African Rigorous Innovative Stroke Epidemiological Surveillance (ARISES)

项目总结 中风是全球导致死亡和残疾的主要原因；但其准确的 低收入和中等收入国家(LMIC)的负担不明显，特别是在 非洲。监控系统在LMIC几乎不存在，他们在那里 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，少数几个可用地区 对非洲中风负担的估计来自于 疾病(GBD)，主要源自使用不可靠或不充分的模型 数据。开发一种可扩展、可持续、严谨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 关于中风的实际负担和决定因素的实时社区数据 在非洲。这将改善在适当护理下的早期通知和陈述 设施；并为制定、实施和评估有效的 以社区为基础的中风预防、非洲的其他干预措施和政策以及 其他LMIC地区，承担着全球80%以上的中风负担。 非洲严格创新卒中流行病学的总体目标 监控是部署和验证首个可扩展的mHealth 基于社区的交互式卒中信息和监测系统(SISS) 用于可靠地测量和实时跟踪中风的人口负担； 在建设可持续能力以提高中风识字率的同时， 两个先前存在的人口监测点的早期介绍和结果 (Dss)：尼日利亚的一个城市和一个农村地区。 为了实现这一点，我们将利用我们以前创建的资源，包括 1)一部笔画视频纪录片，旨在提高笔画识字和识别能力 社区，2)适合文化的舞蹈节目，以提高对 中风，3)在社区中筛查中风的象形文字工具，以及4)特殊的 准确、严谨的中风表型软件。此外，在1095年， 在尼日利亚的家庭中，我们试行测试了电子监控的关键组件 包括临床医生可用来引出报告的文本消息平台的系统 远程中风事件和mHealth平台，社区通过该平台 会员可以通知卫生工作者中风的发生或死亡。约99% 的社区成员可以轻松使用移动电话；而超过95%的人 表达了通过电话或短信沟通的便利性，愿意 报告中风事件，和/或通过电子监控监控他们的健康状况 系统。为了确保几乎全部病例纳入和准确的分母人口， 我们会继续绘制社区地图，更新人口数字和 人口统计资料，并建立一个新的多管齐下的“冷热追捕”案件 选定决策支持系统集成中的逐户调查确定技术 促进可持续发展的正统和非正统护理系统。我们还将整合 将SISS纳入可持续护理矩阵，以改善DSS中的中风预后。 将新的电子监控、社区参与和 RISES中的卒中护理矩阵使其成为一个整体模型，可以扩展到其他模型 美国和LMIC的低资源设置，以提高易用性、准确性和 产生中风负担的流行病学指数的频率，同时还 提高中风识字率、预防、早期表现和预后 移动健康。

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.