Our study is now published in Epidemics!

🔗 https://doi.org/10.1016/j.epidem.2023.100726

We proposed a methodological framework for providing interim estimates of waning vaccine effectiveness in the presence of multi-variant circulation from population-level data.

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@_akiraendo
Shouto Yonekura

Summary

With the emergence of more transmissible and/or immune-escape SARS-CoV-2 variants, monitoring the duration of vaccine-induced immunity against each variant became further important.

Standard epidemiological studies for estimating waning VE against infection, e.g. test-negative case control design, require extensive time and resources to construct individual-level datasets along with variant classification for each case.

While such robust (if time-taking) studies are crucial, it is also worth getting a sense of waning VE as a tentative figure before fine-scale studies come out.
As such, we proposed a Bayesian framework for estimating waning VE from routinely collected population-level data.

Our model takes case numbers by vaccine status, vaccination rates and time-varying relative frequency of variants as inputs, all often routinely collected and publicly available, and estimates the waning curve of VE over time against each variant.

We applied our framework to simulated outbreak data and the COVID-19 epidemic in Japan. Our framework yielded estimates that are overall consistent with the waning VE curves that would be obtained from individual-level records(such as test-negative study data).

To wrap up, our framework offers crude but timely estimates of VE, which would serve as a wake-up call for outbreak control until robust studies such as test-negative design are made available.

Great to see this out, which we have long awaited!

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