Center for Research in Scientific Computation, & Center for Quantitative Studies in Biomedicine, North Carolina State University, Raleigh, NC 27695-8212, USA.
J Biol Dyn. 2010 Mar;4(2):176-95. doi: 10.1080/17513750903023715.
Public health professionals are charged with the task of designing prevention programs for the effective control of biologically intricate infectious diseases at a population level. The effective vaccination of a population for pneumococcal diseases (infections caused by Streptococcus pneumoniae) remains a relevant question in the scientific community. It is complicated by heterogeneity in individuals' responses to exposure to the bacterium and their responses to vaccination. Due to these complexities, most modelling efforts in this area have been on the cellular/bacteria level. Here, we introduce an age-structured SEIS-type model of pneumococcal diseases and their vaccination. We discuss the use of this framework in predicting the impact of vaccine strategies, with pneumococcal diseases as an example. Using parameter values reasonable for a developed country, we discuss the effects of targeting the colonization and/or infection stages on the age profiles of morbidity in a population.
公共卫生专业人员的任务是设计预防计划，以有效控制人群层面上生物学上复杂的传染病。人群中肺炎球菌病（由肺炎链球菌引起的感染）的有效疫苗接种仍然是科学界的一个相关问题。由于个体对细菌暴露的反应和对疫苗接种的反应存在异质性，因此情况变得复杂。由于这些复杂性，该领域的大多数建模工作都集中在细胞/细菌水平上。在这里，我们引入了一种肺炎球菌病及其疫苗接种的年龄结构 SEIS 型模型。我们讨论了使用该框架预测疫苗接种策略的影响，以肺炎球菌病为例。使用对于发达国家合理的参数值，我们讨论了针对定植和/或感染阶段对人群发病率年龄分布的影响。
