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Modelling coinfection to inform management of maize lethal necrosis in Kenya

last modified Jun 21, 2017 03:32 PM

A new study shows how mathematical modelling can be used to optimise control of maize lethal necrosis, a devastating disease greatly threatening food security in sub-Saharan Africa. Maize lethal necrosis first emerged in Kenya six years ago, and losses of up to 90% of yield have been reported from affected regions. Since most of Kenya’s maize comes from small and medium-sized farms, inexpensive ways of controlling the disease are crucially needed. The study shows that a combination of crop rotation, using virus-free 'clean seed' and roguing (removing plants showing symptoms) can potentially be effective in controlling MLN. However, maximum effectiveness requires a coordinated response amongst growers, since otherwise disease control would be thwarted by repeated re-invasion from disease in neighbouring uncontrolled fields.

The research arose from the Working Group on Multiscale Vectored Plant Viruses at the National Institute for Mathematical and Biological Synthesis (NIMBioS), which is at the University of Tennessee in Knoxville. This group met three times over the last two years, and included mathematicians, ecologists, plant pathologists and evolutionary biologists. The goal was developing novel mathematical methods for plant disease epidemiology. Maize lethal necrosis occurs when plants are co-infected by two viruses, maize chlorotic mottle virus and sugarcane mosaic virus. Co-infection is important for a range of disease, but is rarely modelled: tackling this problem required a new mathematical approach. Nik Cunniffe was a member of the Working Group, and was the last author on the paper, which is now available online in the American Phytopathological Society journal, Phytopathology.

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