Time-varying optimization of COVID-19 vaccine prioritization in the context of limited vaccination capacity

Abstract Dynamically adapting the allocation of COVID-19 vaccines to evolving epidemiological situation could be key reduce burden. Here we developed a data-driven mechanistic model SARS-CoV-2 transmission explore optimal vaccine prioritization strategies in China. We found that time-varying vaccination program (i.e., allocating different target groups as epidemic evolves) can highly beneficial it is capable simultaneously achieving objectives (e.g., minimizing number deaths and infections). Our findings suggest boosting capacity up 2.5 million first doses per day (0.17% rollout speed) or higher greatly burden, should new wave start unfold China with reproduction ?1.5. The highest priority categories are consistent under broad range assumptions. Finally, high early phase campaign achieve large gains strategic prioritizations.