Background Accumulating evidence indicates that COVID-19 causes adverse outcomes in ethnic minority groups. However, little is known about the impact of ethnicity and household size on acquiring infection with SARS-CoV-2. Methods We undertook a retrospective cohort study, in Leicester (UK), of all individuals assessed for COVID-19 with polymerase chain reaction (PCR) testing at University Hospitals of Leicester NHS Trust between 1st March and 28th April 2020. We used logistic regression to identify sociodemographic, clinical and temporal factors associated with SARS-CoV-2 PCR positivity before/after lockdown. Findings 971/4051 (24.0%) patients with suspected COVID-19 were found to be PCR positive for SARS-CoV-2. PCR positivity was more common amongst individuals from ethnic minortiy backgrounds than their White counterparts (White 20.0%, South Asian 37.5%, Black 36.1%, Other 32.2%; p <0.001 for all ethnic minority groups vs White). After adjustment, compared to White ethnicity, South Asian (aOR 2.44 95%CI 2.01, 2.97), Black (aOR 2.56 95%CI 1.71, 3.84) and Other (aOR 2.53 95%CI 1.74, 3.70) ethnicities were more likely to test positive, as were those with a larger estimated household size (aOR 1.06 95%CI 1.02, 1.11). We saw increasing proportions of positive tests in the three weeks post-lockdown amongst the ethnic minority , but not the White, cohort. Estimated household size was associated with PCR positivity after, but not before, lockdown (aOR 1.10 95%CI 1.03, 1.16). Interpretation In individuals presenting with suspected COVID-19, those from ethnic minority communities and larger households had an increased likelihood of SARS-CoV-2 PCR positivity. Pandemic control measures may have more rapid impact on slowing viral transmission amongst those of White ethnicity compared to ethnic minority groups, Research is urgently required to understand the mechanisms underlying these disparities and whether public health interventions have differential effects on individuals from ethnic minority groups. Funding

Cerebral autoregulation (CA) refers to the control of cerebral tissue blood flow (CBF) in response to changes in perfusion pressure. Due to the challenges of measuring intracranial pressure, CA is often described as the relationship between mean arterial pressure (MAP) and CBF. Dynamic CA (dCA) can be assessed using multiple techniques, with transfer function analysis (TFA) being the most common. A 2016 white paper by members of an international Cerebrovascular Research Network (CARNet) that is focused on CA strove to improve TFA standardization by way of introducing data acquisition, analysis, and reporting guidelines. Since then, additional evidence has allowed for the improvement and refinement of the original recommendations, as well as for the inclusion of new guidelines to reflect recent advances in the field. This second edition of the white paper contains more robust, evidence-based recommendations, which have been expanded to address current streams of inquiry, including optimizing MAP variability, acquiring CBF estimates from alternative methods, estimating alternative dCA metrics, and incorporating dCA quantification into clinical trials. Implementation of these new and revised recommendations is important to improve the reliability and reproducibility of dCA studies, and to facilitate inter-institutional collaboration and the comparison of results between studies.

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