ArticleScientific reports2023
Developing a predictive model for an emerging epidemic on cassava in sub-Saharan Africa.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Modelling plant disease spread via high-resolution human mobility networks.Journal of the Royal Society, Interface · 2026Article
- Predicting the cross-continental spread of the cassava brown streak disease epidemic in sub-Saharan Africa.Scientific reports · 2026Article
- Article
- Optimizing crop clustering to minimize pathogen invasion in agriculture.Scientific reports · 2025Article
- Where to refine spatial data to improve accuracy in crop disease modelling: an analytical approach with examples for cassava.Royal Society open science · 2025Article
- Integration of temperature-driven population model and pest monitoring data to estimate initial conditions and timing of first field invasion: application to the cassava whitefly,Journal of the Royal Society, Interface · 2025Article
- Optimal control prevents itself from eradicating stochastic disease epidemics.PLoS computational biology · 2025Article
- Predicting the effect of landscape structure on epidemic invasion using an analytical estimate for infection rate.Royal Society open science · 2025Article
- Developing a spatio-temporal model for banana bunchy top disease: leveraging remote sensing and survey data.Frontiers in plant science · 2025Article
- Article
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Authors and funding
6 authors.
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Abstract
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.
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