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

Area of Science:

• Medical Entomology
• Geographic Information Systems (GIS)
• Remote Sensing

Background:

• Sand flies, ticks, and mosquitoes are significant vectors of diseases.
• Understanding their distribution is crucial for public health and disease control.
• Existing data on vector collections are often fragmented and inaccessible.

Purpose of the Study:

• To introduce SandflyMap, a novel online service providing access to global sand fly, tick, and mosquito collection records.
• To present habitat suitability models for disease vectors.
• To facilitate research and collaboration in medical entomology and public health.

Main Methods:

• Integration of remote sensing data with collection point data.
• Development of an online geographical information system (GIS) using ESRI's ArcGIS Server 10.
• Data validation for geographical and taxonomic accuracy, including vouchered specimens.
• Development of user-friendly data contribution tools (Excel forms and charts).

Main Results:

• SandflyMap provides free public online access to global vector collection records and habitat suitability models.
• The platform enables visualization of past vector collections and predicted species distribution.
• Searchable and downloadable collection records are available.
• A workflow for data entry from literature is detailed, with an example for South American sand flies.

Conclusions:

• SandflyMap enhances accessibility and value of existing vector collection data.
• The platform serves as a collaborative hub for researchers and public health professionals.
• It aids in exploring the relationship between geography and vector-borne disease transmission.