Mathematical and Computational Modeling Sciences Center, School of Human Evolution and Social Change, Arizona State University, Tempe, AZ 85282, USA.
Bull Math Biol. 2012 Apr;74(4):958-80. doi: 10.1007/s11538-011-9704-y. Epub 2011 Dec 7.
In the context of pandemic influenza, the prompt and effective implementation of control measures is of great concern for public health officials around the world. In particular, the role of vaccination should be considered as part of any pandemic preparedness plan. The timely production and efficient distribution of pandemic influenza vaccines are important factors to consider in mitigating the morbidity and mortality impact of an influenza pandemic, particularly for those individuals at highest risk of developing severe disease. In this paper, we use a mathematical model that incorporates age-structured transmission dynamics of influenza to evaluate optimal vaccination strategies in the epidemiological context of the Spring 2009 A (H1N1) pandemic in Mexico. We extend previous work on age-specific vaccination strategies to time-dependent optimal vaccination policies by solving an optimal control problem with the aim of minimizing the number of infected individuals over the course of a single pandemic wave. Optimal vaccination policies are computed and analyzed under different vaccination coverages (21%-77%) and different transmissibility levels ([Formula: see text] in the range of 1.8-3). The results suggest that the optimal vaccination can be achieved by allocating most vaccines to young adults (20-39 yr) followed by school age children (6-12 yr) when the vaccination coverage does not exceed 30%. For higher [Formula: see text] levels ([Formula: see text]), or a time delay in the implementation of vaccination (>90 days), a quick and substantial decrease in the pool of susceptibles would require the implementation of an intensive vaccination protocol within a shorter period of time. Our results indicate that optimal age-specific vaccination rates are significantly associated with [Formula: see text], the amount of vaccines available and the timing of vaccination.
在大流行流感的背景下，及时有效地实施控制措施是全世界公共卫生官员关注的焦点。特别是，疫苗接种的作用应被视为任何大流行准备计划的一部分。及时生产和有效分配大流行流感疫苗是减轻流感大流行发病率和死亡率影响的重要因素，特别是对于那些有发展为严重疾病风险最高的人。在本文中，我们使用了一个包含流感年龄结构传播动力学的数学模型，来评估墨西哥 2009 年春季 A(H1N1)大流行的流行病学背景下的最佳疫苗接种策略。我们通过解决一个最优控制问题，将针对特定年龄的疫苗接种策略扩展到与时间相关的最优疫苗接种策略，目的是在单一大流行波的过程中最大限度地减少受感染个体的数量。我们在不同的疫苗接种覆盖率（21%-77%）和不同的传染性水平（[公式：见正文]在 1.8-3 的范围内）下计算和分析最优疫苗接种策略。结果表明，当疫苗接种覆盖率不超过 30%时，最优疫苗接种可以通过将大部分疫苗分配给年轻成年人（20-39 岁），然后是学龄儿童（6-12 岁）来实现。对于更高的[公式：见正文]水平（[公式：见正文]），或疫苗接种实施的时间延迟（>90 天），要实现易感人群的快速大量减少，需要在较短的时间内实施密集的疫苗接种方案。我们的结果表明，最佳的年龄特异性疫苗接种率与[公式：见正文]、可用疫苗数量和疫苗接种时间密切相关。
