EVALUATION AND EXPANSION OF A GEOGRAPHIC INFORMATION SYSTEM (GIS) DEGREE DAY MODEL TO PREDICT RIFT VALLEY FEVER VIRUS RISK IN NORTH AMERICA
Arthropod-Borne Animal Diseases Research
2013 Annual Report
1a.Objectives (from AD-416):
The objective of this cooperative research project is to conduct geo-spatial analysis of the primary climate and habitat factors that will influence the establishment of Rift Valley fever in the continental United States. A preliminary GIS model already exists; and we will expand this model to the 14 states deemed to be at the highest levels of RVF risk through pathways analysis, and create an online database where users can assess risk in areas and over time periods of specific interest.
1b.Approach (from AD-416):
We will update the model with new laboratory data (provided by outside collaborators) on the temperature-based transmission risk of possible U.S. vectors. If we can establish an accurate and robust enough data source, we will attempt to calibrate the temperature-based model with field data from Kenya. We will add at least one new layer to the risk assessment representing vector habitat. The combination of climate data, habitat data, and livestock density will enable predictions of maximum risk of RVF transmission and establishment in the US. We will create a database of transmission risk data that can be queried for risk analyses at specific locations or times.
This final report summarizes the work done at the University of Wyoming. The agreement was to design a spatially explicit GIS-based model that identifies the temporal and spatial patterns which determine risk of establishment of Rift Valley fever virus (RVFV) in the United States. Furthermore, a web portal was created for information dissemination. The model can now incorporate the most recently released weather data and model temperature-based risk across the United States in near real-time. The model works on three sources of data: (1) using interpolated temperature produced by NOAA for the US at a 0.5 x 0.5 degree resolution; (2) using city- and town-based data from over 2,800 weather stations that report on a daily basis, and; (3) using the short-term weather forecast data produced by NOAA. This data is used to produce a functional web-based platform that shows the daily risk for disease transmission of arthropod-borne illness, such as West Nile virus and RVFV in the lower 48 states. This agreement resulted in 5 publications and numerous presentations.