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Developing a predictive model for an emerging epidemic on cassava in sub-Saharan Africa

The agricultural productivity of smallholder farmers in sub-Saharan Africa (SSA) is severely constrained by pests and pathogens, impacting economic stability and food security. An epidemic of cassava brown streak disease, causing significant yield loss, is spreading rapidly from Uganda into surround...

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Detalles Bibliográficos
Autores principales: Godding, David, Stutt, Richard O. J. H., Alicai, Titus, Abidrabo, Phillip, Okao-Okuja, Geoffrey, Gilligan, Christopher A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10400665/
https://www.ncbi.nlm.nih.gov/pubmed/37537204
http://dx.doi.org/10.1038/s41598-023-38819-x
Descripción
Sumario:The agricultural productivity of smallholder farmers in sub-Saharan Africa (SSA) is severely constrained by pests and pathogens, impacting economic stability and food security. An epidemic of cassava brown streak disease, causing significant yield loss, is spreading rapidly from Uganda into surrounding countries. Based on sparse surveillance data, the epidemic front is reported to be as far west as central DRC, the world’s highest per capita consumer, and as far south as Zambia. Future spread threatens production in West Africa including Nigeria, the world’s largest producer of cassava. Using innovative methods we develop, parameterise and validate a landscape-scale, stochastic epidemic model capturing the spread of the disease throughout Uganda. The model incorporates real-world management interventions and can be readily extended to make predictions for all 32 major cassava producing countries of SSA, with relevant data, and lays the foundations for a tool capable of informing policy decisions at a national and regional scale.