He Zonglin, Zhang Casper J P, Huang Jian, Zhai Jingyan, Zhou Shuang, Chiu Joyce Wai-Ting, Sheng Jie, Tsang Winghei, Akinwunmi Babatunde O, Ming Wai-Kit
Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, China.
Faculty of Medicine, International School, Jinan University, Guangzhou, China.
J Med Internet Res. 2020 Sep 17;22(9):e21685. doi: 10.2196/21685.
A novel pneumonia-like coronavirus disease (COVID-19) caused by a novel coronavirus named SARS-CoV-2 has swept across China and the world. Public health measures that were effective in previous infection outbreaks (eg, wearing a face mask, quarantining) were implemented in this outbreak. Available multidimensional social network data that take advantage of the recent rapid development of information and communication technologies allow for an exploration of disease spread and control via a modernized epidemiological approach. By using spatiotemporal data and real-time information, we can provide more accurate estimates of disease spread patterns related to human activities and enable more efficient responses to the outbreak. Two real cases during the COVID-19 outbreak demonstrated the application of emerging technologies and digital data in monitoring human movements related to disease spread. Although the ethical issues related to using digital epidemiology are still under debate, the cases reported in this article may enable the identification of more effective public health measures, as well as future applications of such digitally directed epidemiological approaches in controlling infectious disease outbreaks, which offer an alternative and modern outlook on addressing the long-standing challenges in population health.
一种由名为严重急性呼吸综合征冠状病毒2（SARS-CoV-2）的新型冠状病毒引起的新型肺炎样冠状病毒病（COVID-19）已席卷中国和全球。在此次疫情中实施了在以往感染暴发中有效的公共卫生措施（如佩戴口罩、隔离）。利用信息和通信技术近期的快速发展所获取的多维社交网络数据，使得通过现代化的流行病学方法探索疾病传播和控制成为可能。通过使用时空数据和实时信息，我们能够更准确地估计与人类活动相关的疾病传播模式，并能对疫情做出更高效的应对。COVID-19疫情期间的两个实际案例展示了新兴技术和数字数据在监测与疾病传播相关的人类活动方面的应用。尽管与数字流行病学使用相关的伦理问题仍在讨论中，但本文报道的案例可能有助于确定更有效的公共卫生措施，以及此类数字导向的流行病学方法在控制传染病暴发中的未来应用，这为应对人群健康方面长期存在的挑战提供了一种不同的现代视角。
