Developing a predictive model for an emerging epidemic on cassava in sub-Saharan Africa.
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
03 08 2023
03 08 2023
Historique:
received:
05
07
2022
accepted:
15
07
2023
medline:
7
8
2023
pubmed:
4
8
2023
entrez:
3
8
2023
Statut:
epublish
Résumé
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.
Identifiants
pubmed: 37537204
doi: 10.1038/s41598-023-38819-x
pii: 10.1038/s41598-023-38819-x
pmc: PMC10400665
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
12603Subventions
Organisme : Bill & Melinda Gates Foundation
ID : INV-010472
Pays : United States
Informations de copyright
© 2023. Springer Nature Limited.
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