The Changing Impact of Vaccines in the Covid-19 Pandemic: A Modeling Study

Background: Much of the world's population had already been infected with COVID-19 by the time that the Omicron variant emerged at the end of 2021, but the scale of the Omicron wave was larger than any that had come before or since, and left a global imprinting of immunity which changed the COVID landscape. In this study, we explore the changing value of vaccines in a landscape of dynamic immunity and rapidly evolving variants of concern. Method(s): We use Covasim, an established agent-based model of COVID-19 enhanced with detailed intra-host dynamics. First, we simulate a vaccine trial over March 2020 - April 2022 within a population resembling that of South Africa, and estimate how both vaccine efficacy (reduction in the risk of severe disease for vaccinated vs unvaccinated individuals) and efficiency (number of doses needed to avert a death) change as the population experiences waves of wild-type, Beta, Delta, and Omicron infections. Next, we introduce six hypothetical variants starting from February 2022 and evaluate the impact of (a) the existing set of vaccines, and (b) vaccines specifically targeted to the new variants. Result(s): We estimate that within our simulated population, vaccine efficacy against severe disease decreased from 80% to 20% in the wake of the first wave of wild-type COVID-19, then increased back to ~70% over the latter half of 2020 as population immunity waned. This pattern repeated following each subsequent wave of infections, with vaccine efficacy falling to its lowest (10%) in the immediate wake of the Omicron wave in December 2021. The efficiency of vaccination decreases over time at an increasing rate: at peak efficiency, fewer than 100 doses would have been required to avert a single death, but by the end of January 2022, we estimate that nearly 4,000 doses would be required to avert a single death. We find that variant-chasing vaccines will only add value above pre-existing vaccines if we can shorten the window between variant introduction and vaccine deployment to under three weeks, an impossible time-frame without significant NPI use. Conclusion(s): Although the vaccines have proven to be remarkably effective, our work demonstrates that the population immunity acquired over the first two years of the pandemic significantly reduced the impact per dose of doses delivered after this time. Next-generation vaccines to fight future COVID variants and/or other respiratory diseases must be delivered rapidly at scale for vaccine strategies to be maximally effective.

Statistical and agent-based modelling of the transmissibility of different SARS-CoV-2 variants in England and impact of different interventions.

The English SARS-CoV-2 epidemic has been affected by the emergence of new viral variants such as B.1.177, Alpha and Delta, and changing restrictions. We used statistical models and the agent-based model Covasim, in June 2021, to estimate B.1.177 to be 20% more transmissible than the wild type, Alpha to be 50-80% more transmissible than B.1.177 and Delta to be 65-90% more transmissible than Alpha. Using these estimates in Covasim (calibrated 1 September 2020 to 20 June 2021), in June 2021, we found that due to the high transmissibility of Delta, resurgence in infections driven by the Delta variant would not be prevented, but would be strongly reduced by delaying the relaxation of restrictions by one month and with continued vaccination. This article is part of the theme issue 'Technical challenges of modelling real-life epidemics and examples of overcoming these'.

Modelling the impact of reopening schools in the UK in early 2021 in the presence of the alpha variant and with roll-out of vaccination against SARS-CoV-2.

Following the resurgence of the COVID-19 epidemic in the UK in late 2020 and the emergence of the alpha (also known as B117) variant of the SARS-CoV-2 virus, a third national lockdown was imposed from January 4, 2021. Following the decline of COVID-19 cases over the remainder of January 2021, the question of when and how to reopen schools became an increasingly pressing one in early 2021. This study models the impact of a partial national lockdown with social distancing measures enacted in communities and workplaces under different strategies of reopening schools from March 8, 2021 and compares it to the impact of continual full national lockdown remaining until April 19, 2021. We used our previously published agent-based model, Covasim, to model the emergence of the alpha variant over September 1, 2020 to January 31, 2021 in presence of Test, Trace and Isolate (TTI) strategies. We extended the model to incorporate the impacts of the roll-out of a two-dose vaccine against COVID-19, with 200,000 daily vaccine doses prioritised by age starting with people 75 years or older, assuming vaccination offers a 95% reduction in disease acquisition risk and a 30% reduction in transmission risk. We used the model, calibrated until January 25, 2021, to simulate the impact of a full national lockdown (FNL) with schools closed until April 19, 2021 versus four different partial national lockdown (PNL) scenarios with different elements of schooling open: 1) staggered PNL with primary schools and exam-entry years (years 11 and 13) returning on March 8, 2021 and the rest of the schools years on March 15, 2020; 2) full-return PNL with both primary and secondary schools returning on March 8, 2021; 3) primary-only PNL with primary schools and exam critical years (years 11 and 13) going back only on March 8, 2021 with the rest of the secondary schools back on April 19, 2021 and 4) part-rota PNL with both primary and secondary schools returning on March 8, 2021 with primary schools remaining open continuously but secondary schools on a two-weekly rota-system with years alternating between a fortnight of face-to-face and remote learning until April 19, 2021. Across all scenarios, we projected the number of new daily cases, cumulative deaths and effective reproduction number R until April 30, 2021. Our calibration across different scenarios is consistent with alpha variant being around 60% more transmissible than the wild type. We find that strict social distancing measures, i.e. national lockdowns, were essential in containing the spread of the virus and controlling hospitalisations and deaths during January and February 2021. We estimated that a national lockdown over January and February 2021 would reduce the number of cases by early March to levels similar to those seen in October 2020, with R also falling and remaining below 1 over this period. We estimated that infections would start to increase when schools reopened, but found that if other parts of society remain closed, this resurgence would not be sufficient to bring R above 1. Reopening primary schools and exam critical years only or having primary schools open continuously with secondary schools on rotas was estimated to lead to lower increases in cases and R than if all schools opened. Without an increase in vaccination above the levels seen in January and February, we estimate that R could have increased above 1 following the reopening of society, simulated here from April 19, 2021. Our findings suggest that stringent measures were integral in mitigating the increase in cases and bringing R below 1 over January and February 2021. We found that it was plausible that a PNL with schools partially open from March 8, 2021 and the rest of the society remaining closed until April 19, 2021 would keep R below 1, with some increase evident in infections compared to continual FNL until April 19, 2021. Reopening society in mid-April, without an increase in vaccination levels, could push R above 1 and induce a surge in infections, but the effect of vaccination may be able to control this in future depending on the transmission blocking properties of the vaccines.

Drug-induced autoimmune liver disease (DIAILD)

Introduction: Idiosyncratic drug-induced liver injury (DILI) affects an estimated 19 per 100,000 persons yearly and is a major cause of acute liver failure. Drug-induced autoimmune liver disease (DIAILD) is a poorly defined and under-reported liver disorder, and probably an underestimated liver disease. A small number of drug-induced liver injury (DILI) cases exhibit features typical of autoimmune hepatitis (AIH). To differentiate between true AIH triggered by drugs (DI-AIH) and immune mediated DILI still remains a challenge. Case Description/Methods: We present a 71-year-old ICU nurse with past medical history of hyperlipidemia, hypothyroidism and GERD presenting for nausea, epigastric pain, and chills. Of note, 5 days prior to onset of symptoms she received her vaccine for COVID-19. Medications that she takes at home are cimetidine, Protonix, Lipitor, Synthroid, Zofran, Vitamin A, and D supplementation. Review of systems were pertinent for mild itching, nausea, and chills. Physical exam is unremarkable except for low grade fevers, scleral icterus, and jaundice. Labs are significant for T.bili 13.5, AST 1673, ALT 2372, ALP 246, INR 1.59, ANA 1:160, AFP 169, CT abdomen/pelvis with and without contrast was unremarkable except for mild constipation. Liver biopsy was obtained that revealed submassive hepatic multilobular necrosis with confluent lytic necrosis and cholestasis involving 60-70% of the cores. Portal triads showed surrounding lymphocytic infiltrate without bile duct involvement and active interface hepatitis. active interface hepatitis, . Per pathology report the histological findings were nonspecific and a diagnosis of drug toxicity is the most compatible with given history. She was started on prednisone 40 mg daily and her liver enzymes started to improve. Discussion: In our patient we attributed the acute liver injury secondary to cimetidine from immune mediated DILI. Initially we speculated that covid 19 vaccine could have attributed to her acute hepatitis. However, at the time there were no other cases reported of Covid 19 related acute liver injury;and it could have coincidentally occurred at the same time. It will be interesting to see in the future if Covid 19 vaccine presents similar to this case. Although it is a clinical challenge to differentiate AIH and DI-AIH;it is important to keep both conditions in your differential.

Modelling the potential impact of mask use in schools and society on COVID-19 control in the UK.

As the UK reopened after the first wave of the COVID-19 epidemic, crucial questions emerged around the role for ongoing interventions, including test-trace-isolate (TTI) strategies and mandatory masks. Here we assess the importance of masks in secondary schools by evaluating their impact over September 1-October 23, 2020. We show that, assuming TTI levels from August 2020 and no fundamental changes in the virus's transmissibility, adoption of masks in secondary schools would have reduced the predicted size of a second wave, but preventing it would have required 68% or 46% of those with symptoms to seek testing (assuming masks' effective coverage 15% or 30% respectively). With masks in community settings but not secondary schools, the required testing rates increase to 76% and 57%.