RAPID: Data driven mathematical modeling of the shared epidemiology of Zika and other arboviruses across the globe

RAPID：全球寨卡病毒和其他虫媒病毒共同流行病学的数据驱动数学模型

• 批准号: 1642174
• 负责人: Derek Cummings
• 金额: $ 20万
• 依托单位: University of Florida
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-05-01 至 2017-10-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1642174&HistoricalAwards=false
• 关键词: RAPID; Data; driven; mathematical; modeling

This RAPID award will develop estimates of the transmission capability and potential global burden of infection of the Zika virus. These estimates are urgently needed but difficult to obtain because of inaccuracies in blood tests and under reporting of infections. Using existing serum samples together with mathematical modeling, the project will fill knowledge gaps about i) transmission parameters for Zika, ii) the consistency of surveillance approaches, and iii) the global risk of Zika transmission. This approach will also capture information about other viral infections (e.g., chikungunya and dengue) and the potential for future spread. Results from this project will be relevant to the Zika public health emergency, and the researchers have set in place mechanisms to share quality-assured interim and final data as rapidly and widely as possible, including with public health and research communities.This project will use mathematical models informed by sample serology to estimate the transmission potential for Zika across the globe. Currently, the utility of inference is limited with surveillance reports alone and traditional serological methods, the latter because of cross-reactivity between arboviruses. This project will use a new low-cost, high throughput assay to test for the historic exposure of different antibodies for Zika and other arboviruses. It will compare the rate susceptible individuals in communities that acquire different arboviruses over time. From these results, geostatistical models to predict the force of infection will be developed and risk maps for Zika and other arboviruses will be validated. This knowledge will be used to characterize the shared epidemiology of arboviral diseases around the world.

该RAPID奖将对寨卡病毒的传播能力和感染的潜在全球负担进行估计。迫切需要这些估计数，但由于血液检查不准确和感染报告不足，难以获得这些估计数。利用现有血清样本和数学建模，该项目将填补以下方面的知识空白：1)寨卡病毒传播参数；2)监测方法的一致性；3)寨卡病毒传播的全球风险。这种方法还将获取有关其他病毒感染（例如基孔肯雅热和登革热）以及未来传播可能性的信息。该项目的结果将与寨卡公共卫生紧急情况相关，研究人员已经建立了机制，以便尽可能迅速和广泛地共享有质量保证的中期和最终数据，包括与公共卫生和研究界共享数据。该项目将使用样本血清学提供的数学模型来估计寨卡病毒在全球的传播潜力。目前，仅凭监测报告和传统的血清学方法推断的效用有限，后者由于虫媒病毒之间的交叉反应性。该项目将使用一种新的低成本、高通量的检测方法来检测寨卡病毒和其他虫媒病毒的不同抗体的历史暴露情况。它将比较不同时间内感染不同虫媒病毒的社区中易感个体的比率。根据这些结果，将开发用于预测感染力量的地质统计模型，并验证寨卡病毒和其他虫媒病毒的风险图。这一知识将用于描述世界各地虫媒病毒性疾病的共同流行病学特征。

项目成果

Predicting intensities of Zika infection and microcephaly using transmission intensities of other arboviruses

利用其他虫媒病毒的传播强度预测寨卡病毒感染和小头畸形的强度

• DOI: 10.2471/blt.16.174128
• 发表时间: 2016
• 期刊: Bulletin of the World Health Organization
• 影响因子: 11.1
• 作者: Rodr?guez-Barraquer, Isabel;Salje, Henrik;Lessler, Justin;Cummings, Derek AT
• 通讯作者: Cummings, Derek AT