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Updated: May 27, 2025

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描述美国的空间连接性和对地理疾病动态和元人口建模的影响:纵向观测研究

Giulia Pullano1, Lucila Gisele Alvarez-Zuzek2, Vittoria Colizza3

  • 1Department of Biology, Georgetown University, 37th and O Streets NW, Washington, DC, 20057-1229, United States, 1 202 687 9256.

JMIR public health and surveillance
|February 18, 2025
PubMed
概括

即使在COVID-19期间,美国的人类流动模式也保持稳定,这解释了广泛的疫情. 静态的,集群的移动数据可以有效地模拟疾病传播.

关键词:
在 COVID-19 疫情中,这就是SARS-CoV-2病毒.安全图表安全图表美国 美国 美国冠状病毒冠状病毒的新冠病毒.数字健康数字健康这是一个流行病流行病.地理疾病动态 疾病动态医疗信息学 医疗信息学人类流动性 人类流动性传染病是一种传染性疾病.移动健康 移动健康 移动健康 移动健康超级人口建模模型移动应用程序 移动应用程序移动健康的移动健康移动数据的移动性数据流行病是一种流行病.公共卫生公共卫生.保持社会距离,保持社会距离.空间连接性 空间连接性时间空间的时间空间.

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