A comparison of two frameworks for multi-state modelling, applied to outcomes after hospital admissions with COVID-19 (preprint)

We compare two multi-state modelling frameworks that can be used to represent dates of events following hospital admission for people infected during an epidemic. The methods are applied to data from people admitted to hospital with COVID-19, to estimate the probability of admission to ICU, the probability of death in hospital for patients before and after ICU admission, the lengths of stay in hospital, and how all these vary with age and gender. One modelling framework is based on defining transition-specific hazard functions for competing risks. A less commonly used framework defines partially-latent subpopulations who will experience each subsequent event, and uses a mixture model to estimate the probability that an individual will experience each event, and the distribution of the time to the event given that it occurs. We compare the advantages and disadvantages of these two frameworks, in the context of the COVID-19 example. The issues include the interpretation of the model parameters, the computational efficiency of estimating the quantities of interest, implementation in software and assessing goodness of fit. In the example, we find that some groups appear to be at very low risk of some events, in particular ICU admission, and these are best represented by using "cure-rate" models to define transition-specific hazards. We provide general-purpose software to implement all the models we describe in the "flexsurv" R package, which allows arbitrarily-flexible distributions to be used to represent the cause-specific hazards or times to events.

Trends in COVID-19 hospital outcomes in England before and after vaccine introduction, a cohort study (preprint)

Widespread vaccination campaigns have changed the landscape for COVID-19, vastly altering symptoms and reducing morbidity and mortality. We estimate trends in mortality by month of admission and vaccination status among those hospitalised with COVID-19 in England between March 2020 to September 2021, controlling for demographic factors and hospital load. Among 259,727 hospitalised COVID-19 cases, 51,948 (20.0%) experienced mortality in hospital. Hospitalised fatality risk ranged from 40.3% (95% confidence interval 39.4-41.3%) in March 2020 to 8.1% (7.2-9.0%) in June 2021. Older individuals and those with multiple co-morbidities were more likely to die or else experienced longer stays prior to discharge. Compared to unvaccinated people, the hazard of hospitalised mortality was 0.71 (0.67-0.77) with a first vaccine dose, and 0.56 (0.52-0.61) with a second vaccine dose. Compared to hospital load at 0-20% of the busiest week, the hazard of hospitalised mortality during periods of peak load (90-100%), was 1.23 (1.12-1.34). The prognosis for people hospitalised with COVID-19 in England has varied substantially throughout the pandemic and according to case-mix, vaccination, and hospital load. Our estimates provide an indication for demands on hospital resources, and the relationship between hospital burden and outcomes.

Effectiveness and durability of protection against future SARS-CoV-2 infection conferred by COVID-19 vaccination and previous infection; findings from the UK SIREN prospective cohort study of healthcare workers March 2020 to September 2021 (preprint)

BackgroundUnderstanding the duration and effectiveness of infection and vaccine-acquired SARS-CoV-2 immunity is essential to inform pandemic policy interventions, including the timing of vaccine-boosters. We investigated this in our large prospective cohort of UK healthcare workers undergoing routine asymptomatic PCR testing. MethodsWe assessed vaccine effectiveness (VE) (up to 10-months after first dose) and infection-acquired immunity by comparing time to PCR-confirmed infection in vaccinated and unvaccinated individuals using a Cox regression-model, adjusted by prior SARS-CoV-2 infection status, vaccine-manufacturer/dosing-interval, demographics and workplace exposures. ResultsOf 35,768 participants, 27% (n=9,488) had a prior SARS-CoV-2 infection. Vaccine coverage was high: 97% had two-doses (79% BNT162b2 long-interval, 8% BNT162b2 short-interval, 8% ChAdOx1). There were 2,747 primary infections and 210 reinfections between 07/12/2020 and 21/09/2021. Adjusted VE (aVE) decreased from 81% (95% CI 68%-89%) 14-73 days after dose-2 to 46% (95% CI 22%-63%) >6-months; with no significant difference for short-interval BNT162b2 but significantly lower aVE (50% (95% CI 18%-70%) 14-73 days after dose-2 from ChAdOx1. Protection from infection-acquired immunity showed evidence of waning in unvaccinated follow-up but remained consistently over 90% in those who received two doses of vaccine, even in those infected over 15-months ago. ConclusionTwo doses of BNT162b2 vaccination induce high short-term protection to SARS-CoV-2 infection, which wanes significantly after six months. Infection-acquired immunity boosted with vaccination remains high over a year after infection. Boosters will be essential to maintain protection in vaccinees who have not had primary infection to reduce infection and transmission in this population. Trial registration numberISRCTN11041050

Self assessment overestimates historical COVID-19 disease relative to sensitive serological assays: cross sectional study in UK key workers (preprint)

Objective To measure the association between self-reported signs and symptoms and SARS-CoV-2 seropositivity. Design Cross sectional study of three key worker groups. Setting Six acute NHS hospitals and two Police and Fire and Rescue sites in England. Participants Individuals were recruited from three streams: (A) Police and Fire and Rescue services (n=1147), (B) healthcare workers (n=1546) and (C) healthcare workers with previously positive virus detection (n=154). Main outcome measures Detection of anti-SARS-CoV-2 antibodies in plasma. Results 943 of the 2847 participants (33%) reported belief they had had COVID-19, having experienced compatible symptoms (including 152 from Stream C). Among individuals reporting COVID-19 compatible symptoms, 466 (49%) were seronegative on both Nucleoprotein (Roche) and Spike-protein (EUROIMMUN) antibody assays. However, among the 268 individuals with prior positive SARS-CoV-2 tests, of whom 96% reported symptoms with onset a median of 63 days (IQR 52 to 75 days) prior to venesection, Roche and EUROIMMUN assays had 96.6% (95% CI 93.7% to 98.2%) and 93.3% (95% CI 89.6% to 95.7%) sensitivity respectively. Symptomatic but seronegative individuals had significantly earlier symptom onset dates than the symptomatic seropositive individuals, shorter illness duration and a much lower anosmia reporting frequency. Conclusions Self-reported belief of COVID-19 was common among our frontline worker cohort. About half of these individuals were seronegative, despite a high sensitivity of serology in this cohort, at least in individuals with previous positive PCR results. This is compatible with non-COVID-19 respiratory disease during the COVID-19 outbreak having been commonly mistaken for COVID-19 within the key worker cohort studied.