Rift Valley Fever Epidemiology, Surveillance, and Control: What Have Models Contributed?

Métras Raphaëlle, Collins Lisa M., White Richard G., Alonso Silvia, Chevalier Véronique, Thuranira-McKeever Christine, Pfeiffer Dirk Udo. 2011. Rift Valley Fever Epidemiology, Surveillance, and Control: What Have Models Contributed?. Vector Borne and Zoonotic Diseases, 11 (6) : pp. 761-771.

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Abstract : Background: Rift Valley fever (RVF) is an emerging vector-borne zoonotic disease that represents a threat to human health, animal health, and livestock production, particularly in Africa. The epidemiology of RVF is not well understood, so that forecasting RVF outbreaks and carrying out efficient and timely control measures remains a challenge. Various epidemiological modeling tools have been used to increase knowledge on RVF epidemiology and to inform disease management policies. Aim: This narrative review gives an overview of modeling tools used to date to measure or model RVF risk in animals, and presents how they have contributed to increasing our understanding of RVF occurrence or informed RVF surveillance and control strategies. Methodology: Systematic literature searches were performed in PubMed and ISI Web of Knowledge. Additional research work was identified from other sources. Results: Literature was scarce. Research work was highly heterogeneous in methodology, level of complexity, geographic scale of approach, and geographical area of study. Gaps in knowledge and data were frequent, and uncertainty was not always explored. Spatial approaches were the most commonly utilized techniques and have been used at both local and continental scales, the latter leading to the implementation of an early warning system. Three articles using dynamic transmission models explored the potential of RVF endemicity. Risk factor studies identified water-related environmental risk factors associated with RVF occurrence in domestic livestock. Risk assessments identified importation of infected animals, contaminated products, or infected vectors as key risk pathways for the introduction of RVF virus into disease-free areas. Conclusions: Enhanced outbreak prediction and control and increased knowledge on RVF epidemiology would benefit from additional field data, continued development, and refinement of modeling techniques for exploring plausible disease transmission mechanisms and the impact of intervention strategies. (Résumé d'auteur)

Mots-clés Agrovoc : Virus de la fièvre de la vallée du Rift, Contrôle de maladies, Surveillance épidémiologique, Épidémiologie, Modèle de simulation, Modèle mathématique, Gestion du risque, Méthode statistique, Fièvre de la Vallée du Rift

Mots-clés géographiques Agrovoc : Afrique, Monde, Sénégal, Mauritanie, Cameroun, Togo, Bénin, Côte d'Ivoire, Burkina Faso, Nigéria, Arabie Saoudite, Kenya, Égypte, Yémen

Classification Agris : L73 - Animal diseases
U10 - Computer science, mathematics and statistics

Champ stratégique Cirad : Axe 4 (2005-2013) - Santé animale et maladies émergentes

Auteurs et affiliations

  • Métras Raphaëlle, Royal Veterinary College (GBR)
  • Collins Lisa M., Royal Veterinary College (GBR)
  • White Richard G., LSHTM (GBR)
  • Alonso Silvia, Royal Veterinary College (GBR)
  • Chevalier Véronique, CIRAD-ES-UPR AGIRs (FRA)
  • Thuranira-McKeever Christine, Royal Veterinary College (GBR)
  • Pfeiffer Dirk Udo, Royal Veterinary College (GBR)

Source : Cirad - Agritrop (

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