Nowcasting the spread of COVID-19 to inform control policies in Hong Kong

Abstract

In this talk, I will discuss two of the COVID-19 nowcasting projects in my group that help informed the Hong Kong government on its pandemic control policies. In the first project, we developed a new framework that parameterizes disease transmission models with age-specific digital mobility data. By fitting the model to case data in Hong Kong, we were able to accurately track the local effective reproduction number of COVID-19 in near real-time (i.e. no longer constrained by the delay of around 9 days between infection and reporting of cases) which is essential for quick assessment of the effectiveness of interventions on reducing transmissibility. Our findings showed that accurate nowcast and forecast of COVID-19 epidemics can be obtained by integrating valid digital proxies of physical mixing into conventional epidemic models. In the second project, we assessed the relative transmissibility of two new SARS-CoV-2 lineages with the N501Y mutation in the receptor-binding domain of the spike protein have spread rapidly in the United Kingdom in late-2020. We estimated that the earlier 501Y lineage without amino acid deletion Δ69/Δ70 circulating mainly between early September to mid-November was 10% (6-13%) more transmissible than the 501N lineage, and the 501Y lineage with amino acid deletion Δ69/Δ70 circulating since late September was 75% (70-80%) more transmissible than the 501N lineage.