Kodera Sachiko, Takada Akito, Rashed Essam A, Hirata Akimasa
Department of Electrical and Mechanical Engineering, Nagoya Institute of Technology, Nagoya 466-8555, Japan.
Center of Biomedical Physics and Information Technology, Nagoya Institute of Technology, Nagoya 466-8555, Japan.
Vaccines (Basel). 2023 Mar 13;11(3):633. doi: 10.3390/vaccines11030633.
Since the emergence of COVID-19, the forecasting of new daily positive cases and deaths has been one of the essential elements in policy setting and medical resource management worldwide. An essential factor in forecasting is the modeling of susceptible populations and vaccination effectiveness (VE) at the population level. Owing to the widespread viral transmission and wide vaccination campaign coverage, it becomes challenging to model the VE in an efficient and realistic manner, while also including hybrid immunity which is acquired through full vaccination combined with infection. Here, the VE model of hybrid immunity was developed based on an in vitro study and publicly available data. Computational replication of daily positive cases demonstrates a high consistency between the replicated and observed values when considering the effect of hybrid immunity. The estimated positive cases were relatively larger than the observed value without considering hybrid immunity. Replication of the daily positive cases and its comparison would provide useful information of immunity at the population level and thus serve as useful guidance for nationwide policy setting and vaccination strategies.
自新冠病毒病出现以来，每日新增确诊病例和死亡人数的预测一直是全球政策制定和医疗资源管理的关键要素之一。预测的一个重要因素是在人群层面建立易感人群模型和疫苗有效性（VE）模型。由于病毒传播广泛且疫苗接种运动覆盖范围广，要以高效且现实的方式对疫苗有效性进行建模变得具有挑战性，同时还需纳入通过全程接种疫苗并结合感染获得的混合免疫。在此，基于一项体外研究和公开数据建立了混合免疫的疫苗有效性模型。在考虑混合免疫的影响时，每日新增确诊病例的计算复制显示出复制值与观测值之间具有高度一致性。在不考虑混合免疫的情况下，估计的确诊病例相对大于观测值。每日新增确诊病例的复制及其比较将提供人群层面免疫力的有用信息，从而为全国性政策制定和疫苗接种策略提供有用指导。
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