一个交互式的国家数字监控系统,用于在孟加拉国打击COVID-19
Farhana Sarker1,2, Moinul H Chowdhury1, Ishrak Jahan Ratul3
1CMED Health Ltd., Dhaka, Bangladesh.
Frontiers in digital health
|May 30, 2023
概括
孟加拉国全国范围的数字监控系统使用人工智能快速选COVID-19病例,识别高风险个人及时干预. 这个系统有助于资源分配,并减少病毒的严重程度.
科学领域:
- 公共卫生 公共卫生
- 传染病流行病学 传染病流行病学
- 数字健康数字健康
背景情况:
- 由于有限的资源和准备,COVID-19在孟加拉国造成了严重的健康危机.
- 像RT-PCR这样的传统诊断方法在农村地区难以获得,并且耗时.
- 数据驱动的智能监控系统对于快速的COVID-19查和风险评估至关重要.
研究的目的:
- 设计,开发和实施一个全国性的基于Web的监控系统,用于COVID-19教育,查和跟踪.
- 为政府和非政府组织提供一个平台来管理COVID-19应对.
- 为了识别有风险的患者,并促进及时转诊进行检测和治疗.
主要方法:
- 一个移动应用程序和云服务器组成了监控系统.
- 社区卫生专业人员通过家庭访问或电话来收集数据.
- 基于规则的人工智能 (AI) 分析数据以进行风险分层和决策.
主要成果:
- 该系统在2020年4月至2022年12月期间完成了1,980,323次检查.
- 人工智能将查的人群分为风险组:51%安全,35%低风险,9%高风险,4%中等风险,1%非常高风险.
- 一个国家仪表板集成收集的数据,以提供全面的概述.
结论:
- 该系统使得有症状的患者能够迅速采取行动,包括隔离或住院.
- 它支持风险绘制,卫生资源规划和对脆弱地区的分配.
- 数字监控系统对于减轻孟加拉国COVID-19的严重程度至关重要.
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