美国科罗拉多大学Daniel B. Larremore和Kate M. Bubar研究团队合作取得一项新成果。他们按年龄和血清状况的模型排序COVID-19疫苗优先策略。这一研究成果发表在2021年1月21日的《科学》上。

他们使用数学模型比较了五种按年龄分层的优先级排序策略。 优先于20-49岁成年人的高效传播阻断疫苗可将累积发病率降到最低，但在大多数情况下，当优先考虑60岁以上成年人时，死亡率和减寿可以降至最低。

使用个体水平的血清学检测将剂量重定向至血清阴性个体，可以改善每种剂量的边际影响，同时有可能减少COVID-19影响中现有的不平等现象。尽管最大影响优先级策略在各国、传播率、苗接种速度以及对自然获得的免疫力的估计方面基本一致，但该框架可用于比较不同环境下优先级策略的影响。

据悉，SARS-CoV-2疫苗的初始供应有限，引发了如何对可用剂量进行优先排序的问题。

附：英文原文

Title: Model-informed COVID-19 vaccine prioritization strategies by age and serostatus

Author: Kate M. Bubar, Kyle Reinholt, Stephen M. Kissler, Marc Lipsitch, Sarah Cobey, Yonatan H. Grad, Daniel B. Larremore

Issue&Volume: 2021/01/21

Abstract: Limited initial supply of SARS-CoV-2 vaccine raises the question of how to prioritize available doses. Here, we used a mathematical model to compare five age-stratified prioritization strategies. A highly effective transmission-blocking vaccine prioritized to adults ages 20-49 years minimized cumulative incidence, but mortality and years of life lost were minimized in most scenarios when the vaccine was prioritized to adults over 60 years old. Use of individual-level serological tests to redirect doses to seronegative individuals improved the marginal impact of each dose while potentially reducing existing inequities in COVID-19 impact. While maximum impact prioritization strategies were broadly consistent across countries, transmission rates, vaccination rollout speeds, and estimates of naturally acquired immunity, this framework can be used to compare impacts of prioritization strategies across contexts.

DOI: 10.1126/science.abe6959

Source: https://science.sciencemag.org/content/early/2021/01/21/science.abe6959