The power of artificial intelligence for managing pandemics: A primer for public health professionals.

IF 1.9 4区 医学 Q3 HEALTH POLICY & SERVICES
Martin McKee, Rikard Rosenbacke, David Stuckler
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引用次数: 0

Abstract

Artificial intelligence (AI) applications are complex and rapidly evolving, and thus often poorly understood, but have potentially profound implications for public health. We offer a primer for public health professionals that explains some of the key concepts involved and examines how these applications might be used in the response to a future pandemic. They include early outbreak detection, predictive modelling, healthcare management, risk communication, and health surveillance. Artificial intelligence applications, especially predictive algorithms, have the ability to anticipate outbreaks by integrating diverse datasets such as social media, meteorological data, and mobile phone movement data. Artificial intelligence-powered tools can also optimise healthcare delivery by managing the allocation of resources and reducing healthcare workers' exposure to risks. In resource distribution, they can anticipate demand and optimise logistics, while AI-driven robots can minimise physical contact in healthcare settings. Artificial intelligence also shows promise in supporting public health decision-making by simulating the social and economic impacts of different policy interventions. These simulations help policymakers evaluate complex scenarios such as lockdowns and resource allocation. Additionally, it can enhance public health messaging, with AI-generated health communications shown to be more effective than human-generated messages in some cases. However, there are risks, such as privacy concerns, biases in models, and the potential for 'false confirmations', where AI reinforces incorrect decisions. Despite these challenges, we argue that AI will become increasingly important in public health crises, but only if integrated thoughtfully into existing systems and processes.

人工智能管理大流行病的力量:公共卫生专业人员入门指南。
人工智能 (AI) 应用复杂且发展迅速,因此人们往往对其知之甚少,但它却可能对公共卫生产生深远影响。我们为公共卫生专业人员提供了一份入门指南,解释了其中涉及的一些关键概念,并探讨了如何将这些应用用于应对未来的大流行病。这些应用包括早期疫情检测、预测建模、医疗保健管理、风险交流和健康监测。人工智能应用,尤其是预测算法,有能力通过整合社交媒体、气象数据和手机移动数据等各种数据集来预测疫情爆发。由人工智能驱动的工具还可以通过管理资源分配和减少医护人员面临的风险来优化医疗服务。在资源分配方面,它们可以预测需求并优化物流,而人工智能驱动的机器人可以最大限度地减少医疗环境中的物理接触。通过模拟不同政策干预措施的社会和经济影响,人工智能在支持公共卫生决策方面也大有可为。这些模拟有助于决策者评估封锁和资源分配等复杂情况。此外,人工智能还能加强公共卫生信息的传递,在某些情况下,人工智能生成的健康信息比人类生成的信息更有效。不过,人工智能也存在一些风险,如隐私问题、模型中的偏差以及 "错误确认 "的可能性,即人工智能会强化不正确的决定。尽管存在这些挑战,但我们认为,人工智能在公共卫生危机中将变得越来越重要,但前提是必须深思熟虑地融入现有系统和流程。
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来源期刊
CiteScore
4.50
自引率
3.70%
发文量
197
期刊介绍: Policy making and implementation, planning and management are widely recognized as central to effective health systems and services and to better health. Globalization, and the economic circumstances facing groups of countries worldwide, meanwhile present a great challenge for health planning and management. The aim of this quarterly journal is to offer a forum for publications which direct attention to major issues in health policy, planning and management. The intention is to maintain a balance between theory and practice, from a variety of disciplines, fields and perspectives. The Journal is explicitly international and multidisciplinary in scope and appeal: articles about policy, planning and management in countries at various stages of political, social, cultural and economic development are welcomed, as are those directed at the different levels (national, regional, local) of the health sector. Manuscripts are invited from a spectrum of different disciplines e.g., (the social sciences, management and medicine) as long as they advance our knowledge and understanding of the health sector. The Journal is therefore global, and eclectic.
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