William Davidson Institute, University of Michigan, Ann Arbor, MI, United States of America.
PLoS One. 2022 Feb 10;17(2):e0263612. doi: 10.1371/journal.pone.0263612. eCollection 2022.
Vaccines are one of the most cost-effective tools for improving human health and well-being. The impact of a vaccine on population health is partly determined by its coverage rate, the proportion of eligible individuals vaccinated. Coverage rate is a function of the vaccine presentation and the population in which that presentation is deployed. This population includes not only the individuals vaccinated, but also the logistics and healthcare systems responsible for vaccine delivery. Because vaccine coverage rates remain below targets in many settings, vaccine manufacturers and purchasers have a shared interest in better understanding the relationship between vaccine presentation, population characteristics, and coverage rate. While there have been some efforts to describe this relationship, existing research and tools are limited in their ability to quantify coverage rate changes across a broad set of antigens, vaccine presentations, and geographies. In this article, we present a method for estimating the impact of improved vaccine technologies on vaccination coverage rates. It is designed for use with low- and middle-income country vaccination programs. This method uses publicly available data and simple calculations based on probability theory to generate coverage rate values. We first present the conceptual framework and mathematical approach. Using a Microsoft Excel-based implementation, we then apply the method to a vaccine technology in early-stage development: micro-array patch for a measles-rubella vaccine (MR-MAP). Example outputs indicate that a complete switch from the current subcutaneous presentation to MR-MAP in the 73 countries ever eligible for Gavi support would increase overall vaccination coverage by 3.0-4.9 percentage points depending on the final characteristics of the MR-MAP. This change equates to an additional 2.6-4.2 million children vaccinated per year. Our method can be readily extended to other antigens and vaccine technologies to provide quick, low-cost estimates of coverage impact. As vaccine manufacturers and purchasers face increasingly complex decisions, such estimates could facilitate objective comparisons between options and help these decision makers obtain the most value for money.
疫苗是改善人类健康和福祉的最具成本效益的工具之一。疫苗对人群健康的影响部分取决于其覆盖率,即接种合格人群的比例。覆盖率是疫苗接种方案和部署该方案人群的函数。该人群不仅包括接种疫苗的个体,还包括负责疫苗接种的后勤和医疗保健系统。由于在许多情况下疫苗覆盖率仍低于目标水平,疫苗制造商和采购商都有共同的兴趣,希望更好地了解疫苗接种方案、人群特征和覆盖率之间的关系。尽管已经有一些努力来描述这种关系,但现有研究和工具在量化广泛抗原、疫苗接种方案和地理位置的覆盖率变化方面能力有限。在本文中,我们提出了一种估计改进的疫苗技术对疫苗接种覆盖率影响的方法。它专为低收入和中等收入国家的疫苗接种计划设计。该方法使用公开数据和基于概率论的简单计算来生成覆盖率值。我们首先介绍概念框架和数学方法。然后,我们使用基于 Microsoft Excel 的实现来应用该方法到一种处于早期开发阶段的疫苗技术:麻疹-风疹微阵列贴剂(MR-MAP)。示例输出表明,在曾经有资格获得 Gavi 支持的 73 个国家中,从当前的皮下接种方案完全切换到 MR-MAP 将使总体接种覆盖率提高 3.0-4.9 个百分点,具体取决于 MR-MAP 的最终特征。这一变化相当于每年额外接种 260 万至 420 万儿童。我们的方法可以很容易地扩展到其他抗原和疫苗技术,以提供对覆盖率影响的快速、低成本估计。随着疫苗制造商和采购商面临越来越复杂的决策,这种估计可以促进选项之间的客观比较,并帮助这些决策者获得最大的资金价值。