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: 10579303
• 负责人: BRUCE OVBIAGELE
• 金额: $ 43.88万
• 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/10579303
• 关键词: Advocacy; Africa; African; Authorization documentation; Caring; Cause of Death; Cellular Phone; Cessation of life; Communication; 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; 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; authority; burden of illness; care systems; case finding; combat; community engagement; disability; epidemiology study; improved; indexing; innovation; integration site; 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.

项目概要 中风是全球死亡和残疾的主要原因；但其精确 低收入和中等收入国家（LMIC）的负担不明确，特别是在 非洲。中低收入国家几乎不存在监控系统 最需要的是可靠地确定和跟踪中风的实际负担， 其流行病学趋势和结果。与其他地区不同，可用的地区很少 对非洲中风负担的估计来自全球负担 疾病（GBD），主要源自使用不可靠或缺乏的模型 数据。开发可扩展、可持续、严格的主动电子监控系统 利用现有的移动医疗技术将提供可靠的 关于中风实际负担和决定因素的实时社区数据 在非洲。这将改善早期通知和适当护理的呈现 设施;并为有效的开发、实施和评估提供信息 非洲和非洲的基于社区的中风预防、其他干预措施和政策 其他中低收入国家地区的中风负担占全球的 80% 以上。 非洲严格创新脑卒中流行病学总体目标 Surveillance (ARISES) 旨在部署和验证首个可扩展的移动医疗 基于社区的交互式中风信息和监测系统（SISS） 可靠测量和实时跟踪中风人群负担； 同时建立可持续能力以提高中风知识， 两个现有人口监测站点的早期报告和结果 (DSS)：尼日利亚一城一乡。 为了实现这一目标，我们将利用我们之前创建的资源，包括 1) 一部中风视频纪录片，旨在提高人们对中风的认识和认识 社区，2) 适合文化的舞蹈动作，以提高人们对 中风，3）用于社区筛查中风的象形工具，以及 4）特殊的 用于准确、严格的中风表型分析的软件。此外，在 1,095 在尼日利亚的家庭中，我们对电子监控的关键组件进行了试点测试 系统包括临床医生可以用来引出报告的短信平台 远程中风事件和移动医疗平台，社区可以通过该平台 会员可以将中风发生或死亡的情况通知卫生工作者。约99% 的社区成员可以轻松使用手机；而超过95% 通过电话或短信表达沟通的便利性、意愿 报告中风事件，和/或通过电子监控监测其健康状况 系统。为了确保几乎全部病例纳入和准确的分母人口， 我们将继续绘制社区站点地图、更新人口数据并 人口统计资料，并提出新颖的多管齐下的“冷热追击”案例 在选定的 DSS 集成中采用挨家挨户调查的确定技术 正统和非正统的可持续护理系统。我们还将整合 将 SISS 纳入可持续护理矩阵，以改善 DSS 中的中风结果。 新颖的电子监控、社区参与和 ARISES 中的中风护理矩阵使其成为一个整体模型，可扩展到其他模型 美国和中低收入国家的低资源设置，以提高易用性、准确性和 中风负担流行病学指数的产生频率，同时也 提高中风素养、预防、早期表现和结果 移动健康。