Sutton Karyn L, Banks H T, Castillo-Chavez Carlos
Center for Research in Scientific Computation, & Center for Quantitative Studies in Biomedicine North Carolina State University, Raleigh, NC 27695-8212.
Math Comput Model. 2010 Mar 1;51(5-6):369-388. doi: 10.1016/j.mcm.2009.12.014.
The design and evaluation of epidemiological control strategies is central to public health policy. While inverse problem methods are routinely used in many applications, this remains an area in which their use is relatively rare, although their potential impact is great. We describe methods particularly relevant to epidemiological modeling at the population level. These methods are then applied to the study of pneumococcal vaccination strategies as a relevant example which poses many challenges common to other infectious diseases. We demonstrate that relevant yet typically unknown parameters may be estimated, and show that a calibrated model may used to assess implemented vaccine policies through the estimation of parameters if vaccine history is recorded along with infection and colonization information. Finally, we show how one might determine an appropriate level of refinement or aggregation in the age-structured model given age-stratified observations. These results illustrate ways in which the collection and analysis of surveillance data can be improved using inverse problem methods.
流行病学控制策略的设计与评估是公共卫生政策的核心。虽然反问题方法在许多应用中经常使用，但在这一领域其应用相对较少，尽管其潜在影响很大。我们描述了与人群层面的流行病学建模特别相关的方法。然后将这些方法应用于肺炎球菌疫苗接种策略的研究，作为一个相关实例，该实例提出了许多其他传染病常见的挑战。我们证明可以估计相关但通常未知的参数，并表明如果记录了疫苗接种史以及感染和定植信息，校准后的模型可用于通过参数估计来评估已实施的疫苗政策。最后，我们展示了在给定年龄分层观测数据的情况下，如何在年龄结构模型中确定适当的细化或汇总水平。这些结果说明了使用反问题方法改进监测数据收集和分析的方式。
