The COVID-19 virus is mutating rapidly. As subvariants like BA.4 and BA.5 emerge, we must act fast to curb the pandemic. Vaccination is the most effective way to control epidemic, but the protection it offers declines as the virus evolves. Predicting vaccine effectiveness in a short time frame is key to winning this battle. CUHK researchers have developed a bioinformatics platform that can provide a snapshot of vaccine effectiveness in real time, instead of it taking months.

Sinovac and BioNTech work more effectively in people who have an abundance amount of a particular bacterium called Bifidobacterium adolescentis in their gut. In most of us, this reduces with age, modern diet, stress, and the use of antibiotics, and a joint CUHK-HKU study has found that those who lack it have a lower antibody response to the vaccines. This implies that modulating the gut has potential to power up the impact of COVID vaccines.

Innovative algorithms developed by a CUHK team, using bioinformatics analysis of virus genome, can estimate vaccine effectiveness (VE) by quantifying the relationship between the genetic mismatch between flu vaccines and current virus strains. This real-time prediction method of VE early in flu season gives the government a heads-up in selecting effective vaccines and organising resources before mass vaccination.

Research results show that physical distancing can only be relaxed in ratio to the rate of vaccination in the city’s population until herd immunity is achieved. A CUHK team developed a social contact index (SCI) which quantifies the effect of distancing and vaccination combined, to bridge gaps between intervention measures and disease transmission.