Public health surveillance is defined as the ongoing, systematic collection, analysis, and interpretation of health data and is closely integrated with the timely dissemination of information that the public needs to know and upon which the public should act. Public health surveillance is central to modern public health practice by contributing data and information usually through a national notifiable disease reporting system (NNDRS). Although early identification and prediction of future disease trends may be technically feasible, more work is needed to improve accuracy so that policy makers can use these predictions to guide prevention and control efforts. In this article, we review the advantages and limitations of the current NNDRS in most countries, discuss some lessons learned about prevention and control from the first wave of COVID-19, and describe some technological innovations in public health surveillance, including geographic information systems (GIS), spatial modeling, artificial intelligence, information technology, data science, and the digital twin method. We conclude that the technology-driven innovative public health surveillance systems are expected to further improve the timeliness, completeness, and accuracy of case reporting during outbreaks and also enhance feedback and transparency, whereby all stakeholders should receive actionable information on control and be able to limit disease risk earlier than ever before.

中文翻译：

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新发感染的公共卫生监测创新

公共卫生监测被定义为对健康数据进行持续、系统的收集、分析和解释，并与及时传播公众需要了解和公众应采取行动的信息紧密结合。公共卫生监测是现代公共卫生实践的核心，通常通过国家法定疾病报告系统（NNDRS）提供数据和信息。尽管早期识别和预测未来疾病趋势在技术上可能是可行的，但还需要做更多的工作来提高准确性，以便政策制定者可以利用这些预测来指导预防和控制工作。在本文中，我们回顾了大多数国家当前 NNDRS 的优点和局限性，讨论了第一波 COVID-19 中预防和控制的一些经验教训，并描述了公共卫生监测方面的一些技术创新，包括地理信息系统（ GIS）、空间建模、人工智能、信息技术、数据科学和数字孪生方法。我们的结论是，技术驱动的创新公共卫生监测系统有望进一步提高疫情爆发期间病例报告的及时性、完整性和准确性，并增强反馈和透明度，使所有利益相关者都应获得可操作的控制信息，并能够限制疾病风险比以往任何时候都更早。