The relationship between epidemiology and disease management is long-standing but sometimes tenuous. It may seem self-evident that improved understanding of epidemic processes will lead to more effective control practices but this remains a testable proposition rather than demonstrated reality. A wide range of models differing in mathematical sophistication and computational complexity has been proposed as a means of achieving a greater understanding of epidemiology and carrying this through to improved management. The potential exists to align these modeling approaches to evaluation of control practices and prediction of the consequent epidemic outcomes, but these have yet to make a major impact on practical disease management. For the immediate future simpler pragmatic approaches for analysis of disease progress, using nonlinear growth functions and/or integrated measures such as area under disease progress curves, will play a key role in informing tactical and strategic decisions on control treatments. These approaches have proved useful in describing control effectiveness and, in some cases, optimizing or changing control practices.

中文翻译：

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疾病进展分析是评估疾病管理实践的基础。

流行病学和疾病管理之间的关系是长期存在的，但有时是脆弱的。似乎不言而喻的是，对流行病过程的加深了解将导致更有效的控制措施，但这仍然是可检验的主张，而不是已证明的现实。已经提出了在数学复杂度和计算复杂度方面各不相同的各种模型，作为对流行病学有更深入了解并将其贯彻到改进管理的一种手段。有可能使这些建模方法与控制措施的评估和对随后流行病结果的预测相吻合，但这些方法尚未对实际疾病管理产生重大影响。对于近期更简单实用的疾病进展分析方法，使用非线性增长函数和/或综合措施（例如疾病进展曲线下的面积），将在为控制治疗提供战术和战略决策方面发挥关键作用。实践证明，这些方法对于描述控制效果以及在某些情况下优化或更改控制实践很有用。