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

التفاصيل البيبلوغرافية
العنوان: Identification of foot and mouth disease risk areas using a multi-criteria analysis approach.
المؤلفون: Santos DVD; Departamento de Saúde Animal, Secretaria de Defesa Agropecuária, Ministério da Agricultura Pecuária e Abastecimento, Brasília, Brazil.; Laboratório de Epidemiologia Veterinária, Faculdade de Veterinária, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil., Silva GSE; Laboratório de Epidemiologia Veterinária, Faculdade de Veterinária, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil., Weber EJ; Laboratório de Geoprocessamento, Centro de Ecologia, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil., Hasenack H; Laboratório de Geoprocessamento, Centro de Ecologia, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil., Groff FHS; Departamento de Defesa Agropecuária, Secretaria da Agricultura, Pecuária e Irrigação do Estado do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil., Todeschini B; Departamento de Saúde Animal, Secretaria de Defesa Agropecuária, Ministério da Agricultura Pecuária e Abastecimento, Brasília, Brazil.; Laboratório de Epidemiologia Veterinária, Faculdade de Veterinária, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil., Borba MR; Laboratório de Epidemiologia Veterinária, Faculdade de Veterinária, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil., Medeiros AAR; Laboratório de Epidemiologia Veterinária, Faculdade de Veterinária, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil.; Departamento de Defesa Agropecuária, Secretaria da Agricultura, Pecuária e Irrigação do Estado do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil., Leotti VB; Departamento de Estatística, Instituto de Matemática e Estatística, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil., Canal CW; Laboratório de Virologia, Faculdade de Veterinária, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil., Corbellini LG; Laboratório de Epidemiologia Veterinária, Faculdade de Veterinária, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil.
المصدر: PloS one [PLoS One] 2017 May 26; Vol. 12 (5), pp. e0178464. Date of Electronic Publication: 2017 May 26 (Print Publication: 2017).
نوع المنشور: Journal Article
اللغة: English
بيانات الدورية: Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE
أسماء مطبوعة: Original Publication: San Francisco, CA : Public Library of Science
مواضيع طبية MeSH: Foot-and-Mouth Disease/*epidemiology, Animals ; Brazil/epidemiology ; Cattle ; Disease Outbreaks ; Models, Theoretical ; Risk Factors
مستخلص: 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.
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تواريخ الأحداث: Date Created: 20170530 Date Completed: 20170918 Latest Revision: 20240326
رمز التحديث: 20240326
مُعرف محوري في PubMed: PMC5446179
DOI: 10.1371/journal.pone.0178464
PMID: 28552973
قاعدة البيانات: MEDLINE
الوصف
تدمد:1932-6203
DOI:10.1371/journal.pone.0178464