title: A quantitative risk assessment approach for mosquito-borne diseases: malaria re-emergence in southern France.
abstract: BACKGROUND
  The Camargue region is a former malaria endemic area, where potential Anopheles vectors are still abundant. Considering the importation of Plasmodium due to the high number of imported malaria cases in France, the aim of this article was to make some predictions regarding the risk of malaria re-emergence in the Camargue.
  
  
  METHODS
  Receptivity (vectorial capacity) and infectivity (vector susceptibility) were inferred using an innovative probabilistic approach and considering both Plasmodium falciparum and Plasmodium vivax. Each parameter of receptivity (human biting rate, anthropophily, length of trophogonic cycle, survival rate, length of sporogonic cycle) and infectivity were estimated based on field survey, bibliographic data and expert knowledge and fitted with probability distributions taking into account the variability and the uncertainty of the estimation. Spatial and temporal variations of the parameters were determined using environmental factors derived from satellite imagery, meteorological data and entomological field data. The entomological risk (receptivity/infectivity) was calculated using 10,000 different randomly selected sets of values extracted from the probability distributions. The result was mapped in the Camargue area. Finally, vulnerability (number of malaria imported cases) was inferred using data collected in regional hospitals.
  
  
  RESULTS
  The entomological risk presented large spatial, temporal and Plasmodium species-dependent variations. The sensitivity analysis showed that susceptibility, survival rate and human biting rate were the three most influential parameters for entomological risk. Assessment of vulnerability showed that among the imported cases in the region, only very few were imported in at-risk areas.
  
  
  CONCLUSIONS
  The current risk of malaria re-emergence seems negligible due to the very low number of imported Plasmodium. This model demonstrated its efficiency for mosquito-borne diseases risk assessment.
authors.affiliation: Institut de Recherche pour le Développement, UR016, Montpellier cedex 5, France. nicolas.poncon@agriculture.gouv.fr
authors.forename: Nicolas
authors.initials: N
authors.lastname: Ponçon
authors.forename: Annelise
authors.initials: A
authors.lastname: Tran
authors.forename: Céline
authors.initials: C
authors.lastname: Toty
authors.forename: Adrian Jf
authors.initials: AJ
authors.lastname: Luty
authors.forename: Didier
authors.initials: D
authors.lastname: Fontenille
mesh_terms: D000818:Animals; D004196:Disease Outbreaks / Q000706:statistics & numerical data*; D005602:France / Q000453:epidemiology; D006801:Humans; D007299:Insect Bites and Stings / Q000453:epidemiology; D007303:Insect Vectors / Q000469:parasitology*; D008288:Malaria / Q000453:epidemiology* / Q000635:transmission; D010963:Plasmodium falciparum / Q000254:growth & development; D010966:Plasmodium vivax / Q000254:growth & development; D018570:Risk Assessment / Q000379:methods*