School of Public Health, University of California, Berkeley, CA 94720, USA.
Adv Exp Med Biol. 2010;673:172-83. doi: 10.1007/978-1-4419-6064-1_12.
The purpose of infectious disease transmission modelling is often to understand the factors that are responsible for the persistence of transmission, the dynamics of the infection process and how best to control transmission. As such, there should be great potential to use mathematical models to routinely plan and evaluate disease control programs. In reality, there are many challenges that have precluded the practical use of disease models in this regard. One challenge relates to the mathematical complexity of the models, which has made it difficult for field workers and health officials to understand and use them. Another challenge is that, despite their mathematical complexity, models typically do not have sufficient structural complexity to consider many of the site-specific epidemiologic and disease control details that the practicing health official routinely considers. Moreover, most modelling studies have not been sufficiently explicit or exemplary in explaining how field data may be incorporated into the models to impact public health decision-making. In this chapter, we start with a classic model of schistosomiasis transmission and relate its key properties to the more detailed model of Schistosoma japonicum model presented in chapter by Remais and chapter by Spear and Hubbard. We then discuss how various controls (e.g., chemotherapy, snail control and sanitation) may be evaluated via the detailed model. We then demonstrate in a practical manner, using S. japonicum data from China, how field data may be incorporated to inform the practice of disease control. Finally, we present a new model structure that considers how heterogeneous populations are interconnected, which has particular relevance to understanding disease control and emergence in today's highly mobile world.
传染病传播建模的目的通常是了解导致传播持续存在的因素、感染过程的动态以及控制传播的最佳方法。因此，应该有很大的潜力利用数学模型来常规地规划和评估疾病控制计划。但实际上，有许多挑战使得疾病模型在这方面无法实际应用。一个挑战涉及模型的数学复杂性，这使得现场工作人员和卫生官员难以理解和使用它们。另一个挑战是，尽管模型具有数学复杂性，但它们通常没有足够的结构复杂性来考虑实践卫生官员通常考虑的许多特定于地点的流行病学和疾病控制细节。此外，大多数建模研究在解释如何将现场数据纳入模型以影响公共卫生决策方面都不够明确或具有典范性。在本章中，我们从血吸虫病传播的经典模型开始，并将其关键属性与 Remais 章节和 Spear 和 Hubbard 章节中介绍的更详细的日本血吸虫模型联系起来。然后，我们讨论了如何通过详细模型评估各种控制措施（例如化疗、钉螺控制和卫生）。然后，我们以一种实际的方式展示了如何利用来自中国的日本血吸虫数据来告知疾病控制实践。最后，我们提出了一种新的模型结构，该结构考虑了异质人群是如何相互关联的，这对于理解当今高度流动的世界中的疾病控制和出现具有特殊意义。
