prevalence {SimInf} | 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.
prevalence(model, formula, type = c("pop", "nop", "wnp"), node = NULL, as.is = FALSE)
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,
|
type |
The type of prevalence measure to calculate at each
time point in |
node |
Indices specifying the subset nodes to include in the
calculation of the prevalence. Default is |
as.is |
The default ( |
A data.frame
if as.is = FALSE
, 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, threads = 1) ## 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, type = "nop") ## Determine the proportion of infected individuals in each node ## at the time-points in 'tspan'. prevalence(result, I~S+I+R, type = "wnp") ## 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, type = "wnp")