R code supporting: Detecting disease progression from animal movement using hidden Markov models
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Kim, Dongmin
kimx3725@umn.edu
kimx3725@umn.edu
Abstract
This repository contains R code supporting: Detecting disease progression from animal movement using hidden Markov models (HMMs). We provide a series of .Rmd files that can be compiled to form a transferable workflow for detecting infection from animal movement. We demonstrate the flexibility of (H)HMMs in capturing different disease scenarios and a workflow for appropriate model selection. Our approach has the potential to improve wildlife disease surveillance, inform management of vulnerable populations, and enhance understanding of disease dynamics.
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See Readme file.
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NSF INTERN grant
Smithsonian Institution Fellowship Program (SIFP)
Doctoral Dissertation Fellowship
Minnesota Agricultural Experimental Station
Sahara Conservation and the Environment Agency - Abu Dhabi
Smithsonian Institution Fellowship Program (SIFP)
Doctoral Dissertation Fellowship
Minnesota Agricultural Experimental Station
Sahara Conservation and the Environment Agency - Abu Dhabi
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Kim, Dongmin; Michelot, Théo; Mertes, Katherine; Stabach, Jared A; Fieberg, John R. (2025). R code supporting: Detecting disease progression from animal movement using hidden Markov models. Retrieved from the Data Repository for the University of Minnesota (DRUM), https://hdl.handle.net/11299/277126.
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