Optimizing Global Genomic Surveillance for Early Detection of Emerging SARS-CoV-2 Variants

Area of Science:

• Epidemiology
• Genomic Surveillance
• Public Health

Background:

• Global viral threats necessitate robust genomic surveillance.
• High costs and unequal resource distribution hinder effective implementation.
• Targeting international travelers in travel hubs offers an efficient early detection strategy for SARS-CoV-2 variants.

Purpose of the Study:

• To evaluate the efficiency of traveler-targeted surveillance for early detection of SARS-CoV-2 variants.
• To compare baseline surveillance with resource-allocation strategies prioritizing travelers.
• To assess the effectiveness of this approach for future variants under various scenarios.

Main Methods:

• Developed and calibrated a multiple-strain metapopulation model.
• Utilized epidemiological, phylogenetic, and air travel data.
• Compared baseline surveillance with traveler-focused approaches for Omicron BA.1/BA.2 and hypothetical future variants.

Main Results:

• Focusing surveillance on travelers at key global hubs significantly reduced detection delays.
• Traveler-targeted approaches outperformed baseline strategies, even with reduced resources.
• Simulations confirmed effectiveness for future variants across different scenarios, including varying transmission and vaccine effectiveness.

Conclusions:

• Provides a quantitative, cost-effective framework for enhancing global genomic surveillance.
• Reallocating resources to international travelers in select hubs improves early variant detection.
• Strengthens public health interventions and pandemic preparedness.