title: Spatial Models for Prediction and Early Warning of Aedes aegypti Proliferation from Data on Climate Change and Variability in Cuba.
abstract: Climate variability, the primary expression of climate change, is one of the most important environmental problems affecting human health, particularly vector-borne diseases. Despite research efforts worldwide, there are few studies addressing the use of information on climate variability for prevention and early warning of vector-borne infectious diseases.
  
  
  
  Show the utility of climate information for vector surveillance by developing spatial models using an entomological indicator and information on predicted climate variability in Cuba to provide early warning of danger of increased risk of dengue transmission.
  
  
  
  An ecological study was carried out using retrospective and prospective analyses of time series combined with spatial statistics. Several entomological and climatic indicators were considered using complex Bultó indices -1 and -2. Moran's I spatial autocorrelation coefficient specified for a matrix of neighbors with a radius of 20 km, was used to identify the spatial structure. Spatial structure simulation was based on simultaneous autoregressive and conditional autoregressive models; agreement between predicted and observed values for number of Aedes aegypti foci was determined by the concordance index Di and skill factor Bi.
  
  
  
  Spatial and temporal distributions of populations of Aedes aegypti were obtained. Models for describing, simulating and predicting spatial patterns of Aedes aegypti populations associated with climate variability patterns were put forward. The ranges of climate variability affecting Aedes aegypti populations were identified. Forecast maps were generated for the municipal level.
  
  
  
  Using the Bultó indices of climate variability, it is possible to construct spatial models for predicting increased Aedes aegypti populations in Cuba. At 20 x 20 km resolution, the models are able to provide warning of potential changes in vector populations in rainy and dry seasons and by month, thus demonstrating the usefulness of climate information for epidemiological surveillance.
authors.affiliation: Climate Center, Meteorology Institute (CLIM), Havana, Cuba. paulo.ortiz@insmet.cu.
authors.forename: Paulo L
authors.initials: PL
authors.lastname: Ortiz
authors.forename: Alina
authors.initials: A
authors.lastname: Rivero
authors.forename: Yzenia
authors.initials: Y
authors.lastname: Linares
authors.forename: Alina
authors.initials: A
authors.lastname: Pérez
authors.forename: Juan R
authors.initials: JR
authors.lastname: Vázquez
mesh_terms: D000330:Aedes; D000818:Animals; D057231:Climate Change / Q000706:statistics & numerical data*; D003462:Cuba; D064308:Ecological Parameter Monitoring / Q000379:methods* / Q000706:statistics & numerical data; D005544:Forecasting; D006801:Humans; D007303:Insect Vectors; D008954:Models, Biological; D011158:Population Growth; D011159:Population Surveillance / Q000379:methods; D011446:Prospective Studies; D012189:Retrospective Studies; D013029:Space-Time Clustering