13个国家的合成人与人接触网络的高分辨率数据集,用于传染病传播
Zhilu Yuan1,2, Ziyao Luo1,2, Shenyao Lin1,2
1State Key Laboratory of Subtropical Building and Urban Science, Shenzhen University, Shenzhen, China.
Data in brief
|January 21, 2026
概括
生成合成的人类接触网络对于疾病传播建模至关重要. 本研究提出了一种方法,为13个国家创建详细的个人级网络,以帮助传染病研究.
科学领域:
- 流行病学 流行病学
- 计算生物学 计算生物学
- 网络科学 网络科学
背景情况:
- 像COVID-19这样的传染病威胁需要先进的建模工具.
- 基于代理的模型 (ABM) 需要高分辨率的人类联系网络来进行准确的模拟.
- 公共可用,细粒度的联系网络数据集很少.
研究的目的:
- 为了解决人与人接触网络数据的稀缺问题.
- 开发一种方法来生成个人级别的合成联系网络.
- 创建现实的联系网络,用于疾病传播模型.
主要方法:
- 确定了合成网络生成的九个关键参数.
- 通过在线搜索编制了13个国家的参数值.
- 每个国家为1万个人建立了多层次的联系网络,包括人口统计特征和各种环境中的联系模式.
主要成果:
- 创建合成联系网络,包括家庭,学校,工作场所和社区的互动.
- 通过将社会人口统计指标与官方人口普查数据进行比较来验证网络.
- 证明了合成网络在模拟疾病传播方面的实用性.
结论:
- 开发的方法为创建合成人与人接触网络提供了宝贵的资源.
- 这些网络可以提高基于病原体的流行病学模型的准确性和适用性.
- 这项研究有助于更好地准备和应对传染病的应对策略.
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