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    Mapping the spatial distribution of the Japanese encephalitis vector, Culex tritaeniorhynchus Giles, 1901 (Diptera: Culicidae) within areas of Japanese encephalitis risk

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    12
    Author
    Longbottom, J; Browne, AJ; Pigott, DM; Sinka, ME; Golding, N; Hay, SI; Moyes, CL; Shearer, FM
    Date
    2017-03-16
    Source Title
    Parasites and Vectors
    Publisher
    BIOMED CENTRAL LTD
    University of Melbourne Author/s
    Golding, Nicholas; Shearer, Freya
    Affiliation
    School of BioSciences
    Melbourne School of Population and Global Health
    Metadata
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    Document Type
    Journal Article
    Citations
    Longbottom, J., Browne, A. J., Pigott, D. M., Sinka, M. E., Golding, N., Hay, S. I., Moyes, C. L. & Shearer, F. M. (2017). Mapping the spatial distribution of the Japanese encephalitis vector, Culex tritaeniorhynchus Giles, 1901 (Diptera: Culicidae) within areas of Japanese encephalitis risk. PARASITES & VECTORS, 10 (1), https://doi.org/10.1186/s13071-017-2086-8.
    Access Status
    Open Access
    URI
    http://hdl.handle.net/11343/259191
    DOI
    10.1186/s13071-017-2086-8
    Abstract
    BACKGROUND: Japanese encephalitis (JE) is one of the most significant aetiological agents of viral encephalitis in Asia. This medically important arbovirus is primarily spread from vertebrate hosts to humans by the mosquito vector Culex tritaeniorhynchus. Knowledge of the contemporary distribution of this vector species is lacking, and efforts to define areas of disease risk greatly depend on a thorough understanding of the variation in this mosquito's geographical distribution. RESULTS: We assembled a contemporary database of Cx. tritaeniorhynchus presence records within Japanese encephalitis risk areas from formal literature and other relevant resources, resulting in 1,045 geo-referenced, spatially and temporally unique presence records spanning from 1928 to 2014 (71.9% of records obtained between 2001 and 2014). These presence data were combined with a background dataset capturing sample bias in our presence dataset, along with environmental and socio-economic covariates, to inform a boosted regression tree model predicting environmental suitability for Cx. tritaeniorhynchus at each 5 × 5 km gridded cell within areas of JE risk. The resulting fine-scale map highlights areas of high environmental suitability for this species across India, Nepal and China that coincide with areas of high JE incidence, emphasising the role of this vector in disease transmission and the utility of the map generated. CONCLUSIONS: Our map contributes towards efforts determining the spatial heterogeneity in Cx. tritaeniorhynchus distribution within the limits of JE transmission. Specifically, this map can be used to inform vector control programs and can be used to identify key areas where the prevention of Cx. tritaeniorhynchus establishment should be a priority.

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