Optimizing Global Genomic Surveillance for Early Detection of Emerging SARS-CoV-2 Variants
Haogao Gu, Jifan Li, Wanying Sun, Mengting Li, Kathy Leung, Joseph T., Wu, Hsiang-Yu Yuan, Maggie H. Wang, Bingyi Yang, Matthew R. McKay, Ning Ning,, and Leo L.M. Poon

TL;DR
This study demonstrates that targeting genomic surveillance efforts at international travelers in major travel hubs can significantly improve early detection of SARS-CoV-2 variants, offering a cost-effective strategy for global health monitoring.
Contribution
The paper introduces a calibrated multi-strain metapopulation model showing that focusing surveillance on travelers at key hubs enhances early detection without increasing overall efforts.
Findings
Traveler-focused surveillance shortens detection delays.
Outperforms baseline strategies even with reduced resources.
Effective across various future variant scenarios.
Abstract
Background: Global viral threats underscore the need for effective genomic surveillance, but high costs and uneven resource distribution hamper its implementation. Targeting surveillance to international travelers in major travel hubs may offer a more efficient strategy for the early detection of SARS-CoV-2 variants. Methods: We developed and calibrated a multiple-strain metapopulation model of global SARS-CoV-2 transmission using extensive epidemiological, phylogenetic, and high-resolution air travel data. We then compared baseline surveillance with various resource-allocation approaches that prioritize travelers, focusing on Omicron BA.1/BA.2 retrospectively and on hypothetical future variants under different emergence, transmission and vaccine effectiveness scenarios. Findings: Focusing existing surveillance resources on travelers at key global hubs significantly shortened…
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Taxonomy
MethodsEmirates Airlines Office in Dubai
