Centre for Environmental Policy, Imperial College London, Silwood Park, Ascot SL5 7PY, United Kingdom.
Department of Plant Pathology, Ohio State University, Wooster, OH 44691.
Plant Dis. 2018 May;102(5):837-854. doi: 10.1094/PDIS-04-17-0612-FE. Epub 2018 Mar 30.
In recent years, mathematical modeling has increasingly been used to complement experimental and observational studies of biological phenomena across different levels of organization. In this article, we consider the contribution of mathematical models developed using a wide range of techniques and uses to the study of plant virus disease epidemics. Our emphasis is on the extent to which models have contributed to answering biological questions and indeed raised questions related to the epidemiology and ecology of plant viruses and the diseases caused. In some cases, models have led to direct applications in disease control, but arguably their impact is better judged through their influence in guiding research direction and improving understanding across the characteristic spatiotemporal scales of plant virus epidemics. We restrict this article to plant virus diseases for reasons of length and to maintain focus even though we recognize that modeling has played a major and perhaps greater part in the epidemiology of other plant pathogen taxa, including vector-borne bacteria and phytoplasmas.
近年来，数学建模越来越多地被用于补充不同组织层次的生物现象的实验和观察研究。在本文中，我们考虑了使用广泛的技术和用途开发的数学模型对植物病毒病流行的研究的贡献。我们强调的是，模型在多大程度上有助于回答生物学问题，实际上提出了与植物病毒的流行病学和生态学以及由此引起的疾病相关的问题。在某些情况下，模型已直接应用于疾病控制，但可以说，它们的影响通过指导研究方向和提高对植物病毒流行的特征时空尺度的理解来更好地判断。出于篇幅和保持重点的原因，本文仅限于植物病毒病，尽管我们认识到建模在包括媒介传播细菌和植原体在内的其他植物病原体类群的流行病学中发挥了主要甚至更大的作用。
