Social determinants of ethnic disparities in SARS-CoV-2 infection: UK Biobank SARS-CoV-2 Serology Study.

BACKGROUND: The social determinants of ethnic disparities in risk of SARS-CoV-2 infection during the first wave of the pandemic in the UK remain unclear. METHODS: In May 2020, a total of 20 195 adults were recruited from the general population into the UK Biobank SARS-CoV-2 Serology Study. Between mid-May and mid-November 2020, participants provided monthly blood samples. At the end of the study, participants completed a questionnaire on social factors during different periods of the pandemic. Logistic regression yielded ORs for the association between ethnicity and SARS-CoV-2 immunoglobulin G antibodies (indicating prior infection) using blood samples collected in July 2020, immediately after the first wave. RESULTS: After exclusions, 14 571 participants (mean age 56; 58% women) returned a blood sample in July, of whom 997 (7%) had SARS-CoV-2 antibodies. Seropositivity was strongly related to ethnicity: compared with those of White ethnicity, ORs (adjusted for age and sex) for Black, South Asian, Chinese, Mixed and Other ethnic groups were 2.66 (95% CI 1.94-3.60), 1.66 (1.15-2.34), 0.99 (0.42-1.99), 1.42 (1.03-1.91) and 1.79 (1.27-2.47), respectively. Additional adjustment for social factors reduced the overall likelihood ratio statistics for ethnicity by two-thirds (67%; mostly from occupational factors and UK region of residence); more precise measurement of social factors may have further reduced the association. CONCLUSIONS: This study identifies social factors that are likely to account for much of the ethnic disparities in SARS-CoV-2 infection during the first wave in the UK, and highlights the particular relevance of occupation and residential region in the pathway between ethnicity and SARS-CoV-2 infection.

Optimising outpatient efficiency - development of an innovative 'Did Not Attend' management approach.

OBJECTIVE: To examine non-attendance [or Did Not Attend (DNA)] rates in a community mental health follow-up outpatient clinic and evaluate a pragmatic initiative to reduce non-attendance. METHODS: Clinical audit of attendance across two community psychiatry outpatient clinics was used to establish DNA rates at baseline. Both clinics sought to reduce the DNA rate and were made aware of the outcome of the first cycle of audit. Clinic A (intervention clinic) introduced an innovative new management approach aimed at reducing DNAs, whilst Clinic B (control clinic) introduced no further systematic measures. The clinics were then re-audited to establish the impact of the changes. RESULTS: We found that the introduction of the new management approach in Clinic A was associated with reduced numbers of service users failing to attend for a clinic appointment (n = 1134, relative risk 0.59, 95% Confidence Interval (C.I.) 0.44-0.77, NNT = 12). No such difference was identified in Clinic B. CONCLUSIONS: Intervention to reduce the DNA rate is realistically achievable with minimal effort and modest additional cost. The actions required of clinicians are practicable, and can have a direct impact without large-scale organisational change.