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A model for the assessment of bluetongue virus serotype 1 persistence in Spain

Author

Listed:
  • Cecilia Aguilar-Vega
  • Eduardo Fernández-Carrión
  • Javier Lucientes
  • José Manuel Sánchez-Vizcaíno

Abstract

Bluetongue virus (BTV) is an arbovirus of ruminants that has been circulating in Europe continuously for more than two decades and has become endemic in some countries such as Spain. Spain is ideal for BTV epidemiological studies since BTV outbreaks from different sources and serotypes have occurred continuously there since 2000; BTV-1 has been reported there from 2007 to 2017. Here we develop a model for BTV-1 endemic scenario to estimate the risk of an area becoming endemic, as well as to identify the most influential factors for BTV-1 persistence. We created abundance maps at 1-km2 spatial resolution for the main vectors in Spain, Culicoides imicola and Obsoletus and Pulicaris complexes, by combining environmental satellite data with occurrence models and a random forest machine learning algorithm. The endemic model included vector abundance and host-related variables (farm density). The three most relevant variables in the endemic model were the abundance of C. imicola and Obsoletus complex and density of goat farms (AUC 0.86); this model suggests that BTV-1 is more likely to become endemic in central and southwestern regions of Spain. It only requires host- and vector-related variables to identify areas at greater risk of becoming endemic for bluetongue. Our results highlight the importance of suitable Culicoides spp. prediction maps for bluetongue epidemiological studies and decision-making about control and eradication measures.

Suggested Citation

  • Cecilia Aguilar-Vega & Eduardo Fernández-Carrión & Javier Lucientes & José Manuel Sánchez-Vizcaíno, 2020. "A model for the assessment of bluetongue virus serotype 1 persistence in Spain," PLOS ONE, Public Library of Science, vol. 15(4), pages 1-22, April.
    • Handle: RePEc:plo:pone00:0232534
    DOI: 10.1371/journal.pone.0232534
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    References listed on IDEAS

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    1. Archer, Kellie J. & Kimes, Ryan V., 2008. "Empirical characterization of random forest variable importance measures," Computational Statistics & Data Analysis, Elsevier, vol. 52(4), pages 2249-2260, January.
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