Description Usage Arguments Value Examples
Calculate the proportion of individuals with disease in the population, or the proportion of nodes with at least one diseased individual, or the proportion of individuals with disease in each node.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16  prevalence(
model,
formula,
level = 1,
index = NULL,
format = c("data.frame", "matrix")
)
## S4 method for signature 'SimInf_model,formula'
prevalence(
model,
formula,
level = 1,
index = NULL,
format = c("data.frame", "matrix")
)

model 
The 
formula 
A formula that specifies the compartments that
define the cases with a disease or that have a specific
characteristic (numerator), and the compartments that define
the entire population of interest (denominator). The
lefthandside of the formula defines the cases, and the
righthandside defines the population, for example,

level 
The level at which the prevalence is calculated at
each time point in 
index 
Indices specifying the subset of nodes to include in
the calculation of the prevalence. Default is 
format 
The default ( 
A data.frame
if format = "data.frame"
, else
a matrix.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27  ## Create an 'SIR' model with 6 nodes and initialize
## it to run over 10 days.
u0 < data.frame(S = 100:105, I = c(0, 1, 0, 2, 0, 3), R = rep(0, 6))
model < SIR(u0 = u0, tspan = 1:10, beta = 0.16, gamma = 0.077)
## Run the model to generate a single stochastic trajectory.
result < run(model)
## Determine the proportion of infected individuals (cases)
## in the population at the timepoints in 'tspan'.
prevalence(result, I ~ S + I + R)
## Identical result is obtained with the shorthand 'I~.'
prevalence(result, I ~ .)
## Determine the proportion of nodes with infected individuals at
## the timepoints in 'tspan'.
prevalence(result, I ~ S + I + R, level = 2)
## Determine the proportion of infected individuals in each node
## at the timepoints in 'tspan'.
prevalence(result, I ~ S + I + R, level = 3)
## Determine the proportion of infected individuals in each node
## at the timepoints in 'tspan' when the number of recovered is
## zero.
prevalence(result, I ~ S + I + R  R == 0, level = 3)

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