Human behavior-driven epidemic surveillance in urban landscapes
arxiv(2024)
摘要
We introduce a surveillance strategy specifically designed for urban areas to
enhance preparedness and response to disease outbreaks by leveraging the unique
characteristics of human behavior within urban contexts. By integrating data on
individual residences and travel patterns, we construct a Mixing matrix that
facilitates the identification of critical pathways that ease pathogen
transmission across urban landscapes enabling targeted testing strategies. Our
approach not only enhances public health systems' ability to provide early
epidemiological alerts but also underscores the variability in strategy
effectiveness based on urban layout. We prove the feasibility of our
mobility-informed policies by mapping essential mobility flows to major transit
stations, showing that few resources focused on specific stations yields a more
effective surveillance than non-targeted approaches. This study emphasizes the
critical role of integrating human behavioral patterns into epidemic management
strategies to improve the preparedness and resilience of major cities against
future outbreaks.
更多查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要