Data for: Capturing complex interactions in disease ecology with simplicial sets
Silk, Matthew J.; Wilber, Mark Q.; Fefferman, Nina H. (2023), Data for: Capturing complex interactions in disease ecology with simplicial sets, Dryad, Dataset, https://doi.org/10.5061/dryad.ghx3ffbrw
Here we provide archived code for: Code for Capturing Complex Interactions in Disease Ecology with Simplicial Sets. Ecology Letters. The code provided can be used to generate the figures used in the manuscript as well as to generate appendix 3 in the supplementary materials. In the paper, we describe how higher-order network approaches can be applied in disease ecology research. We explain what simplicial sets are; why their use would be beneficial in different subject areas; where these areas are: social, transmission, movement/spatial and ecological networks; and when using them would help most in each context. To demonstrate their application, we develop a novel approach to identify how pathogens persist within a host population (see code for Appendix 3 in this repository). We also provide an overview of how to use simplicial sets, highlighting specific metrics, generative models and software. Finally, we synthesize key research questions simplicial sets will help us answer and highlight the methodological developments required.
Software code (R, Python, Julia) to generate the figures (1-4) and appendix 3 in Capturing Complex Interactions in Disease Ecology with Simplicial Sets
Air Force Office of Scientific Research, Award: FA9550-20-1-0275
National Institute of Food and Agriculture, Award: Hatch Project 1012932