Estimating waning vaccine effectiveness from population-level surveillance data in multi-variant epidemics

Monitoring time-varying vaccine effectiveness (e.g., due to waning of immunity and the emergence of novel variants) provides crucial information for outbreak control. Existing studies of time-varying vaccine effectiveness have used individual-level data, most importantly dates of vaccination and variant classification, which are often not available in a timely manner or from a wide range of population groups. We present a novel Bayesian framework for estimating the waning of variant-specific vaccine effectiveness in the presence of multi-variant circulation from population-level surveillance data. Applications to simulated outbreak and COVID-19 epidemic in Japan are also presented. Our results show that variant-specific waning vaccine effectiveness estimated from population-level surveillance data could approximately reproduce the estimates from previous test-negative design studies, allowing for rapid, if crude, assessment of the epidemic situation before fine-scale studies are made available.Author summaryThe emergence of immunity-escaping SARS-CoV-2 variants and the waning of vaccine effectiveness have highlighted the need for near-real-time monitoring of variant-specific protection in the population to guide control efforts. However, standard epidemiological studies to this end typically require access to detailed individual-level dataset, which may not be timely available in an ongoing outbreak. A more convenient and less resource-intensive approach using routinely-collected data could complement such studies by providing tentative estimates of waning vaccine effectiveness until the conclusive evidence becomes available. In this paper, we propose a novel Bayesian framework for estimating waning vaccine effectiveness against multiple co-circulating variants that requires only population-level surveillance data. Using simulated outbreak data of multiple variants,we showed that the proposed method can plausibly recover the ground truth from population-level data. We also applied the proposed method to empirical COVID-19 data in Japan, which yielded estimates that are overall in line with those derived from studies using individual-level data.