Institute of Health Economics, #1200, 10405 Jasper Avenue, Edmonton, AB, T5J 3N4, Canada.
Health Organisation, Policy, and Economics, School of Health Sciences, University of Manchester, Manchester, UK.
Pharmacoeconomics. 2021 Sep;39(9):1059-1073. doi: 10.1007/s40273-021-01037-2. Epub 2021 Jun 17.
The objective of this study was to implement a model-based approach to identify the optimal allocation of a coronavirus disease 2019 (COVID-19) vaccine in the province of Alberta, Canada.
We developed an epidemiologic model to evaluate allocation strategies defined by age and risk target groups, coverage, effectiveness and cost of vaccine. The model simulated hypothetical immunisation scenarios within a dynamic context, capturing concurrent public health strategies and population behavioural changes.
In a scenario with 80% vaccine effectiveness, 40% population coverage and prioritisation of those over the age of 60 years at high risk of poor outcomes, active cases are reduced by 17% and net monetary benefit increased by $263 million dollars, relative to no vaccine. Concurrent implementation of policies such as school closure and senior contact reductions have similar impacts on incremental net monetary benefit ($352 vs $292 million, respectively) when there is no prioritisation given to any age or risk group. When older age groups are given priority, the relative benefit of school closures is much larger ($214 vs $118 million). Results demonstrate that the rank ordering of different prioritisation options varies by prioritisation criteria, vaccine effectiveness and coverage, and concurrently implemented policies.
Our results have three implications: (i) optimal vaccine allocation will depend on the public health policies in place at the time of allocation and the impact of those policies on population behaviour; (ii) outcomes of vaccine allocation policies can be greatly supported with interventions targeting contact reduction in critical sub-populations; and (iii) identification of the optimal strategy depends on which outcomes are prioritised.
本研究旨在实施一种基于模型的方法，以确定在加拿大艾伯塔省 COVID-19 疫苗的最佳分配方案。
我们开发了一种流行病学模型，以评估按年龄和风险目标群体、覆盖范围、疫苗有效性和成本定义的分配策略。该模型在动态环境中模拟假设的免疫接种情景，同时捕捉公共卫生策略和人口行为变化。
在疫苗有效性为 80%、40%人口覆盖和优先考虑高风险人群（60 岁以上）的情况下，与无疫苗相比，活跃病例减少 17%，净货币收益增加 2.63 亿美元。同时实施学校关闭和减少老年人接触等政策，在没有向任何年龄或风险群体优先考虑的情况下，对增量净货币收益的影响相似（分别为 3.52 亿美元和 2.92 亿美元）。当优先考虑老年人群体时，学校关闭的相对收益要大得多（2.14 亿美元与 1.18 亿美元）。结果表明，不同优先选项的排序顺序取决于分配时的公共卫生政策以及这些政策对人口行为的影响。
我们的结果有三个含义：（i）最佳疫苗分配将取决于分配时的公共卫生政策以及这些政策对人口行为的影响；（ii）疫苗分配政策的结果可以通过针对关键亚人群的接触减少干预措施得到极大支持；（iii）最佳策略的确定取决于优先考虑的结果。
