Optimising health and economic impacts of COVID-19 vaccine prioritisation strategies in the WHO European Region: a mathematical modelling study.
Optimising health and economic impacts of COVID-19 vaccine prioritisation strategies in the WHO European Region: a mathematical modelling study.
复制标题
DOI：
10.1016/j.lanepe.2021.100267
复制
发表时间：
2022-01
期刊：
影响因子：
--
通讯作者：
Jit M
中科院分区：
文献类型：
--
作者：
Liu Y;Sandmann FG;Barnard RC;Pearson CAB;Pastore R;Pebody R;Flasche S;Jit M
世界卫生组织（世卫组织）欧洲区的国家在COVID-19疫苗供应条件方面存在差异。我们评估了在这个人口和社会经济多样化的地区，不同年龄的疫苗优先战略对健康和经济的影响。我们对2020年每日报告的COVID-19死亡率拟合了特定年龄的房室模型，以在疫苗推出前提供免疫水平。模型反映了各国在人口结构、接触模式、流行病史、预期寿命和人均GDP方面的差异。我们检查了优先考虑的四种策略：所有成年人（V+），年轻人（20-59岁）其次是老年人（60+）（V20），老年人其次是年轻人（V60），老年人（75+）（V75）其次是逐渐年轻的年龄组。我们探索了四种推广方案（R1-4）-最慢的方案（R1）到2022年12月达到30%的覆盖率，最快的方案（R4）到2021年12月达到80%。总结了2021- 2022年的五个决策指标：死亡率，发病率，合并症调整预期寿命的损失，合并症和质量调整寿命年以及人力资本。对六种疫苗进行了测试-性能最高的疫苗对感染和疾病的有效性为95%，对疾病的有效性最低为50%，对感染的有效性为0%。在20个决策指标和推出方案组合中，只有一个组合的最佳战略适用于所有国家;在19个组合中，V60比V75更可取或相似。在38个有拟合模型的国家中，11-37个国家根据决策指标或推出设想方案制定了不同的最佳战略。当推广缓慢和疫苗概况不太有利时，优先考虑老年人有更大的好处。最佳的基于年龄的疫苗优先策略对国家特征、决策指标和推广速度敏感。涉及更多基于年龄阶段的优先战略（V75）不一定比针对广泛年龄组（V60）更好的健康和经济结果。预计疫苗推广缓慢的国家可能特别受益于优先考虑老年人。世界卫生组织、比尔及梅林达·盖茨基金会、医学研究理事会（联合王国）、国家卫生研究所（联合王国）、欧洲联盟委员会、外交、联邦和发展事务部（联合王国）、惠康信托基金
Countries in the World Health Organization (WHO) European Region differ in terms of the COVID-19 vaccine supply conditions. We evaluated the health and economic impact of different age-based vaccine prioritisation strategies across this demographically and socio-economically diverse region. We fitted age-specific compartmental models to the reported daily COVID-19 mortality in 2020 to inform the immunity level before vaccine roll-out. Models capture country-specific differences in population structures, contact patterns, epidemic history, life expectancy, and GDP per capita. We examined four strategies that prioritise: all adults (V+), younger (20-59 year-olds) followed by older adults (60+) (V20), older followed by younger adults (V60), and the oldest adults (75+) (V75) followed by incrementally younger age groups. We explored four roll-out scenarios (R1-4) — the slowest scenario (R1) reached 30% coverage by December 2022 and the fastest (R4) 80% by December 2021. Five decision-making metrics were summarised over 2021-22: mortality, morbidity, and losses in comorbidity-adjusted life expectancy, comorbidity- and quality-adjusted life years, and human capital. Six vaccine profiles were tested — the highest performing vaccine has 95% efficacy against both infection and disease, and the lowest 50% against diseases and 0% against infection. Of the 20 decision-making metrics and roll-out scenario combinations, the same optimal strategy applied to all countries in only one combination; V60 was more or similarly desirable than V75 in 19 combinations. Of the 38 countries with fitted models, 11-37 countries had variable optimal strategies by decision-making metrics or roll-out scenarios. There are greater benefits in prioritising older adults when roll-out is slow and when vaccine profiles are less favourable. The optimal age-based vaccine prioritisation strategies were sensitive to country characteristics, decision-making metrics, and roll-out speeds. A prioritisation strategy involving more age-based stages (V75) does not necessarily lead to better health and economic outcomes than targeting broad age groups (V60). Countries expecting a slow vaccine roll-out may particularly benefit from prioritising older adults. World Health Organization, Bill and Melinda Gates Foundation, the Medical Research Council (United Kingdom), the National Institute of Health Research (United Kingdom), the European Commission, the Foreign, Commonwealth and Development Office (United Kingdom), Wellcome Trust
登录
查看更多内容
影响因子：
4.5
作者：
Ara, Roberta;Brazier, John E.
通讯作者：
Brazier, John E.
影响因子：
13.6
作者：
Levin AT;Hanage WP;Owusu-Boaitey N;Cochran KB;Walsh SP;Meyerowitz-Katz G
通讯作者：
Meyerowitz-Katz G
影响因子：
9.7
作者：
Courtemanche, Charles;Garuccio, Joseph;Yelowitz, Aaron
通讯作者：
Yelowitz, Aaron
疫苗对SARS-COV-2：数学建模分析的疫苗对基于年龄的优先级，全球分配和公共卫生影响。
影响因子：
5.5
作者：
Hogan AB;Winskill P;Watson OJ;Walker PGT;Whittaker C;Baguelin M;Brazeau NF;Charles GD;Gaythorpe KAM;Hamlet A;Knock E;Laydon DJ;Lees JA;Løchen A;Verity R;Whittles LK;Muhib F;Hauck K;Ferguson NM;Ghani AC
通讯作者：
Ghani AC
影响因子：
15.1
作者：
Mishra S;Mindermann S;Sharma M;Whittaker C;Mellan TA;Wilton T;Klapsa D;Mate R;Fritzsche M;Zambon M;Ahuja J;Howes A;Miscouridou X;Nason GP;Ratmann O;Semenova E;Leech G;Sandkühler JF;Rogers-Smith C;Vollmer M;Unwin HJT;Gal Y;Chand M;Gandy A;Martin J;Volz E;Ferguson NM;Bhatt S;Brauner JM;Flaxman S;COVID-19 Genomics UK (COG-UK) Consortium
通讯作者：
COVID-19 Genomics UK (COG-UK) Consortium