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2014年西非埃博拉疫情中各种药物和公共卫生战略的成功，以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，考虑到一个人的变化？的传染性，在医院或社区环境中发生的传播的变化，以及由于地理和空间变化引起的传播差异。这一拟议工具将利用西非疫情的现有数据，准确反映实地情况。因此，这项研究的结果将提供即时相关和实时的信息。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。该数据集包含来自当前疫情的1360例病例和7400例追踪接触者，将用于参数化模型。这些数据将提供有关个人行为变化的信息，以应对疾病传播、社区间流动和自我克制措施。将在模型中评估药物数据，包括实验性疫苗以及基于社区的抗病毒疗法，如ZMapp和法匹拉韦。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、治疗中心的能力大小以及家庭防护包的分配和功效。这一工具将为公共卫生专业人员提供重要信息，协助他们就资源分配作出重要决定，以最大限度地扩大影响和公共卫生成果。