD (3669.3; 95% CI: 3500.4, 3838.1 per 100 000 person-years) was 1.44 (95% CI: 1.42, 1.45) times higher than the average ASMR during the same months of the previous 5 years, whereas in the general population of England it was 1.38 times higher. Age-specific mortality rates in people with RAIRD compared with the pre-COVID rates were higher from the age of 35 upwards, whereas in the general population the increased risk began from age 55 upwards. Women had a greater increase in mortality rates during COVID-19 compared with men., Conclusion: The risk of all-cause death is more prominently raised during COVID-19 among people with RAIRD than among the general population. We urgently need to quantify how much risk is due to COVID-19 infection and how much is due to disruption to health-care services., (© The Author(s) 2020. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Background: Up to 70% of patients report ongoing symptoms 4 weeks after hospitalisation for pneumonia; the impact on primary care is poorly understood., Aim: To investigate the frequency of primary care consultations after hospitalisation for pneumonia, and the reasons for consultation., Design and Setting: A population-based cohort study in England using a UK primary care database of anonymised medical records (Clinical Practice Research Datalink [CPRD]) linked to Hospital Episode Statistics (HES)., Method: Adults with the first International Classification of Diseases, 10th Revision (ICD-10) code for pneumonia (J12-J18) recorded in HES between July 2002 and June 2017 were included. Primary care consultation within 30 days of discharge was identified as the recording of any medical Read code (excluding administration-related codes) in CPRD. Competing-risks regression analyses were conducted to determine the predictors of consultation and antibiotic use at consultation; death and readmission were competing events. Reasons for consultation were examined., Results: Of 56 396 adults, 55.9% ( n = 31 542) consulted primary care within 30 days of hospital discharge. The rate of consultation was highest within 7 days (4.7 per 100 person-days). The strongest predictor for consultation was a higher number of primary care consultations in the year before index admission (adjusted subhazard ratio [sHR] 8.98, 95% confidence interval [CI] = 6.42 to 12.55). The most common reason for consultation was for a respiratory disorder (40.7%, n = 12 840), 11.8% for pneumonia specifically. At consultation, 31.1% ( n = 9823) received further antibiotics. Penicillins (41.6%, n = 5753/13 829) and macrolides (21.9%, n = 3029/13 829) were the most common antibiotics prescribed., Conclusion: Following hospitalisation for pneumonia, a significant proportion of patients consulted primary care within 30 days, highlighting the morbidity experienced by patients during recovery from pneumonia., (© The Authors.)

Disease poses a significant threat to aquaculture. While there are a number of factors contributing to pathogen transmission risk, movement of live fish is considered the most important. Understanding live fish movement patterns for different aquaculture sectors is therefore crucial to predicting disease occurrence and necessary for the development of effective, risk-based biosecurity, surveillance and containment policies. However, despite this, our understanding of live movement patterns of key aquaculture species, namely salmonids and cyprinids, within England and Wales remains limited. In this study, networks reflecting live fish movements associated with the cyprinid and salmonid sectors in England and Wales were constructed. The structure, composition and key attributes of each network were examined and compared to provide insight into the nature of trading patterns and connectedness, as well as highlight sites at a high risk of spreading disease. Connectivity at both site and catchment level was considered to facilitate understanding at different resolutions, providing further insight into disease outbreaks, with industry wide implications. The study highlighted that connectivity through live fish movements was extensive for both industries. The salmonid and cyprinid networks comprised 2533 and 3645 nodes, with a network density of 5.81 × 10 -4 and 4.2 × 10 -4 , respectively. The maximum network reach of 2392 in the salmonid network was higher, both in absolute terms and as a proportion of the overall network, compared to maximum network reach of 2085 in the cyprinid network. However, in contrast, the number of sites in the cyprinid network with a network reach greater than one was 513, compared to 171 in the salmonid network. Patterns of connectivity indicated potential for more frequent yet smaller scale disease outbreaks in the cyprinid industry and less frequent but larger scale outbreaks in the salmonid industry. Further, high connectivity between river catchments within both networks was shown, posing challenges for zoning at the catchment level for the purpose of disease management. In addition to providing insight into pathogen transmission and epidemic potential within the salmonid and cyprinid networks, the study highlights the utility of network analysis, and the value of accessible, accurate live fish movement data in this context. The application of outputs from this study, and network analysis methodology, to inform future disease surveillance and control policies, both within England and Wales and more broadly, is discussed., (Copyright © 2020. Published by Elsevier B.V.)