Optimizing global COVID-19 vaccine allocation: An agent-based computational model of 148 countries.
Optimizing global COVID-19 vaccine allocation: An agent-based computational model of 148 countries.
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DOI：
10.1371/journal.pcbi.1010463
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发表时间：
2022-09
影响因子：
4.3
通讯作者：
中科院分区：
文献类型：
--
作者：
基于公平和有效的原则，世界卫生组织和Covax将疫苗分配作为一个数学优化问题来制定。本研究旨在利用基于智能体的模拟技术来解决该优化问题。我们建立了开源的基于代理的模型，利用先进的计算服务，在148个国家和地区的1.98亿人口中模拟了具有人口统计学代表性的样本中的病毒传播。所有继续其目前疫苗进展的国家被定义为基准情景。比较情景包括实现最低疫苗接种率和根据大流行水平分配疫苗。这些模拟使用了148个国家从2020年1月到2021年6月的大流行数据。根据基线设想，在三个月的预测期内，世界将增加2436万例和468945例死亡。为所有国家至少10%、20%和26%的人口接种疫苗，每天分别需要额外接种1.12%、3.31%和500万剂疫苗。达到这些基准后，新病例分别减少了0.56、2.74和332万。如果按照目前的全球分布分配，增加500万剂疫苗只能避免145万例新病例。如果根据每个国家的预测病例分配这500万种疫苗，避免的病例将增加6倍以上，达到920万例。在避免的死亡中，分配方法之间也有类似的差异。可以优化新冠肺炎疫苗的全球布局，在公平和有效性方面取得更好的结果。替代疫苗分配方法可能会比目前的全球分配避免数倍的病例和死亡。有了额外疫苗的合理要求，Covax可以采用替代分配策略，减少跨国不平等并拯救更多生命。自2020年初以来，全球新冠肺炎疫情给人们带来了巨大的健康和经济负担。虽然非药物干预措施(例如，部分或完全封锁；社会距离)成功地缓解了病毒在许多国家的传播，但疫苗接种是帮助人们恢复正常生活的关键。已经开发出高效疫苗，但数量不足以很快为世界上每一个人接种疫苗。因此，全球疫苗分配战略在影响、覆盖和公平方面产生了深远的后果。Covax将全球疫苗分配问题描述为一个复杂的优化问题。为了解决优化问题，我们开发了基于代理的模型来试验各种分配策略。使用先进的计算服务，我们的模型能够捕捉个人和国家的异质性，再现观察到的大流行轨迹，并在假设的分配情景下进行预测。我们的结果表明，与目前压倒性地有利于高收入国家的战略相比，替代分配战略具有相当大的优势。我们的开源模拟工具是公开可用的。结果可以半自动的方式更新。经过微小的修改，我们的模拟工具也可以用来帮助决策者探索其他疫苗分配策略和缓解措施。
Based on the principles of equity and effectiveness, the World Health Organization and COVAX formulate vaccine allocation as a mathematical optimization problem. This study aims to solve the optimization problem using agent-based simulations. We built open-sourced agent-based models to simulate virus transition among a demographically representative sample of 198 million people in 148 countries using advanced computational services. All countries continuing their current vaccine progress is defined as the baseline scenario. Comparison scenarios include achieving minimum vaccination rates and allocating vaccines based on pandemic levels. The simulations are fitted using the pandemic data from 148 countries from January 2020 to June 2021. Under the baseline scenario, the world will add 24.36 million cases and 468,945 deaths during the projection period of three months. Inoculating at least 10%, 20%, and 26% of populations in all countries requires 1.12, 3.31, and 5.00 million additional vaccine doses every day, respectively. Achieving these benchmarks reduces new cases by 0.56, 2.74, and 3.32 million, respectively. If allocated by the current global distribution, 5.00 million additional vaccine doses will only avert 1.45 million new cases. If those 5.00 million vaccines are allocated based on projected cases in each country, the averted cases will increase more than six-fold to 9.20 million. Similar differences between allocation methods are observed in averted deaths. The global distribution of COVID-19 vaccines can be optimized to achieve better outcomes in terms of both equity and effectiveness. Alternative vaccine allocation methods may avert several times more cases and deaths than the current global distribution. With reasonable requirements on additional vaccines, COVAX could adopt alternative allocation strategies that reduce cross-country inequity and save more lives. Since early 2020, the global COVID-19 pandemic has imposed enormous health and economic burden. While non-pharmaceutical interventions (e.g., partial or full lockdown; social distancing) have successfully mitigated the virus spreading in many countries, vaccination is key to helping people return to their normal lives. Highly effective vaccines have been developed, but the quantity will not be enough to vaccinate every people in the world soon. As a result, global vaccine allocation strategies lead to profound consequences in terms of impacts, coverage, and equity. COVAX formulated global vaccine allocation as a complex optimization problem. To solve the optimization problem, we developed agent-based models to experiment with various allocation strategies. Using advanced computational services, our models are able to capture individual and national heterogeneity, reproduce observed pandemic trajectories, and conduct forecasts under hypothetical allocation scenarios. Our results show the considerable advantage of alternative allocation strategies over current strategy that overwhelmingly favors high-income countries. Our open-source simulation tool is publicly available. The results can be updated in a semi-automatic manner. Upon minor modifications, our simulation tool can also be used to assist policymakers in exploring other vaccine allocation strategies and mitigation measures.
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影响因子：
34.3
作者：
New, Jin Rou;Cahill, Niamh;Alkema, Leontine
通讯作者：
Alkema, Leontine
影响因子：
0.9
作者：
Lim, Hyeong-Seok
通讯作者：
Lim, Hyeong-Seok
DOI：
10.1056/nejmoa2035389
发表时间：
2021-02-04
期刊：
The New England journal of medicine
影响因子：
--
作者：
Baden LR;El Sahly HM;Essink B;Kotloff K;Frey S;Novak R;Diemert D;Spector SA;Rouphael N;Creech CB;McGettigan J;Khetan S;Segall N;Solis J;Brosz A;Fierro C;Schwartz H;Neuzil K;Corey L;Gilbert P;Janes H;Follmann D;Marovich M;Mascola J;Polakowski L;Ledgerwood J;Graham BS;Bennett H;Pajon R;Knightly C;Leav B;Deng W;Zhou H;Han S;Ivarsson M;Miller J;Zaks T;COVE Study Group
通讯作者：
COVE Study Group
DOI：
10.1056/nejmoa2101544
发表时间：
2021-06-10
期刊：
The New England journal of medicine
影响因子：
--
作者：
Sadoff J;Gray G;Vandebosch A;Cárdenas V;Shukarev G;Grinsztejn B;Goepfert PA;Truyers C;Fennema H;Spiessens B;Offergeld K;Scheper G;Taylor KL;Robb ML;Treanor J;Barouch DH;Stoddard J;Ryser MF;Marovich MA;Neuzil KM;Corey L;Cauwenberghs N;Tanner T;Hardt K;Ruiz-Guiñazú J;Le Gars M;Schuitemaker H;Van Hoof J;Struyf F;Douoguih M;ENSEMBLE Study Group
通讯作者：
ENSEMBLE Study Group
影响因子：
5.4
作者：
Rahmandad, Hazhir;Sterman, John
通讯作者：
Sterman, John