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.