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1.
medrxiv; 2022.
Preprint in English | medRxiv | ID: ppzbmed-10.1101.2022.03.24.22272915

ABSTRACT

ObjectiveTo determine how the severity of successively dominant SARS-CoV-2 variants changed over the course of the COVID-19 pandemic. DesignRetrospective cohort analysis. SettingCommunity- and hospital-sequenced COVID-19 cases in the NHS Greater Glasgow and Clyde (NHS GG&C) Health Board. ParticipantsAll sequenced non-nosocomial adult COVID-19 cases in NHS GG&C infected with the relevant SARS-CoV-2 lineages during analysis periods. B.1.177/Alpha: 1st November 2020 - 30th January 2021 (n = 1640). Alpha/Delta: 1st April - 30th June 2021 (n = 5552). AY.4.2 Delta/non-AY.4.2 Delta: 1st July - 31st October 2021 (n = 9613). Non-AY.4.2 Delta/Omicron: 1st - 31st December 2021 (n = 3858). Main outcome measuresAdmission to hospital, ICU, or death within 28 days of positive COVID-19 test ResultsFor B.1.177/Alpha, 300 of 807 B.1.177 cases were recorded as hospitalised or worse, compared to 232 of 833 Alpha cases. After adjustment, the cumulative odds ratio was 1.51 (95% CI: 1.08-2.11) for Alpha versus B.1.177. For Alpha/Delta, 113 of 2104 Alpha cases were recorded as hospitalised or worse, compared to 230 of 3448 Delta cases. After adjustment, the cumulative odds ratio was 2.09 (95% CI: 1.42-3.08) for Delta versus Alpha. For non-AY.4.2 Delta/AY.4.2 Delta, 845 of 8644 non-AY.4.2 Delta cases were recorded as hospitalised or worse, compared to 101 of 969 AY.4.2 Delta cases. After adjustment, the cumulative odds ratio was 0.99 (95% CI: 0.76-1.27) for AY.4.2 Delta versus non-AY.4.2 Delta. For non-AY.4.2 Delta/Omicron, 30 of 1164 non-AY.4.2 Delta cases were recorded as hospitalised or worse, compared to 26 of 2694 Omicron cases. After adjustment, the median cumulative odds ratio was 0.49 (95% CI: 0.22-1.06) for Omicron versus non-AY.4.2 Delta. ConclusionsThe direction of change in disease severity between successively emerging SARS-CoV-2 variants of concern was inconsistent. This heterogeneity demonstrates that severity associated with future SARS-CoV-2 variants is unpredictable.

2.
arxiv; 2021.
Preprint in English | PREPRINT-ARXIV | ID: ppzbmed-2110.02005v1

ABSTRACT

Assessing the impact of an intervention using time-series observational data on multiple units and outcomes is a frequent problem in many fields of scientific research. In this paper, we present a novel method to estimate intervention effects in such a setting by generalising existing approaches based on the factor analysis model and developing a Bayesian algorithm for inference. Our method is one of the few that can simultaneously: deal with outcomes of mixed type (continuous, binomial, count); increase efficiency in the estimates of the causal effects by jointly modelling multiple outcomes affected by the intervention; easily provide uncertainty quantification for all causal estimands of interest. We use the proposed approach to evaluate the impact that local tracing partnerships (LTP) had on the effectiveness of England's Test and Trace (TT) programme for COVID-19. Our analyses suggest that, overall, LTPs had a small positive impact on TT. However, there is considerable heterogeneity in the estimates of the causal effects over units and time.

3.
arxiv; 2021.
Preprint in English | PREPRINT-ARXIV | ID: ppzbmed-2104.05560v3

ABSTRACT

Objective: To evaluate the relationship between coronavirus disease 2019 (COVID-19) diagnosis with SARS-CoV-2 variant B.1.1.7 (also known as Variant of Concern 202012/01) and the risk of hospitalisation compared to diagnosis with wildtype SARS-CoV-2 variants. Design: Retrospective cohort, analysed using stratified Cox regression. Setting: Community-based SARS-CoV-2 testing in England, individually linked with hospitalisation data. Participants: 839,278 laboratory-confirmed COVID-19 patients, of whom 36,233 had been hospitalised within 14 days, tested between 23rd November 2020 and 31st January 2021 and analysed at a laboratory with an available TaqPath assay that enables assessment of S-gene target failure (SGTF). SGTF is a proxy test for the B.1.1.7 variant. Patient data were stratified by age, sex, ethnicity, deprivation, region of residence, and date of positive test. Main outcome measures: Hospitalisation between 1 and 14 days after the first positive SARS-CoV-2 test. Results: 27,710 of 592,409 SGTF patients (4.7%) and 8,523 of 246,869 non-SGTF patients (3.5%) had been hospitalised within 1-14 days. The stratum-adjusted hazard ratio (HR) of hospitalisation was 1.52 (95% confidence interval [CI] 1.47 to 1.57) for COVID-19 patients infected with SGTF variants, compared to those infected with non-SGTF variants. The effect was modified by age (P<0.001), with HRs of 0.93-1.21 for SGTF compared to non-SGTF patients below age 20 years, 1.29 in those aged 20-29, and 1.45-1.65 in age groups 30 years or older. Conclusions: The results suggest that the risk of hospitalisation is higher for individuals infected with the B.1.1.7 variant compared to wildtype SARS-CoV-2, likely reflecting a more severe disease. The higher severity may be specific to adults above the age of 30.

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