Ryser Marc D, Gravitt Patti E, Myers Evan R
Department of Surgery, Division of Advanced Oncologic and GI Surgery, Duke University School of Medicine, Durham, NC, USA; Department of Mathematics, Duke University, Durham, NC, USA.
Department of Global Health, Milken Institute School of Public Health, George Washington University, Washington, DC, USA.
Papillomavirus Res. 2017 Jun;3:46-49. doi: 10.1016/j.pvr.2017.01.004. Epub 2017 Feb 4.
Health economic modeling has become an invaluable methodology for the design and evaluation of clinical and public health interventions against the human papillomavirus (HPV) and associated diseases. At the same time, relatively little attention has been paid to a different yet complementary class of models, namely that of mechanistic mathematical models. The primary focus of mechanistic mathematical models is to better understand the intricate biologic mechanisms and dynamics of disease. Inspired by a long and successful history of mechanistic modeling in other biomedical fields, we highlight several areas of HPV research where mechanistic models have the potential to advance the field. We argue that by building quantitative bridges between biologic mechanism and population level data, mechanistic mathematical models provide a unique platform to enable collaborations between experimentalists who collect data at different physical scales of the HPV infection process. Through such collaborations, mechanistic mathematical models can accelerate and enhance the investigation of HPV and related diseases.
健康经济模型已成为设计和评估针对人乳头瘤病毒（HPV）及相关疾病的临床和公共卫生干预措施的一种极有价值的方法。与此同时，相对较少受到关注的是另一类不同但互补的模型，即机制数学模型。机制数学模型的主要重点是更好地理解疾病复杂的生物学机制和动态变化。受其他生物医学领域长期且成功的机制建模历史的启发，我们强调了HPV研究的几个领域，在这些领域中机制模型有推动该领域发展的潜力。我们认为，通过在生物学机制和人群水平数据之间建立定量桥梁，机制数学模型提供了一个独特的平台，能够促进在HPV感染过程不同物理尺度上收集数据的实验人员之间的合作。通过这种合作，机制数学模型可以加速并加强对HPV及相关疾病的研究。
