SUMMARY.md

Summary

• Simple deterministic models
  • SIR model
    • Python using SciPy
    • R using deSolve
    • R using odin
    • Julia
    • Octave
    • Scilab
    • C++
    • xppaut
    • VFGEN
    • Javascript
    • Javascript using Observable
  • SEIR model
    • Julia
    • R using deSolve
  • SIS model
    • Javascript using Observable
  • Scaling model
    • Julia
    • Python
    • R using deSolve
• Simple stochastic models
  • Continuous time SIR
    • R
    • R using GillespieSSA
    • R using Rcpp
    • Julia
  • Discrete time SIR
    • R using odin
    • R using POMP
    • R using LibBi
    • Python
    • Julia
  • Discrete time SEIRD
    • R using odin
• Final size of an epidemic
  • Exact recursive expressions
    • Original Matlab code
    • Julia
    • Octave
    • Scilab
    • R
• Non-exponential passage times
  • Discrete Erlang SEIR model
    • Julia
    • R
• Host-vector models
  • One host, one vector
    • Julia
  • N hosts, one vector
    • Julia
  • N hosts, M vectors
    • Julia
• Macroparasite models
  • May and Anderson 1978 model
    • Julia
    • R using deSolve
• Time-varying parameters
  • Seasonally forced deterministic model
    • R
    • Javascript using Observable
  • Semiparametric SIR model
    • Julia
    • R using pomp
• Metapopulation models
  • Deterministic SEIR
    • R using odin
  • SIRS dynamics in a large population of households
    • Julia
• Network models
  • An edge based SIR model on a configuration network
    • R
    • Javascript using Observable
  • An individual based model of pneumococcal transmission
    • R
  • An SIR model in London boroughs
    • R
• Phylodynamic models
  • Simple coalescent model
    • R
• Applications
  • Acute HIV infection
    • R
  • A model of HIV with two risk groups
    • R
  • A deterministic SEIR model of Ebola
    • Python using PyGOM
    • Python using SciPy
  • A stochastic, seasonal, discrete-time model of rotavirus
    • R using POMP
• Keeling and Rohani 2008
  • Program 2.1
    • Original C
    • Original Fortran
    • Original Python
    • Original Matlab/Octave
  • Program 2.6: SEIR
    • R using deSolve
    • Julia
  • Program 3.1: SIS with risk groups
    • R using deSolve
    • Julia
  • Program 3.2: SIS with m risk groups
    • R using deSolve
  • Program 3.4: Age structured SEIR
    • R using deSolve
  • Program 4.4: Multi-host SEIR
    • R using deSolve
• Bjornstad 2018
  • Chapter 1: Introduction
    • Original R code
  • Chapter 2: SIR
    • Original R code
  • Chapter 3: R0
    • Original R code
  • Chapter 4: FoI and age-dependent incidence
    • Original R code
  • Chapter 5: Seasonality
    • Original R code
• Appendices
  • Style guide for notebooks