SandflyMap: leveraging spatial data on sand fly vector distribution for disease risk assessments

We feature SandflyMap (www.sandflymap.org), a new map service within VectorMap (www.vectormap.org) that allows free public online access to global sand fly, tick and mosquito collection records and habitat suitability models. Given the short home range of sand flies, combining remote sensing and col...

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Main Authors: Desmond H. Foley, Richard C. Wilkerson, L. Lynnette Dornak, David B. Pecor, Arpad S. Nyari, Leopoldo M. Rueda, Lewis S. Long, Jason H. Richardson
Format: Article
Language:English
Published: PAGEPress Publications 2012-09-01
Series:Geospatial Health
Subjects:
Online Access:http://www.geospatialhealth.net/index.php/gh/article/view/119
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author Desmond H. Foley
Richard C. Wilkerson
L. Lynnette Dornak
David B. Pecor
Arpad S. Nyari
Leopoldo M. Rueda
Lewis S. Long
Jason H. Richardson
author_facet Desmond H. Foley
Richard C. Wilkerson
L. Lynnette Dornak
David B. Pecor
Arpad S. Nyari
Leopoldo M. Rueda
Lewis S. Long
Jason H. Richardson
author_sort Desmond H. Foley
collection DOAJ
description We feature SandflyMap (www.sandflymap.org), a new map service within VectorMap (www.vectormap.org) that allows free public online access to global sand fly, tick and mosquito collection records and habitat suitability models. Given the short home range of sand flies, combining remote sensing and collection point data give a powerful insight into the environmental determinants of sand fly distribution. SandflyMap is aimed at medical entomologists, vector disease control workers, public health officials and health planners. Data are checked for geographical and taxonomic errors, and are comprised of vouchered specimen information, and both published and unpublished observation data. SandflyMap uses Microsoft Silverlight and ESRI’s ArcGIS Server 10 software platform to present disease vector data and relevant remote sensing layers in an online geographical information system format. Users can view the locations of past vector collections and the results of models that predict the geographic extent of individual species. Collection records are searchable and downloadable, and Excel collection forms with drop down lists, and Excel charts to country, are available for data contributors to map and quality control their data. SandflyMap makes accessible, and adds value to, the results of past sand fly collecting efforts. We detail the workflow for entering occurrence data from the literature to SandflyMap, using an example for sand flies from South America. We discuss the utility of SandflyMap as a focal point to increase collaboration and to explore the nexus between geography and vector-borne disease transmission.
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spelling doaj.art-47814ee4ac1444a8ac7ef2ca95dcc6ec2022-12-21T22:45:52ZengPAGEPress PublicationsGeospatial Health1827-19871970-70962012-09-016310.4081/gh.2012.119119SandflyMap: leveraging spatial data on sand fly vector distribution for disease risk assessmentsDesmond H. Foley0Richard C. Wilkerson1L. Lynnette Dornak2David B. Pecor3Arpad S. Nyari4Leopoldo M. Rueda5Lewis S. Long6Jason H. Richardson7Entomology Branch, Walter Reed Army Institute of Research, Silver Spring, MDEntomology Branch, Walter Reed Army Institute of Research, Silver Spring, MDEntomology Branch, Walter Reed Army Institute of Research, Silver Spring, MDEntomology Branch, Walter Reed Army Institute of Research, Silver Spring, MDEntomology Branch, Walter Reed Army Institute of Research, Silver Spring, MDEntomology Branch, Walter Reed Army Institute of Research, Silver Spring, MDEntomology Branch, Walter Reed Army Institute of Research, Silver Spring, MDEntomology Branch, Walter Reed Army Institute of Research, Silver Spring, MDWe feature SandflyMap (www.sandflymap.org), a new map service within VectorMap (www.vectormap.org) that allows free public online access to global sand fly, tick and mosquito collection records and habitat suitability models. Given the short home range of sand flies, combining remote sensing and collection point data give a powerful insight into the environmental determinants of sand fly distribution. SandflyMap is aimed at medical entomologists, vector disease control workers, public health officials and health planners. Data are checked for geographical and taxonomic errors, and are comprised of vouchered specimen information, and both published and unpublished observation data. SandflyMap uses Microsoft Silverlight and ESRI’s ArcGIS Server 10 software platform to present disease vector data and relevant remote sensing layers in an online geographical information system format. Users can view the locations of past vector collections and the results of models that predict the geographic extent of individual species. Collection records are searchable and downloadable, and Excel collection forms with drop down lists, and Excel charts to country, are available for data contributors to map and quality control their data. SandflyMap makes accessible, and adds value to, the results of past sand fly collecting efforts. We detail the workflow for entering occurrence data from the literature to SandflyMap, using an example for sand flies from South America. We discuss the utility of SandflyMap as a focal point to increase collaboration and to explore the nexus between geography and vector-borne disease transmission.http://www.geospatialhealth.net/index.php/gh/article/view/119database, distribution, SandflyMap, VectorMap, leishmaniasis, georeferencing, geographical information system.
spellingShingle Desmond H. Foley
Richard C. Wilkerson
L. Lynnette Dornak
David B. Pecor
Arpad S. Nyari
Leopoldo M. Rueda
Lewis S. Long
Jason H. Richardson
SandflyMap: leveraging spatial data on sand fly vector distribution for disease risk assessments
Geospatial Health
database, distribution, SandflyMap, VectorMap, leishmaniasis, georeferencing, geographical information system.
title SandflyMap: leveraging spatial data on sand fly vector distribution for disease risk assessments
title_full SandflyMap: leveraging spatial data on sand fly vector distribution for disease risk assessments
title_fullStr SandflyMap: leveraging spatial data on sand fly vector distribution for disease risk assessments
title_full_unstemmed SandflyMap: leveraging spatial data on sand fly vector distribution for disease risk assessments
title_short SandflyMap: leveraging spatial data on sand fly vector distribution for disease risk assessments
title_sort sandflymap leveraging spatial data on sand fly vector distribution for disease risk assessments
topic database, distribution, SandflyMap, VectorMap, leishmaniasis, georeferencing, geographical information system.
url http://www.geospatialhealth.net/index.php/gh/article/view/119
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