Centers for Disease Control and Prevention, National Center for Immunization and Respiratory Diseases, 1600 Clifton Road NE, Atlanta, GA, 30329, USA.
Centers for Disease Control and Prevention, National Center for HIV, Viral Hepatitis, STD, and TB Prevention, Atlanta, GA, USA.
Appl Health Econ Health Policy. 2022 Jul;20(4):457-465. doi: 10.1007/s40258-022-00718-z. Epub 2022 Feb 9.
Cost-effectiveness analyses (CEAs) are often prepared to quantify the expected economic value of potential vaccination strategies. Estimated outcomes and costs of vaccination strategies depend on numerous data inputs or assumptions, including estimates of vaccine efficacy and disease incidence in the absence of vaccination. Limitations in epidemiologic data can meaningfully affect both CEA estimates and the interpretation of those results by groups involved in vaccination policy decisions. Developers of CEAs should be transparent with regard to the ambiguity and uncertainty associated with epidemiologic information that is incorporated into their models. We describe selected data-related challenges to conducting CEAs for vaccination strategies, including generalizability of estimates of vaccine effectiveness, duration and functional form of vaccine protection that can change over time, indirect (herd) protection, and serotype replacement. We illustrate how CEA estimates can be sensitive to variations in specific epidemiologic assumptions, with examples from CEAs conducted for the USA that assessed vaccinations against human papillomavirus and pneumococcal disease. These challenges are certainly not limited to these two case studies and may be relevant to other vaccines.
成本效益分析（CEA）常用于量化潜在疫苗接种策略的预期经济价值。疫苗接种策略的预期结果和成本取决于众多数据输入或假设，包括疫苗效力和接种疫苗情况下疾病发生率的估计。流行病学数据的局限性可能会对 CEA 估计以及参与疫苗政策决策的团体对这些结果的解释产生重大影响。CEA 的开发者应就纳入其模型的流行病学信息的模糊性和不确定性保持透明。我们描述了进行疫苗接种策略 CEA 时的一些与数据相关的挑战，包括疫苗效力估计的可推广性、疫苗保护的持续时间和功能形式可能随时间变化、间接（群体）保护和血清型替代。我们通过评估针对人乳头瘤病毒和肺炎球菌疾病的疫苗接种的美国进行的 CEA 示例，说明了 CEA 估计如何对特定流行病学假设的变化敏感。这些挑战当然不仅限于这两个案例研究，可能与其他疫苗相关。
