ArticlePhytopathology2019
Modeling Epidemics in Seed Systems and Landscapes To Guide Management Strategies: The Case of Sweet Potato in Northern Uganda.
Article in Phytopathology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Modelling plant disease spread via high-resolution human mobility networks.Journal of the Royal Society, Interface · 2026Article
- Article
- Translating virome analyses to support biosecurity, on-farm management, and crop breeding.Frontiers in plant science · 2023Review
- Modelling cassava production and pest management under biotic and abiotic constraints.Plant molecular biology · 2022Review
- "Breaking through the 40% adoption ceiling: Mind the seed system gaps." A perspective on seed systems research for development in One CGIAR.Outlook on agriculture · 2021Article
- Article
- Global Cropland Connectivity: A Risk Factor for Invasion and Saturation by Emerging Pathogens and Pests.Bioscience · 2020Article
- Applying optimal control theory to a spatial simulation model of sudden oak death: ongoing surveillance protects tanoak while conserving biodiversity.Journal of the Royal Society, Interface · 2020Article
- Detection, forecasting and control of infectious disease epidemics: modelling outbreaks in humans, animals and plants.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2019Article
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Seed systems are critical for deployment of improved varieties but also can serve as major conduits for the spread of seedborne pathogens. As in many other epidemic systems, epidemic risk in seed systems often depends on the structure of networks of trade, social interactions, and landscape connectivity. In a case study, we evaluated the structure of an informal sweet potato seed system in the Gulu region of northern Uganda for its vulnerability to the spread of emerging epidemics and its utility for disseminating improved varieties. Seed transaction data were collected by surveying vine sellers weekly during the 2014 growing season. We combined data from these observed seed transactions with estimated dispersal risk based on village-to-village proximity to create a multilayer network or "supranetwork." Both the inverse power law function and negative exponential function, common models for dispersal kernels, were evaluated in a sensitivity analysis/uncertainty quantification across a range of parameters chosen to represent spread based on proximity in the landscape. In a set of simulation experiments, we modeled the introduction of a novel pathogen and evaluated the influence of spread parameters on the selection of villages for surveillance and management. We found that the starting position in the network was critical for epidemic progress and final epidemic outcomes, largely driven by node out-degree. The efficacy of node centrality measures was evaluated for utility in identifying villages in the network to manage and limit disease spread. Node degree often performed as well as other, more complicated centrality measures for the networks where village-to-village spread was modeled by the inverse power law, whereas betweenness centrality was often more effective for negative exponential dispersal. This analysis framework can be applied to provide recommendations for a wide variety of seed systems.[Formula: see text] Copyright © 2019 The Author(s). This is an open access article distributed under the CC BY 4.0 International license.
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