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Modeling Effects of Temperature, Precipitation, and Vegetation on West Nile Virus Infection Rates

Organization(s):Institute for Global Environmental Strategies (IGES) GLOBE v-School
Country:United States of America
Student(s):Sadhana Kumar, Aarush Gupta, Evan Shepherd
Grade Level:Secondary School (grades 9-12, ages 14-18)
GLOBE Teacher:Cassie Soeffing
Contributors:Dr. Rusty Low, scientist, IGES Peder Nelson, scientist, OSU Dr. Erika Podest, scientist, NASA JPL Dr. Becky Boger, scientist Peer Mentor: Matteo Kimura
Report Type(s):International Virtual Science Symposium Report, Mission Mosquito Report
Protocols:Land Cover Classification, Mosquitoes
Presentation Video: View Video
Presentation Poster: View Document
Optional Badges:I am a Data Scientist, I make an Impact
Language(s):English
Date Submitted:02/14/2022
The West Nile Virus (WNV) is one of the most common vector-borne diseases in the United States, with approximately 2,500 cases reported in 2018. Previous research has primarily relied on hydrologic conditions to model WNV transmission and has been unable to find a link between WNV transmission and vegetation, precipitation, or temperature. Statistically analyzed data from the Centers of Disease Control and Prevention (CDC), Global Learning and Observation to Benefit the Environment (GLOBE), and the National Oceanic and Atmospheric Association (NOAA) finds the relationship between the number of WNV cases and three variables (precipitation, vegetation index, and temperature) in the United States, coming up with a comprehensive model for the nation from 2016 to 2019. Visualized vegetation data was extracted from the GLOBE API interface into an interactive ArcGIS dashboard. A significant relationship was found between precipitation and WNV cases in 2019 (p = 0.0001) using multiple linear regression and determined that there is a positive correlation between WNV cases and precipitation and a negative correlation with both vegetation index and temperature. The findings indicate that WNV transmission is affected by multiple confounding variables rather than a single environmental factor. Keywords: West Nile Virus, precipitation, temperature, vegetation index, statistical analysis


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