A risk index model for predicting eastern equine encephalitis virus transmission to horses in Florida.
- Journal Article
- Alphavirus
- Arboviruses
- Diagnosis
- Disease
- Disease control
- Disease Prevalence
- Disease Surveillance
- Disease Transmission
- Encephalitis
- Encephalomyelitis
- Epidemiology
- Equine Health
- Geographical Differences
- Horses
- Infectious Disease
- Mosquito-borne Diseases
- Predictive Model
- Public Health
- Vector-borne disease
- Veterinary Medicine
Summary
The research article discusses the creation of a GIS-based model that is able to predict areas where Eastern Equine Encephalitis Virus (EEEV) could be transmitted to horses in Florida.
Objective
This study aimed to create an accurate predictive model that quantifies EEEV transmission risk to horses in Florida. The model can aid in the surveillance of EEEV and guide prevention efforts.
Methods
- The team developed a risk index model using GIS (Geographic Information System), a computer system used for capturing, storing, checking, and displaying data related to positions on Earth’s surface.
- The model evaluates the risk of EEEV transmission at individual raster cells, a type of pixel with a value. The risk index is graded on a continuous scale, from 0 to 1, and is calculated based on local habitat features and the surrounding land cover types associated with EEEV transmission.
- To validate the model, researchers cross-referenced the approximated risk areas with known cases of EEEV transmission in horses.
Results
- The researchers found that the model effectively predicted the areas of EEEV transmission broadly across Florida. It was especially efficient in predicting cases in the Panhandle, North, and Central regions of the state.
- The South region of Florida had fewer cases; hence the model was less accurate in this area.
- Regardless of regional differences, the model was deemed useful in quantifying EEEV risk at both a regional and more localized scale.
- The model’s results were subsequently used to create predictive maps, which are aimed to assist with guiding surveillance and prevention of EEEV by county mosquito control districts.
Conclusion
Through this study, the team successfully created a risk index model that can predict EEEV transmission risk to horses in Florida. Despite regional differences, the model proved to be a valuable tool for assessing EEEV risk. The predictive maps produced as a result of the model can now be used to guide EEEV surveillance and prevention efforts.
Cite This Article
Publication
Researcher Affiliations
- Department of Global Health, University of South Florida, 4202 E Fowler Ave, Tampa, FL 33620.
- School of Geosciences, University of South Florida, 4202 E Fowler Ave, Tampa, FL 33620.
- Department of Global Health, University of South Florida, 4202 E Fowler Ave, Tampa, FL 33620.
- Department of Global Health, University of South Florida, 4202 E Fowler Ave, Tampa, FL 33620.
Grant Funding
- R01 AI049724 / NIAID NIH HHS
- R56 AI101072 / NIAID NIH HHS
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Citations
This article has been cited 5 times.- Barrantes Murillo DF, Piche-Ovares M, Gamboa-Solano JC, Romero LM, Soto-Garita C, Alfaro-Alarcón A, Corrales-Aguilar E. Serological Positivity against Selected Flaviviruses and Alphaviruses in Free-Ranging Bats and Birds from Costa Rica Evidence Exposure to Arboviruses Seldom Reported Locally in Humans. Viruses 2022 Jan 6;14(1).
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