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紧急情况下的人工智能和公共卫生数据:中东的一个关键问题
Osama Ali Maher1, Giuseppe Pichierri2, Christian Popescu3
1United Nations University, Jakarta, Indonesia.
The American journal of tropical medicine and hygiene
|February 24, 2026
概括
加强公共卫生数据系统,特别是在低收入国家,对于有效应对紧急情况至关重要. 地方数字基础设施是克服数据延迟和实现更快,公平的公共卫生行动的关键.
科学领域:
- 公共卫生 公共卫生
- 医疗信息学 医疗信息学
- 数字健康数字健康
背景情况:
- 有效的公共卫生紧急响应依赖于及时,可靠的数据.
- 人工智能 (AI) 提供了提高疫情预测和资源分配的潜力.
- 数字基础设施的不平等,特别是在低收入和中等收入国家,阻碍了数据管理和应急响应.
研究的目的:
- 检查数据传输延迟如何影响公共卫生紧急响应.
- 在各种环境中识别导致数据延迟的因素.
- 突出当地数字基础设施对于及时采取公共卫生行动的重要性.
主要方法:
- 对公共卫生紧急情况中数据传输延迟的分析.
- 来自流行病,气候相关和受冲突影响地区 (也门,伊拉克,苏丹) 的案例研究.
- 检查挑战,包括基于纸张的收集,分散的数据库,语言障碍,云依赖和电信漏洞等.
主要成果:
- 由于基础设施和系统问题导致的公共卫生数据传输延迟,削弱了应急响应能力.
- 数据中心在高收入地区的地理集中增加了延迟,减少了当地控制.
- 反应式预警系统的结果是由于这些延迟而受到侵蚀的监控数据价值.
结论:
- 人工智能是一个下游工具,而不是一个独立的解决方案;它的有效性取决于强大的数据生态系统.
- 加强本地,互操作和弹性数字基础设施对于公共卫生数据管理至关重要.
- 投资于当地数字基础设施和治理,可确保及时,公平和有效地管理公共卫生紧急情况.
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