Strategies for Vaccine Prioritization

Friday, 13 February 2015: 3:00 PM-4:30 PM
Room LL20A (San Jose Convention Center)
Eva K. Lee,Georgia Institute of Technology, Atlanta, GA
When vaccine availability is limited, prioritized vaccination is considered the best strategy to contain a pandemic. We derive a mathematical decision framework to determine the optimal “switch trigger,” the timing for switching from the prioritized vaccination strategy to the non-prioritized strategy during the course of the pandemic. Our approach couples a disease propagation model with both a vaccine queuing model and optimization engine to determine the optimal switch trigger in a mixed strategy that results in minimum infection and mortality during a pandemic outbreak. Such information is critical to public health policy makers as they determine the best strategies for population protection. This is particularly important in determining when to switch from a prioritized strategy focusing on high risk groups to a non-prioritized strategy where the vaccine becomes publicly available. The analysis highlights the importance of non-interrupted vaccine supply. Although the 2009-H1N1 supply eventually covered over 30% of the population, the resulting attack and mortality rates are inferior to a scenario in which only 20% of the population is covered by a non-interrupted supply. Early vaccination is also important: a 3-week delay diminishes a 9.9% infection reduction to a mere 0.9%. The optimal trigger is sensitive to infectivity and vulnerability of the high-risk groups. Our study also underscores the importance of throughput efficiency in dispensing and its effects on the overall attack and mortality rates. The more transmissible the virus is, the lower the threshold for switching to non-prioritized vaccination. Our model is generalizable, and allows incorporation of seasonality and virus mutation of the biological agents. The system empowers policy makers to make the right decisions at the appropriate time to save more lives, better utilize limited resources, and reduce the health service burden during a pandemic event.  This work is the first mathematical-computational model to combine disease propagation, dispensing operations, and optimization capability; and the first that allows rapid determination of optimal switch triggers. Moreover, it includes innovative computational strategies to derive good near-optimal solutions. CDC confirms that this is the first time an actionable and operational switch trigger has been defined, an advance that is critical and vital to better mitigation of infections and mass casualties.