title: Assessing the future threat from vivax malaria in the United Kingdom using two markedly different modelling approaches.
abstract: BACKGROUND
  The world is facing an increased threat from new and emerging diseases, and there is concern that climate change will expand areas suitable for transmission of vector borne diseases. The likelihood of vivax malaria returning to the UK was explored using two markedly different modelling approaches. First, a simple temperature-dependent, process-based model of malaria growth transmitted by Anopheles atroparvus, the historical vector of malaria in the UK. Second, a statistical model using logistic-regression was used to predict historical malaria incidence between 1917 and 1918 in the UK, based on environmental and demographic data. Using findings from these models and saltmarsh distributions, future risk maps for malaria in the UK were produced based on UKCIP02 climate change scenarios.
  
  
  RESULTS
  The process-based model of climate suitability showed good correspondence with historical records of malaria cases. An analysis of the statistical models showed that mean temperature of the warmest month of the year was the major factor explaining the distribution of malaria, further supporting the use of the temperature-driven processed-based model. The risk maps indicate that large areas of central and southern England could support malaria transmission today and could increase in extent in the future. Confidence in these predictions is increased by the concordance between the processed-based and statistical models.
  
  
  CONCLUSIONS
  Although the future climate in the UK is favourable for the transmission of vivax malaria, the future risk of locally transmitted malaria is considered low because of low vector biting rates and the low probability of vectors feeding on a malaria-infected person.
authors.affiliation: Disease Control and Vector Biology Unit, London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT, UK. Steve.Lindsay@lshtm.ac.uk
authors.forename: Steven W
authors.initials: SW
authors.lastname: Lindsay
authors.forename: David G
authors.initials: DG
authors.lastname: Hole
authors.forename: Robert A
authors.initials: RA
authors.lastname: Hutchinson
authors.forename: Shane A
authors.initials: SA
authors.lastname: Richards
authors.forename: Stephen G
authors.initials: SG
authors.lastname: Willis
mesh_terms: D000818:Animals; D000852:Anopheles / Q000469:parasitology / Q000502:physiology; D002980:Climate; D017753:Ecosystem; D005544:Forecasting; D007303:Insect Vectors / Q000469:parasitology / Q000502:physiology; D016015:Logistic Models; D016780:Malaria, Vivax / Q000453:epidemiology / Q000469:parasitology / Q000635:transmission*; D008954:Models, Biological; D015233:Models, Statistical; D010966:Plasmodium vivax; D012306:Risk; D013696:Temperature; D006113:United Kingdom / Q000453:epidemiology