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Published on: November 29, 2024
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Spatial risks of Orthoebolavirus spillover vary based on outbreak type
Mekala Sundaram1, Patrick R Stephens2
1Savannah River Ecology Laboratory, University of Georgia, Athens, USA; Department of Infectious Diseases and Center for Precision One Health, University of Georgia, Athens, USA.
Summary
Frugivore richness and Ficus habitat suitability are key predictors for Orthoebolavirus outbreaks in sub-Saharan Africa. Different factors influence different outbreak types, necessitating comprehensive models for future spillover prediction.
Area of Science:
- Epidemiology
- Ecology
- Veterinary Medicine
Background:
- Orthoebolaviruses are emerging infectious pathogens primarily found in sub-Saharan Africa.
- Predictive models for Orthoebolavirus outbreaks are limited by uncertainties in spread mechanisms and data scarcity.
Purpose of the Study:
- To develop and test a risk map for Orthoebolavirus outbreaks.
- To explore frugivory and other factors influencing Orthoebolavirus spread.
- To apply statistical methods for analyzing small datasets to understand outbreak drivers.
Main Methods:
- Ensemble machine learning logistic regression with repeated cross-validation was employed.
- Statistical methods were adapted for analysis of small datasets.
- Factors influencing different outbreak classes (human vs. epizootic, viral species) were explored.
Main Results:
- Frugivore richness (AUC=0.95) and Ficus habitat suitability (AUC=0.94) showed the highest predictive power for Orthoebolavirus outbreaks.
- Ficus distribution was an important predictor for all outbreak types.
- Frugivore richness better predicted epizootic than human outbreaks, while hunting activity was a poor predictor overall.
Conclusions:
- Different drivers significantly influence distinct classes of Orthoebolavirus outbreaks.
- Comprehensive models incorporating diverse factors are essential for predicting future spillover events.
- Understanding specific drivers is crucial for targeted prevention and control strategies.
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