Population Interventions Unit, Melbourne School of Population and Global Health, University of Melbourne, 207 Bouverie Street, Carlton, Victoria 3053, Australia.
Population Interventions Unit, Melbourne School of Population and Global Health, University of Melbourne, 207 Bouverie Street, Carlton, Victoria 3053, Australia.
Vaccine. 2022 Jun 21;40(28):3821-3824. doi: 10.1016/j.vaccine.2022.05.039. Epub 2022 May 20.
Immunity to SARS-CoV-2 following vaccination wanes over time in a non-linear fashion, making modelling of likely population impacts of COVID-19 policy options challenging. We observed that it was possible to mathematize non-linear waning of vaccine effectiveness (VE) on the percentage scale as linear waning on the log-odds scale, and developed a random effects logistic regression equation based on UK Health Security Agency data to model VE against Omicron following two and three doses of a COVID-19 vaccine. VE on the odds scale reduced by 47% per month for symptomatic infection after two vaccine doses, lessening to 35% per month for hospitalisation. Waning on the odds scale after triple dose vaccines was 35% per month for symptomatic disease and 19% for hospitalisation. This log-odds system for estimating waning and boosting of COVID-19 VE provides a simple solution that may be used to parametrize SARS-CoV-2 immunity over time parsimoniously in epidemiological models.
接种疫苗后，针对 SARS-CoV-2 的免疫力会随时间推移呈非线性下降，这使得对 COVID-19 政策选择可能对人群产生的影响进行建模具有挑战性。我们发现，针对疫苗效力 (VE) 的非线性下降，可以在对数几率标度上线性化，并且基于英国卫生安全局的数据，我们开发了一个随机效应逻辑回归方程，以针对 COVID-19 疫苗接种两剂和三剂后针对奥密克戎的 VE 进行建模。两剂疫苗接种后，针对有症状感染的 VE 在几率标度上每月下降 47%，下降到住院治疗时的每月 35%。三剂疫苗接种后，针对有症状疾病的 VE 在几率标度上每月下降 35%，针对住院治疗的 VE 每月下降 19%。这种用于估计 COVID-19 VE 衰减和增强的对数几率系统提供了一种简单的解决方案，可以在流行病学模型中节省地对 SARS-CoV-2 免疫力随时间推移进行参数化。
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