国际机场网络中的COVID-19传播算法-DetArpdsds
Cesar Guevara1,2, Dennys Coronel2, Byron Eduardo Salazar Maldonado3
1DataLab, The Institute of Mathematical Sciences (ICMAT-CSIC), Madrid, Spain.
PeerJ. Computer science
|June 22, 2023
概括
这项研究引入了一种新的算法,DetARPDS,用于跟踪COVID-19通过国际机场传播. 该算法在绘制疾病传播途径时实现了93.46%的准确性,改善了检测和处理时间.
科学领域:
- 流行病学 流行病学
- 计算科学 计算科学
- 公共卫生 公共卫生
背景情况:
- 航空运输促进了全球COVID-19的快速传播.
- 机器学习模型在预测疾病传播方面表现有前途.
- 了解机场网络中的疾病传播对于公共卫生至关重要.
研究的目的:
- 分析国际机场网络内的COVID-19传播情况.
- 开发一种计算算法 (DetARPDS) 用于确定疾病传播途径.
- 加强航空旅行中的疾病预防策略.
主要方法:
- 关于路线生成算法 (2017-2021) 的80篇论文的文献综述.
- 分析国际机场数据和COVID-19传播信息 (2020-2022年).
- 使用图形理论,欧几里德距离和迪克斯特拉路线模拟算法的DetARPDS算法的开发.
主要成果:
- DetARPDS算法准确地绘制了COVID-19传播路线,准确率为93.46%.
- 该算法改进了计算方面,如处理时间.
- 更有效地确定了高感染度的机场.
结论:
- DetARPDS算法是追踪机场网络中传播的空气传播疾病的有效工具.
- 这种方法比现有的疾病传播分析方法提供了显著的改进.
- 调查结果可以为公共卫生政策和对航空旅行的干预提供信息.
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