RAPID: Optimal allocation of both non-pharmaceutical and pharmaceutical interventions toward controlling Ebola virus transmission in West Africa

RAPID：非药物和药物干预措施的优化分配，以控制西非埃博拉病毒的传播

• 批准号: 1514673
• 负责人: Alison Galvani
• 金额: $ 19.99万
• 依托单位: Yale University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-12-15 至 2016-02-29
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1514673&HistoricalAwards=false
• 关键词: RAPID; Optimal; allocation; both; non

This research will evaluate the success of various pharmaceutical and public health strategies in the 2014 West Africa Ebola outbreak in order to most effectively control and reduce the spread of disease. The investigators will develop a mathematical model that considers variability in a person?s infectiousness, the variation in transmission that occurs in a hospital or community setting, as well as the differences in transmission due to geography and spatial variation. This proposed tool will utilize current data from the outbreak in West Africa to accurately reflect the on-the-ground situation. Consequently, results from this research will provide immediately relevant and real-time information. The investigators are utilizing contact tracing data collected by the Liberian Ministry of Health and Social Welfare. This dataset of 1360 cases and 7400 traced contacts from the current outbreak will be used to parameterize the model. The data will provide information on individual behavior changes in response to disease spread, between-community movement and self-quarantining measures. Pharmaceutical data including experimental vaccines, as well as community based antiviral therapies such as ZMapp and favipiravir will be evaluated in the model. The following non-pharmaceutical public health interventions will be evaluated in the model: quantity of public health personnel and ambulance services, magnitude of treatment center capacity, and the allocation and efficacy of household protective kits. This tool will offer important information to public health professionals to assist them in making critical decisions on resource allocation in order to maximize impact and public health outcomes.

这项研究将评估各种制药和公共卫生策略在 2014 年西非埃博拉疫情中的成功情况，以便最有效地控制和减少疾病的传播。研究人员将开发一个数学模型，该模型考虑了人的传染性的变异性、医院或社区环境中发生的传播的变异性，以及由于地理和空间变化而导致的传播差异。该拟议工具将利用西非疫情爆发的当前数据来准确反映实地情况。因此，这项研究的结果将提供立即相关的实时信息。调查人员正在利用利比里亚卫生和社会福利部收集的接触者追踪数据。该数据集包含当前疫情中的 1360 例病例和 7400 名追踪接触者，将用于参数化模型。这些数据将提供有关因疾病传播、社区间流动和自我隔离措施而导致的个人行为变化的信息。该模型将评估包括实验疫苗以及基于社区的抗病毒疗法（例如 ZMapp 和法匹拉韦）的药物数据。该模型将评估以下非药物公共卫生干预措施：公共卫生人员和救护车服务的数量、治疗中心容量的大小以及家庭防护套件的分配和有效性。该工具将为公共卫生专业人员提供重要信息，帮助他们做出资源分配的关键决策，以最大限度地发挥影响和公共卫生成果。