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. Note that if the denominator is zero, the
prevalence is 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.