Evidence map›Paper›PMID 28552973›Full record

ArticlePloS one2017

Identification of foot and mouth disease risk areas using a multi-criteria analysis approach.

Diego Viali Dos Santos, Gustavo Sousa E Silva, Eliseu José Weber, Heinrich Hasenack, Fernando Henrique Sautter Groff, Bernardo Todeschini, Mauro Riegert Borba, Antonio Augusto Rosa Medeiros, Vanessa Bielefeldt Leotti, Cláudio Wageck Canal and 1 more

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
2.9field-weighted citation impact, top 10% 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

11 citing papers in PubMed, 26 citations in OpenAlex.

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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

11 authors at 1 institution in 1 country.

Diego Viali Dos SantosDepartamento de Saúde Animal, Secretaria de Defesa Agropecuária, Ministério da Agricultura Pecuária e Abastecimento, Brasília, Brazil.ORCID http://orcid.org/0000-0001-8092-3064
Gustavo Sousa E SilvaLaboratório de Epidemiologia Veterinária, Faculdade de Veterinária, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil.
Eliseu José WeberLaboratório de Geoprocessamento, Centro de Ecologia, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil.
Heinrich HasenackLaboratório de Geoprocessamento, Centro de Ecologia, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil.
Fernando Henrique Sautter GroffDepartamento de Defesa Agropecuária, Secretaria da Agricultura, Pecuária e Irrigação do Estado do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil.
Bernardo TodeschiniDepartamento de Saúde Animal, Secretaria de Defesa Agropecuária, Ministério da Agricultura Pecuária e Abastecimento, Brasília, Brazil.
Mauro Riegert BorbaLaboratório de Epidemiologia Veterinária, Faculdade de Veterinária, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil.
Antonio Augusto Rosa MedeirosLaboratório de Epidemiologia Veterinária, Faculdade de Veterinária, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil.
Vanessa Bielefeldt LeottiDepartamento de Estatística, Instituto de Matemática e Estatística, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil.
Cláudio Wageck CanalLaboratório de Virologia, Faculdade de Veterinária, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil.
Luis Gustavo CorbelliniLaboratório de Epidemiologia Veterinária, Faculdade de Veterinária, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil.
Universidade Federal do Rio Grande do Sul · BR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Foot and mouth disease (FMD) is a highly infectious disease that affects cloven-hoofed livestock and wildlife. FMD has been a problem for decades, which has led to various measures to control, eradicate and prevent FMD by National Veterinary Services worldwide. Currently, the identification of areas that are at risk of FMD virus incursion and spread is a priority for FMD target surveillance after FMD is eradicated from a given country or region. In our study, a knowledge-driven spatial model was built to identify risk areas for FMD occurrence and to evaluate FMD surveillance performance in Rio Grande do Sul state, Brazil. For this purpose, multi-criteria decision analysis was used as a tool to seek multiple and conflicting criteria to determine a preferred course of action. Thirteen South American experts analyzed 18 variables associated with FMD introduction and dissemination pathways in Rio Grande do Sul. As a result, FMD higher risk areas were identified at international borders and in the central region of the state. The final model was expressed as a raster surface. The predictive ability of the model assessed by comparing, for each cell of the raster surface, the computed model risk scores with a binary variable representing the presence or absence of an FMD outbreak in that cell during the period 1985 to 2015. Current FMD surveillance performance was assessed, and recommendations were made to improve surveillance activities in critical areas.

Indexed as

AnimalsBrazilCattleDisease OutbreaksFoot-and-Mouth DiseaseModels, TheoreticalRisk Factors

Identifiers

PMID28552973
PMCPMC5446179
OpenAlexW2618863866

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.