Hilker Frank M, Allen Linda J S, Bokil Vrushali A, Briggs Cheryl J, Feng Zhilan, Garrett Karen A, Gross Louis J, Hamelin Frédéric M, Jeger Michael J, Manore Carrie A, Power Alison G, Redinbaugh Margaret G, Rúa Megan A, Cunniffe Nik J
First author: Institute of Environmental Systems Research, School of Mathematics/Computer Science, Osnabrück University, 49069 Osnabrück, Germany; second author: Department of Mathematics and Statistics, Texas Tech University, Lubbock 79409; third author: Department of Mathematics, Oregon State University, Corvallis 97331; fourth author: Department of Ecology, Evolution and Marine Biology, University of California, Santa Barbara 93106; fifth author: Department of Mathematics, Purdue University, West Lafayette, IN 47907; sixth author: Plant Pathology Department, Institute for Sustainable Food Systems, and Emerging Pathogens Institute, University of Florida, Gainesville 32611; seventh author: National Institute for Mathematical and Biological Synthesis, University of Tennessee, Knoxville 37996; eighth author: IGEPP, Agrocampus Ouest, INRA, Université de Rennes 1, Université Bretagne-Loire, 35000 Rennes, France; ninth author: Centre for Environmental Policy, Imperial College London, Ascot SL5 7PY, United Kingdom; tenth author: Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, NM 87544; eleventh author: Department of Ecology and Evolutionary Biology, Cornell University, Ithaca, NY 14853; twelfth author: United States Department of Agriculture-Agricultural Research Service Corn, Soybean and Wheat Quality Research Unit and Department of Plant Pathology, Ohio State University, Wooster 44691; thirteenth author: Department of Biological Sciences, Wright State University, Dayton, OH 45435; and fourteenth author: Department of Plant Sciences, University of Cambridge, Cambridge CB2 3EA, United Kingdom.
Phytopathology. 2017 Oct;107(10):1095-1108. doi: 10.1094/PHYTO-03-17-0080-FI. Epub 2017 Aug 1.
Maize lethal necrosis (MLN) has emerged as a serious threat to food security in sub-Saharan Africa. MLN is caused by coinfection with two viruses, Maize chlorotic mottle virus and a potyvirus, often Sugarcane mosaic virus. To better understand the dynamics of MLN and to provide insight into disease management, we modeled the spread of the viruses causing MLN within and between growing seasons. The model allows for transmission via vectors, soil, and seed, as well as exogenous sources of infection. Following model parameterization, we predict how management affects disease prevalence and crop performance over multiple seasons. Resource-rich farmers with large holdings can achieve good control by combining clean seed and insect control. However, crop rotation is often required to effect full control. Resource-poor farmers with smaller holdings must rely on rotation and roguing, and achieve more limited control. For both types of farmer, unless management is synchronized over large areas, exogenous sources of infection can thwart control. As well as providing practical guidance, our modeling framework is potentially informative for other cropping systems in which coinfection has devastating effects. Our work also emphasizes how mathematical modeling can inform management of an emerging disease even when epidemiological information remains scanty. [Formula: see text] Copyright © 2017 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .
玉米致死坏死病（MLN）已成为撒哈拉以南非洲粮食安全的严重威胁。MLN由两种病毒共同感染引起，即玉米褪绿斑驳病毒和一种马铃薯Y病毒属病毒，通常是甘蔗花叶病毒。为了更好地了解MLN的动态并为疾病管理提供见解，我们对导致MLN的病毒在生长季节内和生长季节之间的传播进行了建模。该模型考虑了通过媒介、土壤和种子传播，以及外部感染源。在对模型进行参数化后，我们预测了管理措施如何在多个季节中影响疾病流行率和作物表现。拥有大片土地的资源丰富的农民可以通过结合使用清洁种子和控制昆虫来实现良好的防治效果。然而，通常需要进行作物轮作才能实现全面控制。拥有较小土地的资源匮乏的农民必须依靠轮作和拔除病株，控制效果较为有限。对于这两类农民来说，除非在大片区域同步实施管理措施，否则外部感染源可能会破坏防治工作。除了提供实际指导外，我们的建模框架可能对其他因共同感染而产生毁灭性影响的种植系统也具有参考价值。我们的工作还强调了即使在流行病学信息仍然匮乏的情况下，数学建模也可以为新兴疾病的管理提供依据。[公式：见正文] 版权所有© 2017作者。本文是一篇根据知识共享署名 - 非商业性使用 - 禁止演绎4.0国际许可协议发布的开放获取文章。
