Accelerated waning of the humoral response to COVID-19 vaccines in obesity.

Obesity is associated with an increased risk of severe Coronavirus Disease 2019 (COVID-19) infection and mortality. COVID-19 vaccines reduce the risk of serious COVID-19 outcomes; however, their effectiveness in people with obesity is incompletely understood. We studied the relationship among body mass index (BMI), hospitalization and mortality due to COVID-19 among 3.6 million people in Scotland using the Early Pandemic Evaluation and Enhanced Surveillance of COVID-19 (EAVE II) surveillance platform. We found that vaccinated individuals with severe obesity (BMI > 40 kg/m2) were 76% more likely to experience hospitalization or death from COVID-19 (adjusted rate ratio of 1.76 (95% confidence interval (CI), 1.60-1.94). We also conducted a prospective longitudinal study of a cohort of 28 individuals with severe obesity compared to 41 control individuals with normal BMI (BMI 18.5-24.9 kg/m2). We found that 55% of individuals with severe obesity had unquantifiable titers of neutralizing antibody against authentic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus compared to 12% of individuals with normal BMI (P = 0.0003) 6 months after their second vaccine dose. Furthermore, we observed that, for individuals with severe obesity, at any given anti-spike and anti-receptor-binding domain (RBD) antibody level, neutralizing capacity was lower than that of individuals with a normal BMI. Neutralizing capacity was restored by a third dose of vaccine but again declined more rapidly in people with severe obesity. We demonstrate that waning of COVID-19 vaccine-induced humoral immunity is accelerated in individuals with severe obesity. As obesity is associated with increased hospitalization and mortality from breakthrough infections, our findings have implications for vaccine prioritization policies.

Investigation of healthcare-associated SARS-CoV-2 infection: Learning outcomes from an investigative process in the initial phase of the pandemic.

Background: Healthcare-associated (HCA) SARS-CoV-2 infection is a significant contributor to the spread of the 2020 pandemic. Timely review of HCA cases is essential to identify learning to inform infection prevention and control (IPC) policies and organisational response. Aim: To identify key areas for improvement through rapid investigation of HCA SARS-CoV-2 cases and to implement change. Methods: Cases were identified based on date of first positive SARS-CoV-2 PCR sample in relation to date of hospital admission. Cases were reviewed using a structured gap analysis tool to identify key learning points. These were discussed in weekly multidisciplinary meetings to gain consensus on learning outcomes, level of harm incurred by the patient and required actions. Learning was then promptly fed back to individual teams and the organisation. Findings: Of the 489 SARS-CoV-2 cases admitted between 10th March and 23rd June 2020, 114 suspected HCA cases (23.3%) were reviewed; 58/489 (11.8%) were ultimately deemed to be HCA. Five themes were identified: individual patient vulnerability, communication, IPC implementation, policy issues and organisational response. Adaptations to policies based on these reviews were completed within the course of the initial phase of the pandemic. Conclusion: This approach enabled timely learning and implementation of control measures and policy development.

Admission COVID-19 clinical risk assessment for guiding patient placement and diagnostic testing strategy.

INTRODUCTION: Without universal access to point-of-care SARS-CoV-2 testing, many hospitals rely on clinical judgement alone for identifying cases of COVID-19 early. METHODS: Cambridge University Hospitals NHS Foundation Trust introduced a 'traffic light' clinical judgement aid to the COVID-19 admissions unit in mid-March 2020. Ability to accurately predict COVID-19 was audited retrospectively across different stages of the epidemic. RESULTS: One SARS-CoV-2 PCR positive patient (1/41, 2%) was misallocated to a 'green' (non-COVID-19) area during the first period of observation, and no patients (0/32, 0%) were mislabelled 'green' during the second period. 33 of 62 (53%) labelled 'red' (high risk) tested SARS-CoV-2 PCR positive during the first period, while 5 of 22 (23%) 'red' patients were PCR positive in the second. CONCLUSION: COVID-19 clinical risk stratification on initial assessment effectively identifies non-COVID-19 patients. However, diagnosing COVID-19 is challenging and risk of overcalling COVID-19 should be recognised, especially when background prevalence is low.