A meta-analysis of vaccine efficacy from phase III clinical trials of approved vaccines against SARS-CoV-2 and variants.

Background: As we emerge from the COVID-19 pandemic and transition to a post-pandemic era, it is crucial to reflect on our experiences and prepare for future pandemics. Here we evaluate the impact of different methods for calculating the vaccine efficacy of COVID-19 vaccines, which has not been done previously.

Methods: We conducted a meta-analysis of 38 approved COVID-19 vaccines using data from phase III clinical trials between May 4, 2020, and June 10, 2022. We analyze vaccine efficacy against multiple SARS-CoV-2 variants including the original strain, Alpha, Beta, Delta, and Kappa using multiple endpoints. Clinical endpoints are categorized into a tree structure including asymptomatic infection, symptomatic infection, mild to critical illness, and death. We employ re-estimated vaccine efficacies, including relative risk and Poisson regression with robust error variance, for equitable cross-vaccine comparisons.

Results: We re-estimated 63 vaccine efficacies, revealing a 3% to 6% difference in five efficacies compared to the original study. Four efficacies exhibited lower bounds below the critical 50% threshold for the endpoint asymptomatic, symptomatic, moderate, and severe, contrary to the initial reports. However, efficacy consistently surpasses the 50% threshold against symptomatic COVID-19. Overall efficacies range from 34.2% to 100%, 50.3% to 100% against symptomatic, and 66.8% to 100% against severe, and 65% to 95% against variants.

Conclusions: Our systematic classification of vaccine endpoints enables more statistically rigorous meta-analyses across studies. Beyond the quantitative results, our study emphasizes the need to standardize the estimation method for robust assessments of vaccine efficacy. We highlight the incompleteness of the knowledge about different vaccine efficacy in the middle of the pandemic, in particular the need to identify variants during the trials and report on multiple endpoints. We encourage all authors to publicly share their data, fostering additional impartial investigations. This data collection enables comparisons with real-world effectiveness data, enabling future studies of the predictive power of efficacy.