Research activities

Identifying Sentinel Nodes in Active Infectious Disease Surveillance

Targeting surveillance resources toward individuals at high risk of early infection can accelerate the detection of emerging outbreaks. We propose data-driven surveillance strategies that employ complex network analysis to identify the most vulnerable individuals who contracted the earliest infections during historical infectious disease seasons or those situated near the center of a social network. Our surveillance strategies aim to inform health policymakers, which could help them gain more effective response time to mitigate infectious disease threats.

Papers and Research Reports

Epidemic Surveillance of Influenza Infections: A Network-Free Strategy - Hong Kong Special Administrative Region, China, 2008-2011

Du Z, Tan Q, Bai Y, Wang L, Cowling BJ, Holme P

China CDC Weekly (2022)

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Local Surveillance of the COVID-19 Outbreak

Liu C, Xu L, Bai Y, Xu X, Lau EHY, Cowling BJ, Du Z

Frontiers in Physics (2022)

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Coupling the circadian rhythms of population movement and the immune system in infectious disease modeling

Du Z, Holme P

PloS One (2020)

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Sentinel surveillance of traffic conditions with multilayer network

Bai Y, Du Z, Zhang C, Zhao X

Journal of Ambient Intelligence and Humanized Computing (2019)

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