Hong Kong, UAE airport checks could speed up alerts on viruses, researchers say

HKU study finds that focusing on transit passengers at key hubs could significantly improve early detection timelines Targeted surveillance of transit passengers could speed global detection of new virus variants by about three days, a study has found. Photo: Sam Tsang Targeted surveillance of transit passengers at just two major aviation hubs, Hong Kong and the United Arab Emirates, could speed global detection of new virus variants by about three days, a university study has found. Professor Leo Poon Lit-man, chair of public health virology at the University of Hong Kong (HKU), said on Wednesday that the approach would help authorities stay ahead of emerging threats. “Strengthening local surveillance in all regions remains the foundation of global health security. Our proposed strategy does not require redistributing resources from other regions,” he told a radio programme. “Instead, it leverages surveillance at just two busy international aviation hubs to capitalise on existing capacity. “This approach can establish an early warning system that benefits everyone, accelerating detection of emerging viruses without compromising surveillance elsewhere.” The findings were published in the journal Nature Communications in March. The study, conducted by researchers from the school of public health at HKU’s Li Ka Shing Faculty of Medicine, found that strategically targeting genomic surveillance of international travellers at two major aviation hubs could speed up detection of emerging viral variants by several days, even with limited global resources. The researchers noted that maintaining pandemic-level surveillance over long periods requires substantial investment in manpower, funding and logistics, posing challenges for many regions. They developed a genomic surveillance model designed to be sustainable even in resource-limited settings. Professor Leo Poon says the approach will help authorities stay ahead of emerging threats. Photo: Sun Yeung Using a dataset of 9.5 million viral genomes alongside epidemiological data and global air travel patterns, the team reconstructed the global spread of the Omicron variant and simulated surveillance strategies for future threats. The study found that focusing on transit passengers at key hubs such as Hong Kong and the UAE could significantly improve early detection timelines. Unhandled type: inline-plus-widget {"type":"inline-plus-widget"} The report said the approach was readily implementable and well suited for long-term adoption. It added that even when diagnostic or sequencing capacity was reduced by more than 50 per cent, the strategy continued to outperform existing monitoring approaches, showing strong cost-effectiveness and real-world applicability. The team also tested the model across a range of epidemic scenarios and found its effectiveness remained robust regardless of a variant’s transmissibility or population immunity levels, highlighting its potential as a scalable tool for pandemic preparedness. Poon said traditional surveillance mainly focused on local community cases to track transmission. “In contrast, this study targets travellers, with the aim of detecting virus strains earlier and preventing them from entering the community,” he said. He said that the study initially analysed the world’s busiest global travel hubs. It found airports in Hong Kong and the UAE stood out due to their high passenger volumes and proximity to developing regions, making them highly effective locations for detecting variants. Poon noted that resource-constrained countries often lack the funding, manpower and infrastructure for effective detection, leading to delays in identifying new variants. As travellers from developing regions frequently transit through Hong Kong International Airport, targeting this group could enable earlier detection, faster contact tracing and quicker vaccine development, he said. He added that while the study focused primarily on Covid-19 data, further work was under way to apply similar models to other emerging viruses.