Evidence map›Paper›PMID 30785374›Full record

ArticlePhytopathology2019

Modeling Epidemics in Seed Systems and Landscapes To Guide Management Strategies: The Case of Sweet Potato in Northern Uganda.

K F Andersen, C E Buddenhagen, P Rachkara, R Gibson, S Kalule, D Phillips, K A Garrett

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Review
  5. Article
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  8. Article
  9. 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 · 2019
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

K F AndersenPlant Pathology Department, University of Florida, Gainesville, FL 32611-0680, U.S.A.ORCID http://orcid.org/0000-0003-1812-2009
C E BuddenhagenPlant Pathology Department, University of Florida, Gainesville, FL 32611-0680, U.S.A.
P RachkaraDepartment of Rural Development and Agribusiness, Gulu University, Gulu, Uganda.
R GibsonNatural Resource Institute, University of Greenwich, Greenwich, United Kingdom.
S KaluleDepartment of Rural Development and Agribusiness, Gulu University, Gulu, Uganda.
D PhillipsNatural Resource Institute, University of Greenwich, Greenwich, United Kingdom.
K A GarrettPlant Pathology Department, University of Florida, Gainesville, FL 32611-0680, U.S.A.ORCID http://orcid.org/0000-0002-6578-1616

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

EpidemicsIpomoea batatasPlant DiseasesSeedsUgandadisease control and pest managementecology and epidemiologypostharvest pathology and mycotoxinstechniquesvirology

Identifiers

PMID30785374
PMCPMC7779973

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.