RAPID: Collection and Archiving of Vital Data on COVID-19 Vaccine Distribution
RAPID:收集和归档有关 COVID-19 疫苗分发的重要数据
基本信息
- 批准号:2124825
- 负责人:
- 金额:$ 10万
- 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
- 起止时间:2021-06-01 至 2023-05-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Vaccines that are effective at protecting against COVID-19 were first approved for emergency use in the United States in December, 2020. Since that time, as vaccine supply has steadily increased, vaccines have been distributed to states in phases through a variety of channels, including hospitals, pharmacies, nursing homes, public health departments, and mass vaccination sites in an effort to vaccinate as many citizens as possible to reduce morbidity and mortality. Distributing and administering a vaccine on a large scale over a short time period, particularly under extraordinary cold storage requirements, is a challenging and complex logistical problem. This Rapid Response Research (RAPID) grant supports the collection of time-sensitive data on COVID-19 vaccine distribution and administration from the Centers for Disease Control and Prevention (CDC) and a select number of state public health departments. The collection and archiving of time-sensitive data on the vaccination effort in the US will assist researchers in studying the distribution and enable a more efficient response to future pandemics or natural or man-made disasters. This project will collect data on COVID-19 vaccine allocation, distribution and shipment, administration, and inventory to quantify vaccination performance measures such as lead-times, equity with respect to gender or race/ethnicity, and vaccine spoilage. In addition, the project will collect data on policies and decisions made by states that relate to vaccine distribution/administration including the date and type of eligibility expansion, distribution network, the information system used for managing vaccine distribution, number of provider sites in use at select points in time, existence of race/ethnicity elements in the data tracking, and use of state-wide call center or waiting list. All collected data will be de-identified, stored, and managed in a centralized system eventually to make available (as allowable per privacy rules) to researchers. The project will develop an online vaccination portal, whose main goal is to provide a high-level analysis of the collected data, graphics, and data downloading capabilities.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.
有效预防COVID-19的疫苗于2020年12月首次在美国被批准用于紧急使用。从那时起,随着疫苗供应的稳步增加,疫苗通过各种渠道分阶段分发到各州,包括医院、药房、养老院、公共卫生部门和大规模疫苗接种点,努力为尽可能多的公民接种疫苗,以降低发病率和死亡率。在短时间内大规模分发和管理疫苗,特别是在特别需要冷藏的情况下,是一个具有挑战性和复杂的后勤问题。这项快速反应研究(Rapid)赠款支持从疾病控制和预防中心(CDC)和一些选定的州公共卫生部门收集有关COVID-19疫苗分发和管理的时间敏感数据。收集和存档有关美国疫苗接种工作的时间敏感数据将有助于研究人员研究分布情况,并能够更有效地应对未来的大流行或自然或人为灾害。该项目将收集有关COVID-19疫苗分配、分发和运输、管理和库存的数据,以量化疫苗接种绩效指标,如交付时间、性别或种族/民族方面的公平性以及疫苗变质。此外,该项目将收集各州与疫苗分发/管理有关的政策和决定的数据,包括资格扩展的日期和类型、分发网络、用于管理疫苗分发的信息系统、在选定时间点使用的提供者站点数量、数据跟踪中是否存在种族/族裔因素以及使用全州呼叫中心或等候名单。所有收集到的数据将被去识别、存储和管理在一个集中的系统中,最终提供给研究人员(根据隐私规则允许)。该项目将开发一个在线疫苗接种门户网站,其主要目标是提供对收集的数据、图形和数据下载能力的高级分析。该奖项反映了美国国家科学基金会的法定使命,并通过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,被认为值得支持。
项目成果
期刊论文数量(1)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Using COVID-19 Data on Vaccine Shipments and Wastage to Inform Modeling and Decision-Making
- DOI:10.1287/trsc.2022.1134
- 发表时间:2022-04-01
- 期刊:
- 影响因子:4.6
- 作者:Hajibabai, Leila;Hajbabaie, Ali;Vergano, Dan
- 通讯作者:Vergano, Dan
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Ali Hajbabaie其他文献
Effects of ITS-based left turn policies on network performance
基于 ITS 的左转策略对网络性能的影响
- DOI:
- 发表时间:
2010 - 期刊:
- 影响因子:0
- 作者:
Ali Hajbabaie;J. Medina;R. Benekohal - 通讯作者:
R. Benekohal
Traffic Signal Timing and Trajectory Optimization in a Mixed Autonomy Traffic Stream
混合自主交通流中的交通信号配时和轨迹优化
- DOI:
- 发表时间:
2021 - 期刊:
- 影响因子:0
- 作者:
Mehrdad Tajalli;Ali Hajbabaie - 通讯作者:
Ali Hajbabaie
Estimation of Incident Propensity for Reliability Analysis in the Highway Capacity Manual
公路通行能力手册中可靠性分析的事故倾向估计
- DOI:
10.3141/2395-14 - 发表时间:
2013 - 期刊:
- 影响因子:0
- 作者:
S. Aghdashi;N. Rouphail;Ali Hajbabaie - 通讯作者:
Ali Hajbabaie
Estimation of Saturation Headway in Work Zones on Urban Streets
城市街道工作区饱和车头时距估算
- DOI:
10.3141/2615-04 - 发表时间:
2017 - 期刊:
- 影响因子:0
- 作者:
Ali Hajbabaie;Sangkey Kim;Bastian Schroeder;S. Aghdashi;N. Rouphail;Kambiz Tabrizi - 通讯作者:
Kambiz Tabrizi
Real-Time Adaptive Traffic Metering in a Connected Urban Street Network
互联城市街道网络中的实时自适应交通计量
- DOI:
- 发表时间:
2018 - 期刊:
- 影响因子:0
- 作者:
Rasool Mohebifard;Ali Hajbabaie - 通讯作者:
Ali Hajbabaie
Ali Hajbabaie的其他文献
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