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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...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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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 |
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author | Godding, David Stutt, Richard O. J. H. Alicai, Titus Abidrabo, Phillip Okao-Okuja, Geoffrey Gilligan, Christopher A. |
author_facet | Godding, David Stutt, Richard O. J. H. Alicai, Titus Abidrabo, Phillip Okao-Okuja, Geoffrey Gilligan, Christopher A. |
author_sort | Godding, David |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-10400665 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-104006652023-08-05 Developing a predictive model for an emerging epidemic on cassava in sub-Saharan Africa Godding, David Stutt, Richard O. J. H. Alicai, Titus Abidrabo, Phillip Okao-Okuja, Geoffrey Gilligan, Christopher A. Sci Rep Article 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. Nature Publishing Group UK 2023-08-03 /pmc/articles/PMC10400665/ /pubmed/37537204 http://dx.doi.org/10.1038/s41598-023-38819-x Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Godding, David Stutt, Richard O. J. H. Alicai, Titus Abidrabo, Phillip Okao-Okuja, Geoffrey Gilligan, Christopher A. Developing a predictive model for an emerging epidemic on cassava in sub-Saharan Africa |
title | Developing a predictive model for an emerging epidemic on cassava in sub-Saharan Africa |
title_full | Developing a predictive model for an emerging epidemic on cassava in sub-Saharan Africa |
title_fullStr | Developing a predictive model for an emerging epidemic on cassava in sub-Saharan Africa |
title_full_unstemmed | Developing a predictive model for an emerging epidemic on cassava in sub-Saharan Africa |
title_short | Developing a predictive model for an emerging epidemic on cassava in sub-Saharan Africa |
title_sort | developing a predictive model for an emerging epidemic on cassava in sub-saharan africa |
topic | Article |
url | 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 |
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