Healthcare Resilience-Population Level Response
Large-scale disruptions can rapidly reshape population health needs and patterns of healthcare utilization. Using large-scale longitudinal EHR datasets, my research develops epidemiological and spatial models to predict infectious disease burden and associated healthcare demand, while examining how disruptions reshape routine healthcare utilization across populations and geographic regions. This work aims to identify emerging vulnerabilities, anticipate shifts in healthcare needs, and support data-driven preparedness and intervention planning.
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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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.
Publications
Healthcare System Resilience and Adaptability to Pandemic Disruptions in the United States.
Nature Medicine (2024).
Zhong, L., Lopez, D., Pei, S., Gao, J.
Examining inequality in healthcare utilization during pandemic disruptions.
(under review) 2025.
Lian J., Pei, S., Gao, J., Zhong, L.
[paper] [code]
medRxiv (2026)
Zhong. L. et al
[paper] [code]
Identifying the shifting sources predicts the dynamics of COVID-19 in US
Chaos: An Interdisciplinary Journal of Nonlinear Science 32.3 (2022).
Wang, Y., Zhong, L., Du, J., Gao, J., Wang, Q.
[paper] [code]
Vaccination and three non-pharmaceutical interventions determine the dynamics of COVID-19 at 381 metropolitan statistical areas in the US.
Humanities and Social Sciences Communications (2022).
Zhong, L., Diagne, M., Wang, Q., Gao, J.
Country distancing increase reveals the effectiveness of travel restrictions in stopping COVID-19 transmission.
Communications Physics 4, 121 (2021) [cover story].
Zhong, L., Diagne, M., Wang, W., Gao, J.
[paper] [code]
Healthcare Resilience-Connected Hospitals/ Connected Healthcare System
Hospitals do not operate in isolation. They are interconnected through patient flows, referrals, and regional patterns of healthcare delivery. Using longitudinal electronic health record (EHR) data integrated with spatial information, my research reconstructs healthcare delivery networks and characterizes how patient flows across healthcare facilities evolve over time and in response to disruptions. This system-level perspective shifts the focus from the resilience of individual hospitals to the resilience of interconnected healthcare delivery networks, providing a data-driven basis for identifying structural vulnerabilities and informing coordinated preparedness and resource allocation.
Selected Publications
Enhancing structural resilience in healthcare through patient flow network.
(Under review) 2024.
Zhong, L., Rennert, L., Pei, S., Gao, J.
[paper] [code]
Universal expansion of human mobility across urban scales
Nature Cities (2025)
Zhong, L., Dong, L., Wang, Q., Song, C., Gao, J.
Switching exploration modes in human mobility
Journal of The Royal Society Interface (2026).
Zhong, L., Dong, L., Wang, Q., Song, C., Gao, J.
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Healthcare Resilience-Coninutiy of care
Healthcare system disruptions ultimately affect individual patients by altering their ability to access and maintain essential care. Using longitudinal electronic health record (EHR) data and patient-level care trajectories, my research examines how disruptions affect patients’ access to and continuity of care, including changes in treatment patterns, care interruptions, and recovery over time.
Selected Publications
Publication
Persistent Collaboration as a Structural Signature of Scientific Resilience
PNAS Nexus. (2026).
Chen H., Bu Yi., Zhong, L. , Du C., Meyer E., Ding Y., Gao J.
[paper] [code]