Vector Host Niche Analysis to Predict Emergent Zika Outbreak Patterns

Authors: Austin Stanforth*, Ferris State University, Max Jacobo Moreno, Indiana University - Fairbanks School of Public Health
Topics: Medical and Health Geography, Hazards and Vulnerability, Geography and Urban Health
Keywords: GIS, Remote Sensing, Public Health, Disease, Vector, Dengue Fever, Zika
Session Type: Paper
Day: 4/10/2018
Start / End Time: 10:00 AM / 11:40 AM
Room: Lafayette, Marriott, River Tower Elevators, 41st Floor
Presentation File: No File Uploaded

Emergent diseases can be difficult to model with limited incident records. Incorporating historical data of a shared vector host may improve the speed and accuracy of addressing this Public Health need. Preliminary results are presented of statistical analysis which used location specific attributes of Dengue Fever incidence records to test for a viable method for predicting early Zika infection patterns. Using the Magdalena Rio watershed in Colombia as a test site, environmental variables derived from the MOderate Resolution Imaging Spectroradiometer (MODIS) and Tropical Rainfall Measuring Mission (TRMM) satellites were combined with population variables for statistical comparison against historically reported cases of Dengue Fever incidence records for their relationship to early Zika incidence records. Boosted Regression Trees were used to identify and model attributes of vector habits; including multiple temperature metrics, elevation, and vegetation composition. Results suggest levels of transmission risk are impacted by changing environmental characteristics in Aedes aegypti hosts for both viruses. Early analysis suggest shared virus host modeling can be applied to evaluate risk potential of emergent viruses by modeling for the vector’s environmental niche.

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