Medlock Jan, Meyers Lauren Ancel, Galvani Alison
Department of Mathematical Sciences, Clemson University and The University of Texas at Austin.
PLoS Curr. 2009 Dec 9;1:RRN1134. doi: 10.1371/currents.RRN1134.
During unexpected infectious disease outbreaks, public health agencies must make effective use of limited resources. Vaccine distribution may be delayed and staggered through time, as underscored by the 2009 H1N1 influenza pandemic. Using a mathematical model parametrized with data from the 2009 H1N1 pandemic, we found that optimal allocations of vaccine among people in different age groups and people with high-risk conditions depends on the schedule of vaccine availability relative to the progress of the epidemic. For the projected schedule of H1N1 vaccine availability, the optimal strategy to reduce influenza-related deaths is to initial target high-risk people, followed by school-aged children (5-17) and then young adults (18-44). The optimal strategy to minimize hospitalizations, however, is to target ages 5-44 throughout the vaccination campaign, with only a tiny amount of vaccine used on high-risk people. We find that optimizing at each vaccine release time independently does not give the overall optimal strategy. In this manuscript, we derive policy recommendations for 2009 H1N1 vaccine allocation using a mathematical model. In addition, our optimization procedures, which consider staggered releases over the entire epidemic altogether, are applicable to other outbreaks where not all supplies are available initially.
在突发传染病疫情期间,公共卫生机构必须有效利用有限的资源。正如2009年甲型H1N1流感大流行所凸显的那样,疫苗分发可能会随着时间延迟并错开。通过使用一个以2009年甲型H1N1流感大流行数据为参数的数学模型,我们发现,在不同年龄组人群和高风险状况人群中进行疫苗的最优分配,取决于疫苗可获得时间相对于疫情进展的时间表。对于预计的甲型H1N1流感疫苗可获得时间表,减少流感相关死亡的最优策略是首先针对高风险人群,其次是学龄儿童(5 - 17岁),然后是年轻人(18 - 44岁)。然而,将住院人数降至最低的最优策略是在整个疫苗接种活动中针对5 - 44岁人群,仅用少量疫苗用于高风险人群。我们发现,在每次疫苗发放时独立进行优化并不能得出总体最优策略。在本论文中,我们使用数学模型得出了2009年甲型H1N1流感疫苗分配的政策建议。此外,我们的优化程序,即综合考虑在整个疫情期间错开发放,适用于其他并非所有供应最初都可用的疫情。