African Rigorous Innovative Stroke Epidemiological Surveillance (ARISES)

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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.