prevalence,SimInf_model-method | R Documentation |
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.
## S4 method for signature 'SimInf_model'
prevalence(model, formula, level, index, 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
left-hand-side of the formula defines the cases, and the
right-hand-side 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
when extracting data. Default ( |
format |
The default ( |
A data.frame
if format = "data.frame"
, else
a matrix.
## 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 time-points 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 time-points in 'tspan'.
prevalence(result, I ~ S + I + R, level = 2)
## Determine the proportion of infected individuals in each node
## at the time-points in 'tspan'.
prevalence(result, I ~ S + I + R, level = 3)
## Determine the proportion of infected individuals in each node
## at the time-points in 'tspan' when the number of recovered is
## zero.
prevalence(result, I ~ S + I + R | R == 0, level = 3)
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