Extract prevalence from running a particle filter
# S4 method for SimInf_pfilter
prevalence(model, formula, level, index, format = c("data.frame", "matrix"))A data.frame if format = "data.frame", else
a matrix.
the SimInf_pfilter object to extract the
prevalence from.
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.
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.
indices specifying the subset of nodes to include
when extracting data. Default (index = NULL) is to
extract data from all nodes.
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.