RAPID: Tracking and Deconstructing COVID-19 Vaccine Distribution as an Extreme Logistics Event
RAPID: Tracking and Deconstructing COVID-19 Vaccine Distribution as an Extreme Logistics Event
批准号:
2114778
负责人:
Hani Mahmassani
金额:
$12.5万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2021
资助国家:
美国
项目状态:
已结题
起止时间:
2021-02-01 至 2022-08-31
中文摘要
这项快速反应研究(RAPID)拨款将记录和调查COVID-19疫苗的部署和分发,作为一个大规模复杂的极端物流事件。 鉴于这一行动前所未有的规模、规模和紧迫性及其快速发展的性质,必须记录其发展和部署情况,并为未来极端后勤行动的规划、设计和运作汲取经验教训。 通过疫苗接种控制病毒将使美国和世界各地的经济和社会生活正常化,重新开放重要的地方,区域和国际经济。 鉴于生命、生产力和经济产出的巨大损失,加上教育和心理健康结果不佳,沿着,必须对疫苗部署过程进行评估,为未来的极端后勤行动,包括未来的流行病、健康威胁和应对重大自然和人为灾害,吸取经验教训。该研究将实时记录COVID-19疫苗供应链的状态,包括随时间推移的疫苗接种率,为持续部署过程的后期提供临时指导,并为未来极端物流部署(包括其他与健康相关的危机和灾难应对情况)的稳健设计和弹性运营提取经验教训和原则。 研究结果将有助于解决以下问题:(1)美国物流系统和整个生物制药供应链在所需规模和所需紧急时间范围内提供疫苗的能力,(2)达到目标疫苗接种水平所需的时间范围,(3)疫苗供应链和分销过程中的主要漏洞,(4)整个供应链的复原力,即各种来源造成的中断,(5)物流过程的公平性,以达到传统上得不到充分服务的人口,以及(6)实时信息在增强极端物流流程的稳健性和弹性以及建立公众对这些流程的信任方面的价值。由参与分发进程的专家和利益攸关方组成的咨询委员会将进一步为这项工作提供信息。科学意义源于物流过程前所未有的规模、紧迫性和复杂性,其特点是:(a)由来自相当不同领域的多个相互作用的主体做出的决策,(B)许多随机性和破坏潜力的来源,(c)具有级联故障潜力的强相互作用的网络元素,以及(d)该奖项反映了NSF的法定使命,并被认为是值得支持的,使用基金会的知识价值和更广泛的影响审查标准进行评估。
英文摘要
This Rapid Response Research (RAPID) grant will document and investigate the deployment and distribution of the COVID-19 vaccines as a large-scale complex extreme logistics event. Given the unique unprecedented scale, magnitude and urgency of this operation, and its fast-moving nature, it is imperative to document its development and deployment, and extract lessons for the planning, design and operation of future extreme logistical operations. Controlling the virus through vaccination will normalize economic and social life in the US and around the world, reopening vital local, regional, and international economies. Given the huge toll of lost lives, productivity and economic output, along with poor educational and mental health outcomes, it is imperative to take stock of the vaccine deployment process, extracting lessons for future extreme logistical operations including future pandemics, health threats, and responses to major natural and man-made disasters. This study will document in real-time the state of the COVID-19 vaccine supply chain, including vaccination rates over time, provide interim guidance for the latter portions of the continuing deployment process, and extract lessons learned and principles for the robust design and resilient operation of future extreme logistics deployments, including other health-related crises and disaster response situations. The study findings will help address questions about (1) the capacity of the US logistics system and overall biopharma supply chain to deliver vaccine at the desired scale and in the desired urgent time frame, (2) the time frames required to reach target vaccination levels, (3) the main vulnerabilities in the vaccine supply chain and distribution process, (4) resilience of the overall supply chain viz. disruptions due to various sources, (5) equity of the logistical processes in terms of reaching traditionally underserved populations, and (6) the value of real-time information in enhancing the robustness and resilience of extreme logistics processes and building public trust in these processes. This work will be further informed by an advisory board of experts and stakeholders engaged in the distribution process. The scientific significance arises from the unprecedented scale, urgency and complexity of the logistics processes, featuring (a) decisions made by multiple interacting agents from considerably different domains, (b) many sources of stochasticity and disruption potential, (c) strongly interacting network elements with potential for cascading failure, and (d) hierarchical processes featuring strong centralized control at upper levels with highly decentralized loose coupling at lower levels.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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Travel Support for Dynamic Traffic Assignment Conference (DTA 2023); Evanston, Illinois; 10-12 July 2023
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批准号:2330274
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项目类别:Standard Grant
-
资助金额:$2.5万
-
财政年份:2023
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负责人:Hani Mahmassani
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依托单位:
COLLABORATIVE RESEARCH: MODELING HUMAN DRIVING BEHAVIOR AND RESPONSE WITH APPLICATIONS TO INTELLIGENT AGENT-BASED TRAFFIC FLOW SIMULATION
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批准号:0802433
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项目类别:Standard Grant
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资助金额:$24.97万
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财政年份:2007
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负责人:Hani Mahmassani
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依托单位:
COLLABORATIVE RESEARCH: MODELING HUMAN DRIVING BEHAVIOR AND RESPONSE WITH APPLICATIONS TO INTELLIGENT AGENT-BASED TRAFFIC FLOW SIMULATION
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批准号:0527573
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项目类别:Standard Grant
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资助金额:$31.98万
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财政年份:2006
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负责人:Hani Mahmassani
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依托单位:
NSF/USDOT: Collaborative Research: Impact of Real-time Carrier-shipper Interaction on Transportation System Performance
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批准号:0231517
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项目类别:Standard Grant
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资助金额:$15.8万
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财政年份:2003
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负责人:Hani Mahmassani
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依托单位:
Online Transportation Markets: Performance Models and Real-Time Fleet Operational Strategies
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批准号:0085691
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项目类别:Standard Grant
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资助金额:$14.0万
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财政年份:2000
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负责人:Hani Mahmassani
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依托单位:
User Choice Dynamics in Congested Traffic Systems
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批准号:8610459
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项目类别:Standard Grant
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资助金额:$6.8万
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财政年份:1986
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负责人:Hani Mahmassani
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依托单位:
Dynamics of Usage Decisions in Transportation Systems
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批准号:8400306
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项目类别:Standard Grant
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资助金额:$14.7万
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财政年份:1984
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负责人:Hani Mahmassani
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依托单位:
国内基金
海外基金
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