African Rigorous Innovative Stroke Epidemiological Surveillance (ARISES)

非洲严格创新中风流行病学监测 (ARISES)

• 批准号: 10411897
• 负责人: BRUCE OVBIAGELE
• 金额: $ 45.64万
• 依托单位: COLLEGE OF MEDICINE, UNIVERSITY OF IBADAN
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-04-01 至 2025-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10411897
• 关键词: Advocacy; Africa; African; Car Phone; Caring; Cause of Death; Cessation of life; Communities; Community Health; Computer software; Country; Dancing; Data; Development; Education; Ensure; Epidemiologic Monitoring; Epidemiological trend; Epidemiology; Evaluation; Evidence based intervention; Frequencies; Funding; Geographic Information Systems; Goals; Health; Health Technology; Health care facility; Household; Income; Individual; Institutes; Intervention; Low income; Maps; Measurement; Modeling; Monitor; Nigeria; Notification; Outcome; Output; Ownership; Phenotype; Policies; Population; Prevalence; Prevention; Production; Public Health Practice; Reporting; Research; Resource-limited setting; Resources; Respondent; Rural; Screening procedure; Site; Stroke; Stroke prevention; Surveys; System; Techniques; Telephone; Text Messaging; Time; United States National Institutes of Health; Update; Ursidae Family; authority; base; burden of illness; care systems; case finding; combat; community engagement; data format; disability; epidemiology study; improved; indexing; innovation; literacy; low and middle-income countries; mHealth; member; novel; pilot test; rural area; rural setting; screening; sociodemographic factors; statistics; stroke event; stroke outcome; thrombolysis; tool; trend; urban setting; willingness

PROJECT SUMMARY Stroke is a leading cause of death and disability globally; but its precise burden is not clear in Low-and Middle-Income Countries (LMIC) particularly in Africa. Surveillance systems are almost non-existent in LMIC, where they are needed most, for reliable determination and tracking of the actual burden of stroke, its epidemiological trends and outcomes. Unlike other regions, the few available estimates of the burden of stroke in Africa come from the Global Burden of Diseases (GBD), which are mostly derived from models using unreliable or scanty data. Developing a scalable sustainable rigorous active e-Surveillance system that takes advantage of available mobile-health technology will provide reliable real-time community-based data on the actual burden and determinants of stroke in Africa. This will improve early notification and presentation in an appropriate care facility; and inform the development, implementation and evaluation of effective community-based stroke prevention, other interventions and policies in Africa and other LMIC regions, which bear over 80% of the global burden of stroke. The overall goal of African Rigorous Innovative Stroke Epidemiological Surveillance (ARISES) is to deploy and validate a first-of-its-kind scalable mHealth community-based interactive Stroke Information and Surveillance System (SISS) for reliable measurement and real-time tracking of the population burden of stroke; while simultaneously building sustainable capacity for improving stroke literacy, early presentation and outcome in two pre-existing demographic surveillance sites (DSS): one urban and one rural area in Nigeria. To achieve this, we will leverage resources we previously created including 1) a stroke video documentary for improving stroke literacy and recognition in communities, 2) a culturally-appropriate dance routine for sensitization about stroke, 3) a pictographic tool for screening stroke in communities, and 4) a special software for accurate rigorous phenotyping of stroke. Furthermore, in 1,095 households in Nigeria, we pilot-tested the key components of the e-Surveillance system including text messaging platform which clinicians can use to elicit reports of stroke events remotely and a mHealth platform through which community members can notify health-workers about stroke occurrence or death. About 99% of the community members had easy access to mobile phones; while over 95% expressed ease of communicating via phone calls or text messages, willingness to report stroke events, and/or have their health monitored via the e-Surveillance system. To ensure near-total case inclusion and accurate denominator population, we will continue to map the community sites, update population figures and demographic profiles, and institute a novel multipronged ‘hot and cold pursuit’ case ascertainment technique with door-to-door surveys in the selected DSS integrating orthodox and non-orthodox care systems for sustainability. We will also integrate the SISS into a sustainable care matrix to improve stroke outcome in the DSS. The integration of the novel e-Surveillance, community engagement, and stroke care matrix in ARISES makes it a holistic model, which is scalable to other low resource-settings in the USA and LMIC to improve the ease, accuracy and frequency of production of epidemiological indices of stroke burden while also improving stroke literacy, prevention, early presentation and outcome using mHealth.

项目摘要 中风是全球死亡和残疾的主要原因。但是它的精度 伯恩在低收入和中等收入国家（LMIC）尚不清楚 非洲。监视系统在LMIC中几乎不存在 对于可靠的确定和跟踪中风的实际燃烧，最需要的， 它的流行病学趋势和结果。与其他地区不同，少数可用 估计非洲中风烧伤的估计来自全球负担 疾病（GBD），这些疾病主要源自模型，使用不可靠或稀少 数据。开发可扩展的可持续严格主动的主动电子保存系统 利用可用的移动健康技术将提供可靠的 实时基于社区的数据，了解实际燃烧和中风的决定 在非洲。这将改善适当护理中的早期通知和呈现 设施;并告知有效的开发，实施和评估 基于社区的中风预防，非洲的其他干预措施和政策 其他LMIC地区承担了全球中风负担的80％以上。 非洲严格的创新中风流行病学的总体目标 监视（出现）是部署和验证首先可伸缩的MHealth 基于社区的互动中风信息和监视系统（SISS） 用于可靠的测量和实时跟踪中风的种群燃烧； 同时，同时建立了改善中风素养的可持续能力，但 在两个先前存在的人口监视地点的早期演示和结果 （DSS）：尼日利亚一个城市和一个农村地区。 为此，我们将利用我们先前创建的资源，包括 1）中风视频纪录片，用于提高中风素养和认可 社区，2）一种适合文化的舞蹈习惯 中风，3）一种用于社区筛查中风的象形工具，以及4）特殊 用于准确严格表型的软件。此外，1,095 我们在尼日利亚的家庭进行了试点测试的电子保存的关键组成部分 系统包括临床医生可以用来引起报告的文本消息平台 远程中风活动和社区通过的MHealth平台 成员可以将中风发生或死亡通知卫生工人。约99％ 社区成员可以轻松访问手机；而超过95％ 表达通过电话或短信进行通信，意愿 举报中风事件和/或通过电子保育监控其健康状况 系统。为了确保几乎完全的案例包含和准确的分母种群， 我们将继续绘制社区网站，更新人口数字和 人口概况，并建立了一种新颖的多收益“热和寒冷追捕”案件 确定技术在选定的DSS集成中使用挨家挨户调查 可持续性的东正教和非东正教护理系统。我们还将整合 SISS成为可持续的护理矩阵，以改善DSS中的中风结果。 新颖的电子保育，社区参与和 出现中风护理矩阵使其成为整体模型，可扩展到其他模型 美国和LMIC的资源较低，以提高便捷性，准确性和 中风燃烧的流行病学指数的生产频率 改善中风素养，预防，早期演示和结局 MHealth。