Department of Neurology, Oregon Health & Science University, Portland, Oregon, United States of America.
University of Washington, Seattle, Washington, United States of America.
PLoS Negl Trop Dis. 2018 Jun 15;12(6):e0006588. doi: 10.1371/journal.pntd.0006588. eCollection 2018 Jun.
Disease surveillance in rural regions of many countries is poor, such that prolonged delays (months) may intervene between appearance of disease and its recognition by public health authorities. For infectious disorders, delayed recognition and intervention enables uncontrolled disease spread. We tested the feasibility in northern Uganda of developing real-time, village-based health surveillance of an epidemic of Nodding syndrome (NS) using software-programmed smartphones operated by minimally trained lay mHealth reporters.
We used a customized data collection platform (Magpi) that uses mobile phones and real-time cloud-based storage with global positioning system coordinates and time stamping. Pilot studies on sleep behavior of U.S. and Ugandan medical students identified and resolved Magpi-programmed cell phone issues. Thereafter, we deployed Magpi in combination with a lay-operator network of eight mHealth reporters to develop a real-time electronic map of child health, injury and illness relating to NS in rural northern Uganda. Surveillance data were collected for three consecutive months from 10 villages heavily affected by NS. Overall, a total of 240 NS-affected households and an average of 326 children with NS, representing 30 households and approximately 40 NS children per mHealth reporter, were monitored every week by the lay mHealth team. Data submitted for analysis in the USA and Uganda remotely pinpointed the household location and number of NS deaths, injuries, newly reported cases of head nodding (n = 22), and the presence or absence of anti-seizure medication.
This study demonstrates the feasibility of using lay mHealth workers to develop a real-time cartography of epidemic disease in remote rural villages that can facilitate and steer clinical, educational and research interventions in a timely manner.
许多国家的农村地区疾病监测水平较差，疾病出现与公共卫生部门发现之间可能存在数月的延迟。对于传染病，如果不能及时发现和干预，可能会导致疾病的失控传播。我们在乌干达北部测试了利用经过最少培训的基层医疗保健报告员使用软件编程的智能手机进行实时、基于村庄的传染病监测，以监测 Nodding 综合征（NS）流行的可行性。
我们使用了一个定制的数据收集平台（Magpi），该平台使用具有全球定位系统坐标和时间戳的手机和实时基于云的存储。对美国和乌干达医学生睡眠行为的试点研究确定并解决了 Magpi 编程手机问题。此后，我们结合一个由 8 名基层医疗保健报告员组成的基层医疗保健报告员网络，部署了 Magpi，以开发乌干达北部农村地区与 NS 相关的儿童健康、伤害和疾病的实时电子地图。在连续三个月内，从受 NS 严重影响的 10 个村庄中收集了监测数据。总体而言，基层医疗保健报告员每周监测 240 个受 NS 影响的家庭，以及平均 326 名患有 NS 的儿童，每个基层医疗保健报告员代表 30 个家庭和大约 40 名患有 NS 的儿童。由基层医疗保健团队提交的分析数据精确地确定了家庭的位置和 NS 死亡人数、受伤人数、新报告的点头病例（n = 22），以及抗癫痫药物的存在与否。
本研究表明，利用基层医疗保健工作者开发实时农村偏远村庄传染病图谱是可行的，这有助于及时引导临床、教育和研究干预。
