Title |
Modeling Virus Coinfection to Inform Management of Maize Lethal Necrosis in Kenya.
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Published in |
Phytopathology, August 2017
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DOI | 10.1094/phyto-03-17-0080-fi |
Pubmed ID | |
Authors |
Frank M Hilker, Linda J S Allen, Vrushali A Bokil, Cheryl J Briggs, Zhilan Feng, Karen A Garrett, Louis J Gross, Frédéric M Hamelin, Michael J Jeger, Carrie A Manore, Alison G Power, Margaret G Redinbaugh, Megan A Rúa, Nik J Cunniffe |
Abstract |
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 (MCMV) and a potyvirus, often sugarcane mosaic virus (SCMV). To better understand dynamics of MLN and to provide insight into disease management, we model the spread of the viruses causing MLN within and between growing seasons. The model allows for transmission via vectors, soil and seeds, as well as exogenous sources of infection. Following model parameterisation, 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. Crop rotation is often required to effect full control, however. 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 synchronised over large areas, exogenous sources of infection can thwart control. As well as providing practical guidance, our modelling framework is potentially informative for other cropping systems in which coinfection has devastating effects. Our work also emphasises how mathematical modelling can inform management of an emerging disease even when epidemiological information remains scanty. |
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Mendeley readers
Geographical breakdown
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Demographic breakdown
Readers by professional status | Count | As % |
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Researcher | 23 | 24% |
Student > Master | 19 | 20% |
Student > Ph. D. Student | 16 | 16% |
Student > Bachelor | 7 | 7% |
Professor | 4 | 4% |
Other | 13 | 13% |
Unknown | 15 | 15% |
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Mathematics | 7 | 7% |
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Social Sciences | 3 | 3% |
Other | 9 | 9% |
Unknown | 20 | 21% |