Peer-reviewed article
Retrospective assessment of vaccination policy optimizations during an Omicron BA.2 epidemic in Hong Kong: A modelling study.
Benjamin R Young, Faith Ho, Yun Lin, Eric H Y Lau, Peng Wu et al. ·
Summary
Written by AI, not yet AICS's view · claude-haiku-4-5-20251001This is a modelling study of COVID-19 vaccination policy in Hong Kong during the Omicron BA.2 epidemic in 2022. It uses mathematical models to estimate what would have happened if vaccination coverage had been different, particularly in elderly and middle-aged populations. The study concludes that higher vaccination coverage in people over 80 and earlier vaccination campaigns could have prevented many deaths and hospitalizations.
Key points
- If people over 80 had primary series vaccination coverage equal to the general adult population, 27.6% of deaths could have been averted
- High primary series coverage in 40-49-year-olds would have averted 32.6% more hospitalizations
- Advancing vaccination campaigns by two weeks would have prevented 498-601 deaths
- Earlier vaccination of children had no significant impact on population-wide deaths
- The study emphasizes targeting high-risk and transmission-driving age groups rather than universal approaches
Limitations
This is a modelling study using counterfactual simulations, not an evaluation of what actually happened with real-world vaccination outcomes. The model's assumptions about transmission dynamics and vaccine effectiveness are not independently validated against other evidence.
Abstract
BACKGROUND: Suboptimal COVID-19 vaccine distribution hampers their potential disease protection impact. The 2022 BA.2 epidemic in Hong Kong, occurring over a year into vaccination efforts, resulted in one of the highest daily mortality rates of the pandemic. METHODS: We developed an age- and dose-structured SEIR model to describe the transmission dynamics in this epidemic. Then we fitted the model to severe disease data to estimate the transmission dynamics of the epidemics by Bayesian inference. After that, we conducted extensive counterfactual simulations based on the fitted transmission dynamics and considered varying age-specific vaccination coverages and timing to estimate the impact on severe disease across scenarios. RESULTS: If individuals over 80 had primary series coverage similar to the adult population, 27.6 % (95 % posterior predictive interval [PPI]: 24.7 %, 31.1 %) of deaths could have been averted. High primary series coverage in 40-49-year-olds averted 32.6 % (95 % PPI: 30.0 %, 35.5 %) more hospitalisations. Advancing the adult or senior vaccination campaign by two weeks significantly reduced deaths by 498 (95 % PPI: 309, 688) and 601 (95 % PPI: 412, 792), respectively. Earlier vaccination of children had no significant impact on population-wide deaths. CONCLUSIONS: Low elderly primary series coverage led to the most preventable deaths, while high coverage in middle-aged groups significantly averted excess hospitalisations. Our study underscores the importance of targeting COVID-19 vaccinations in high-risk and transmission-driving groups, as well as vaccination time-sensitivity, where each week difference, averts or abets morbidity and mortality.