Evidence map›Paper›PMID 31951877›Full record

ArticleEpidemics2020

Small world in the real world: Long distance dispersal governs epidemic dynamics in agricultural landscapes.

Giovanni Strona, Claudio Castellano, Simone Fattorini, Luigi Ponti, Andrew Paul Gutierrez, Pieter S A Beck

Open access · goldAbstract read
In one paragraph

Article in Epidemics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
4.9field-weighted citation impact, top 6% of its field
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

4 citing papers in PubMed, 19 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Spatial Bayesian Modeling Applied to the Surveys ofFrontiers in plant science · 2020
    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

6 authors at 6 institutions in 4 countries.

Giovanni StronaResearch Centre for Ecological Change, University of Helsinki, P.O. Box 4, FI-00014, Finland; European Commission, Joint Research Centre (JRC), Ispra, Italy. Electronic address: giovanni.strona@helsinki.fi.
Claudio CastellanoIstituto dei Sistemi Complessi (ISC-CNR), Via dei Taurini 19, 00185 Rome, Italy.
Simone FattoriniDepartment of Life, Health and Environmental Sciences, University of L'Aquila, Via Vetoio, Coppito, 67010, L'Aquila, Italy.
Luigi PontiAgenzia nazionale per le nuove tecnologie, l'Energia e lo sviluppo economico sostenibile (ENEA), Centro Ricerche Casaccia, Via Anguillarese 301, 00123, Roma, Italy; Center for the Analysis of Sustainable Agricultural Systems (CASAS Global), 37 Arlington Ave., Kensington, CA, 94707-1035, USA.
Andrew Paul GutierrezCenter for the Analysis of Sustainable Agricultural Systems (CASAS Global), 37 Arlington Ave., Kensington, CA, 94707-1035, USA; Division of Ecosystem Science, College of Natural Resources, University of California, Berkeley, CA, 94720-3114, USA.
Pieter S A BeckEuropean Commission, Joint Research Centre (JRC), Ispra, Italy. Electronic address: pieter.beck@ec.europa.eu.
CACI International (United States) · USEuropean Commission · BEInstitute for Complex Systems · ITNational Agency for New Technologies, Energy and Sustainable Economic Development · ITUniversity of Helsinki · FIUniversity of L'Aquila · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Outbreaks of a plant disease in a landscape can be meaningfully modelled using networks with nodes representing individual crop-fields, and edges representing potential infection pathways between them. Their spatial structure, which resembles that of a regular lattice, makes such networks fairly robust against epidemics. Yet, it is well-known how the addition of a few shortcuts can turn robust regular lattices into vulnerable 'small world' networks. Although the relevance of this phenomenon has been shown theoretically for networks with nodes corresponding to individual host plants, its real-world implications at a larger scale (i.e. in networks with nodes representing crop fields or other plantations) remain elusive. Focusing on realistic spatial networks connecting olive orchards in Andalusia (Southern Spain), the world's leading olive producer, we show how even very small probabilities of long distance dispersal of infectious vectors result in a small-world effect that dramatically exacerbates a hypothetical outbreak of a disease targeting olive trees (loosely modelled on known epidemiological information on the bacterium Xylella fastidiosa, an important emerging threat for European agriculture). More specifically, we found that the probability of long distance vector dispersal has a disproportionately larger effect on epidemic dynamics compared to pathogen's intrinsic infectivity, increasing total infected area by up to one order of magnitude (in the absence of quarantine). Furthermore, even a very small probability of long distance dispersal increased the effort needed to halt a hypothetical outbreak through quarantine by about 50% in respect to scenarios modelling local/short distance pathogen's dispersal only. This highlights how identifying (and disrupting) long distance dispersal processes may be more efficacious to contain a plant disease epidemic than surveillance and intervention concentrated on local scale transmission processes.

Indexed as

MonocultureOliveOutbreakQuarantineVector-borne diseaseXylella fastidiosa

Identifiers

PMID31951877
PMCPMC7086151
OpenAlexW3000418637

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.