Douglas A. Augusto

The paper introduces a dynamic alert system using a Zoonotic Alert Index to improve disease outbreak detection in wildlife, validated with yellow fever data achieving over 94% accuracy.

The paper integrates deep-learning models with species distribution models to improve animal classification in Brazilian fauna, achieving higher accuracy than standalone models.

SISS-Geo is a collaborative platform for monitoring wildlife health in Brazil, integrating citizen science, laboratory diagnostics, and computational tools to address challenges in disease surveillance and risk prediction.