EpiModel (version 0.25)

epiDCM: Deterministic Compartmental SI-SIS-SIR Models

Description

This function solves a deterministic model of an infectious disease with random mixing in the population.

Usage

epiDCM(type, s.num, i.num, r.num = 0, beta, cont, nu = 0,
    b = 0, ms = 0, mi = 0, mr = 0, dt, new.mod = NULL,
    print.mod = FALSE, verbose = FALSE, ...)

Arguments

type

model type (choice of 'SI', 'SIR', or 'SIS')

s.num

number of initial susceptible in population

i.num

number of initial infected in population

r.num

number of initial recovered in population

beta

probability of infection per contact

cont

average number of contacts per person per unit time

nu

average rate of recovery (1/duration of disease)

b

birth rate

ms

mortality rate for susceptibles

mi

mortality rate for infecteds

mr

mortality rate for recovered

dt

either scalar or vector of timesteps for model

new.mod

if not NULL, insert a new model definition

print.mod

extract and print the current model from the function

verbose

print progress

...

additional arguments to pass to model

See Also

plotDCM

Examples

# SI model
out <- epiDCM(type='SI', s.num=500, i.num=1, beta=0.2, cont=0.25, dt=500)
par(mar=c(3.5,3,1,1), mgp=c(2,1,0))
plotDCM(out, c('s.num', 'i.num'), leg='full')

# SIR model
out <- epiDCM(type='SIR', s.num=500, i.num=1, r.num=0,
              beta=0.2, cont=0.25, nu=1/50, dt=500)
plotDCM(out, c('s.num', 'i.num', 'r.num'), leg='full')

# SIS model
out <- epiDCM(type='SIS', s.num=500, i.num=1, r.num=0,
              beta=0.2, cont=0.25, nu=1/50, dt=500)
plotDCM(out, c('s.num', 'i.num'), leg='full')

# SIR model with vital dynamics
out <- epiDCM(type='SIR', s.num=1000, i.num=1, r.num=0,
              beta=0.2, cont=5, nu=1/3,
              b=1/90, ms=1/100, mi=1/35, mr=1/100, dt=500)
plotDCM(out, c('s.num', 'i.num', 'r.num'), leg='full')

# SIS model with sensitivity parameter for contact rate
out <- epiDCM(type='SIS', s.num=500, i.num=1, r.num=0,
              beta=0.2, cont=seq(0.05,0.5,0.05),
              nu=1/50, dt=500, verbose=TRUE)
plotDCM(out, 's.num', leg='lim', alpha=0.6)