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Spatial Disease Dynamics and Human Mobility Network
Analyze data on human movement from fine-grained individual trajectories to commuting and air travel flows, develop models to simulate disease spread, evaluate the effectiveness of various intervention strategies, and contribute to the development of more effective public health policies and strategies for controlling the spread of infectious diseases.
Publications (with links)
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Zhong, L., Dong, L., Wang, Q., Song, C., Gao, J. Universal spatial inflation of human mobility. 2023. (Under review)
Health Resilience/Adaptability to Disaster
How a healthcare/health system adapts to disaster to gain better resilience is largely unknown. Utilize performance-based and network-based methods, and long time-range data to measure the system's behavior to adapt to various disasters, such as pandemics and extreme events, which are in different severity and duration. The system of concerns includes healthcare systems and other related systems.
Fund
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Funded by COVID-19 Research Accelerator Grants (Bill & Melinda Gates Foundation)
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Title: Harness network science to reduce treatment resource disparities and social disadvantages
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People: Lu Zhong (PI), Jianxi Gao (PI)
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Period: July 2021-now
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Assess the impact of disruptions (e.g., the COVID-19 pandemic) on healthcare systems, examine how the disruption contributes to health disparities, and develop evidence-based strategies for improving access to healthcare services and resources, and for building more resilient healthcare systems by leveraging analysis on electronic health record (EHR) data analysis, modeling, and simulations.
Publication
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Zhong, L., Lopez, D., Pei, S., Gao, J. Healthcare System Resilience and Adaptability to Pandemic Disruptions in the United States. Nature Medicine (2024).
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Zhong, L., et al. Optimizing physician-patient networks for enhanced resilience and reduced inequity. 2023. (working paper).
Publication
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Zhong, L., et al. Artificial intelligence enhances health system resilience through hospital collaboration. 2024 (working paper).
AI+Health+Network Science
Utilize data-driven approaches (AI-powered analytical tools) to develop mechanistic models that can capture the behavior of complex systems and networks, understand the system's structure and dynamics, and apply these approaches to healthcare systems to improve decision-making and optimize system performance.
Data Support
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