Our research takes aim at a collective global health mission: to achieve a truly predictive framework enabling the mitigation and preemption of future infectious diseases for the global good.

Machine Learning | Macroecology Of Infectious Diseases | Amphibian Disease Ecology


Machine Learning to Predict Zoonotic Disease

Why do the majority of human infectious diseases originate from wildlife? Aims of this research area are to identify intrinsic characteristics of wild species (e.g., life history, ecological, physiological) signaling their potential to be future reservoirs of zoonotic diseases (human diseases with animal origins); to identify traits of pathogenic microorganisms and their vectors that best predict their potential to facilitate disease; to bring into focus the environmental factors and interactions that trigger pathogen spillover or support large disease outbreaks. Rather than focusing on particular pathogens or host species, we apply machine learning approaches to globally comprehensive databases spanning all known parasites and pathogens of animals and humans.

 

The goal of this research program is to generate actionable predictions that will mitigate global infectious disease burden for wildlife and humans.

 

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Macroecology of Infectious Disease

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Links to relevant resources: Link 1, Link 2, Link 3

 

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Amphibian Disease Ecology

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Links to relevant resources: Link 1, Link 2, Link 3

 

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