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Application of geospatial technologies for understanding and predicting vector populations and vector‐borne disease incidence
Author(s) -
DeGroote John P.,
Larson Scott R.,
Zhang Yanli,
Sugumaran Ramanathan
Publication year - 2012
Publication title -
geography compass
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.587
H-Index - 65
ISSN - 1749-8198
DOI - 10.1111/gec3.12003
Subject(s) - geospatial analysis , vector (molecular biology) , data science , disease , geography , spatial epidemiology , transmission (telecommunications) , epidemiology , environmental health , risk analysis (engineering) , ecology , computer science , biology , cartography , medicine , pathology , biochemistry , gene , recombinant dna , telecommunications
Vector‐borne diseases inflict a heavy health burden. Numerous vector species have expanded their ranges while some vector‐borne diseases have emerged in new geographic areas or reemerged in former endemic areas, potentially due to global climate change. The continued health burden and the expansion in vector and vector‐borne disease ranges have led to an increased need for understanding and predicting in space and time the potential abundance and distribution of vectors and the transmission of vector‐borne diseases. Advances in computing technologies, increased spatial data availability, and greater understanding of ecological drivers have made it commonplace to attempt to understand and estimate, in time and space, vector populations and vector‐borne disease incidence. Although there have been great advances there are still limitations due to complex and varying ecologies and epidemiological contexts of vector‐borne diseases as well as data limitations. In this paper, we will provide an overview of and examine advances and limitations in the use of geospatial technologies for understanding and prediction of the drivers of vector populations and vector‐borne diseases.