Extract prevalence from running a particle filter

Usage

# S4 method for class 'SimInf_pfilter'
prevalence(model, formula, level, index, format = c("data.frame", "matrix"))

Arguments

model: the SimInf_pfilter object to extract the prevalence from.
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, I~S+I+R in a ‘SIR’ model (see ‘Examples’). The . (dot) is expanded to all compartments, for example, I~. is expanded to I~S+I+R in a ‘SIR’ model (see ‘Examples’). The formula can also contain a condition (indicated by |) for each node and time step to further control the population to include in the calculation, for example, I ~ . | R == 0 to calculate the prevalence when the recovered is zero in a ‘SIR’ model. The condition must evaluate to TRUE or FALSE in each node and time step. Please note, if the denominator is zero, the prevalence is NaN. Additionally, when level=3 (within-node prevalence) and the formula contains a condition that evaluates to FALSE, the prevalence is also NaN.
level: The level at which the prevalence is calculated at each time point in tspan. 1 (population prevalence): calculates the proportion of the individuals (cases) in the population. 2 (node prevalence): calculates the proportion of nodes with at least one case. 3 (within-node prevalence): calculates the proportion of cases within each node. Default is 1.
index: indices specifying the subset of nodes to include when extracting data. Default (index = NULL) is to extract data from all nodes.
format: The default (format = "data.frame") is to generate a data.frame with one row per time-step with the prevalence. Using format = "matrix" returns the result as a matrix.

Value

A data.frame if format = "data.frame", else a matrix.