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Risk factors associated with Rift Valley fever epidemics in South Africa in 2008-11.
Métras, Raphaëlle; Jewell, Chris; Porphyre, Thibaud; Thompson, Peter N; Pfeiffer, Dirk U; Collins, Lisa M; White, Richard G.
Afiliación
  • Métras R; 1] Veterinary Epidemiology, Economics and Public Health Group, Department of Production and Population Health, Royal Veterinary College, Hatfield, United Kingdom [2] Centre for the Mathematical Modelling of Infectious Diseases and Faculty of Epidemiology and Population Health, London School of Hygie
  • Jewell C; Institute of Fundamental Sciences, Massey University, New Zealand.
  • Porphyre T; Centre for Immunity, Infection and Evolution, University of Edinburgh, Ashworth Laboratories, Edinburgh, United Kingdom.
  • Thompson PN; Epidemiology Section, Department of Production Animal Studies, University of Pretoria, Onderstepoort, South Africa.
  • Pfeiffer DU; Veterinary Epidemiology, Economics and Public Health Group, Department of Production and Population Health, Royal Veterinary College, Hatfield, United Kingdom.
  • Collins LM; School of Life Sciences, University of Lincoln, United Kingdom.
  • White RG; 1] Centre for the Mathematical Modelling of Infectious Diseases and Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom [2] Tuberculosis Modelling Group, London School of Hygiene and Tropical Medicine, London, United Kingdom.
Sci Rep ; 5: 9492, 2015 Mar 25.
Article en En | MEDLINE | ID: mdl-25804974
ABSTRACT
Rift Valley fever (RVF) is a zoonotic and vector-borne disease, mainly present in Africa, which represents a threat to human health, animal health and production. South Africa has experienced three major RVF epidemics (1950-51, 1973-75 and 2008-11). Due to data scarcity, no previous study has quantified risk factors associated with RVF epidemics in animals in South Africa. Using the 2008-11 epidemic datasets, a retrospective longitudinal study was conducted to identify and quantify spatial and temporal environmental factors associated with RVF incidence. Cox regressions with a Besag model to account for the spatial effects were fitted to the data. Coefficients were estimated by Bayesian inference using integrated nested Laplace approximation. An increase in vegetation density was the most important risk factor until 2010. In 2010, increased temperature was the major risk factor. In 2011, after the large 2010 epidemic wave, these associations were reversed, potentially confounded by immunity in animals, probably resulting from earlier infection and vaccination. Both vegetation density and temperature should be considered together in the development of risk management strategies. However, the crucial need for improved access to data on population at risk, animal movements and vaccine use is highlighted to improve model predictions.
Asunto(s)

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Fiebre del Valle del Rift / Epidemias Tipo de estudio: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Humans País/Región como asunto: Africa Idioma: En Revista: Sci Rep Año: 2015 Tipo del documento: Article

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Fiebre del Valle del Rift / Epidemias Tipo de estudio: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Humans País/Región como asunto: Africa Idioma: En Revista: Sci Rep Año: 2015 Tipo del documento: Article