title: Rift Valley fever epidemiology, surveillance, and control: what have models contributed?
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.
  
  
  OBJECTIVE
  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.
  
  
  METHODS
  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.
authors.affiliation: Veterinary Epidemiology and Public Health Group, Department of Veterinary Clinical Sciences, Royal Veterinary College, Hatfield, Hertfordshire, United Kingdom.
authors.forename: Raphaëlle
authors.initials: R
authors.lastname: Métras
authors.forename: Lisa M
authors.initials: LM
authors.lastname: Collins
authors.forename: Richard G
authors.initials: RG
authors.lastname: White
authors.forename: Silvia
authors.initials: S
authors.lastname: Alonso
authors.forename: Véronique
authors.initials: V
authors.lastname: Chevalier
authors.forename: Christine
authors.initials: C
authors.lastname: Thuranira-McKeever
authors.forename: Dirk U
authors.initials: DU
authors.lastname: Pfeiffer
mesh_terms: D014943:Global Health; D006801:Humans; D008954:Models, Biological; D011159:Population Surveillance; D012295:Rift Valley Fever / Q000453:epidemiology* / Q000517:prevention & control*; D018570:Risk Assessment