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The Influence of New Surveillance Data on Predictive Species Distribution Modeling of Aedes aegypti and Aedes albopictus in the United States

1
Department of Environmental Toxicology, Texas Tech University, Lubbock, TX, 79416, USA
2
Department of Geography, Texas Tech University, Lubbock, TX, 79409, USA
*
Author to whom correspondence should be addressed.
Insects 2019, 10(11), 400; https://doi.org/10.3390/insects10110400
Received: 28 August 2019 / Revised: 18 October 2019 / Accepted: 1 November 2019 / Published: 12 November 2019
(This article belongs to the Special Issue Vectors and Vector-borne Diseases)
The recent emergence or reemergence of various vector-borne diseases makes the knowledge of disease vectors’ presence and distribution of paramount concern for protecting national human and animal health. While several studies have modeled Aedes aegypti or Aedes albopictus distributions in the past five years, studies at a large scale can miss the complexities that contribute to a species’ distribution. Many localities in the United States have lacked or had sporadic surveillance conducted for these two species. To address these gaps in the current knowledge of Ae. aegypti and Ae. albopictus distributions in the United States, surveillance was focused on areas in Texas at the margins of their known ranges and in localities that had little or no surveillance conducted in the past. This information was used with a global database of occurrence records to create a predictive model of these two species’ distributions in the United States. Additionally, the surveillance data from Texas was used to determine the influence of new data from the margins of a species’ known range on predicted species’ suitability maps. This information is critical in determining where to focus resources for the future and continued surveillance for these two species of medical concern. View Full-Text
Keywords: Aedes aegypti; Aedes albopictus; MaxEnt; species distribution modeling; mosquitoes Aedes aegypti; Aedes albopictus; MaxEnt; species distribution modeling; mosquitoes
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Tiffin, H.S.; Peper, S.T.; Wilson-Fallon, A.N.; Haydett, K.M.; Cao, G.; Presley, S.M. The Influence of New Surveillance Data on Predictive Species Distribution Modeling of Aedes aegypti and Aedes albopictus in the United States. Insects 2019, 10, 400.

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