Skip to content

Latest commit

 

History

History
51 lines (41 loc) · 2.56 KB

README.md

File metadata and controls

51 lines (41 loc) · 2.56 KB
Raw

Disease Simulator

This is an agent-based model that simulates the spread and potential persistence of a disease in an animal population (potentially including humans).

The original idea was derived from my work on chronic wasting disease when I was a postdoctoral researcher at the University of Illinois, and the current R code (/R/old/simDeer.R) is complete and based on that scenario. I am currently rewriting the code in Python, with the intention of making it more generalizable. I may eventually rewrite the R code to make it cleaner as well.

If I get really ambitious, I may one day animate the simulation....

In the case of the original deer model each iteration of the model represents a single year. In the course of the year, the following events happen, by calling the following methods:

  • Initialize population: Population() (Population.__init__())
  • Plot initial distribution: Population.plot()

Iterative sequence begins here:

  • Disperse (young leave the mothers): Population.disperse()
  • Plot new distribution

TODO:

  • Calcualate home ranges: Populaton.calculate_ranges() [possibly private]
  • Plot ranges
  • Initialize soil matrix (distribution of infectious material in the environment: Soil() (Soil.__init__())
  • Soil Plot (Heat map of infectious material): Soil.plot()
  • Infect (allow new animals to become infected as a function of distance to infected animals and probability of disease spread): Population.infect()
  • Plot showing newly infected animals
  • Infect soil (allow infected animals to leave contaminants in the soil): Population.infect_soil()
  • Plot soil status
  • Migrate back to winter grounds: Population.migrate('winter')
  • Plot
  • Infect soil
  • Soil plot
  • Animal-to-animal infection
  • Soil-to-animal infection
  • Plot animals
  • Plot soil
  • Mortality: Some animals die as a function of sex, age and disease status (Population.die())
  • Plot
  • Subdivide map into discrete units
  • Local mortality: additional deaths as a function of local carrying capacity
  • Reproduction (babies are born): Population.reproduce()
  • Plot
  • Advance Time (animals age)
  • Diminish Infectious Material in Soil
  • Soil Plot

Finish the above, the combine into a single command allowing the model to run for an arbitrary number of iterations (with or without plots being output along the way). Initialize data summary tables and track:

  • Demographics
  • Disease Prevalence
  • Soil Matrices