Department of Epidemiology, 1959 NE Pacific Street, Magnuson Health Sciences Center, Room F-262, Seattle, WA 98195, United States; International Clinical Research Center, Department of Global Health, 908 Jefferson St., Seattle, WA 98104, United States.
Department of Epidemiology, 1959 NE Pacific Street, Magnuson Health Sciences Center, Room F-262, Seattle, WA 98195, United States; Department of Anthropologym Denny Hall, University of Washington, Seattle, WA 98195, United States.
Vaccine. 2019 Aug 14;37(35):4886-4895. doi: 10.1016/j.vaccine.2019.07.013. Epub 2019 Jul 12.
Pathogen evolution is a potential threat to the long-term benefits provided by public health vaccination campaigns. Mathematical modeling can be a powerful tool to examine the forces responsible for the development of vaccine resistance and to predict its public health implications. We conducted a systematic review of existing literature to understand the construction and application of vaccine resistance models. We identified 26 studies that modeled the public health impact of vaccine resistance for 12 different pathogens. Most models predicted that vaccines would reduce overall disease burden in spite of evolution of vaccine resistance. Relatively few pathogens and populations for which vaccine resistance may be problematic were covered in the reviewed studies, with low- and middle-income countries particularly under-represented. We discuss the key components of model design, as well as patterns of model predictions.
病原体进化是公共卫生疫苗接种活动带来的长期效益所面临的潜在威胁。数学建模可以成为研究导致疫苗耐药性产生的各种因素并预测其公共卫生影响的有力工具。我们对现有文献进行了系统回顾,以了解疫苗耐药性模型的构建和应用。我们确定了 26 项针对 12 种不同病原体的疫苗耐药性公共卫生影响建模研究。大多数模型预测,尽管疫苗耐药性会不断进化,但疫苗仍将降低整体疾病负担。在已审查的研究中,涉及的可能出现疫苗耐药性问题的病原体和人群相对较少,而低收入和中等收入国家的代表性尤其不足。我们讨论了模型设计的关键组成部分以及模型预测的模式。