proportion_cluster_size {superspreading} | R Documentation |
Estimate what proportion of new cases originated within a transmission event of a given size
Description
Calculates the proportion of new cases that originated with a transmission event of a given size. It can be useful to inform backwards contact tracing efforts, i.e. how many cases are associated with large clusters. Here we define a cluster to as a transmission of a primary case to at least one secondary case.
Usage
proportion_cluster_size(
R,
k,
cluster_size,
...,
offspring_dist,
format_prop = TRUE
)
Arguments
R |
A |
k |
A |
cluster_size |
A |
... |
dots not used, extra arguments supplied will cause a warning. |
offspring_dist |
An |
format_prop |
A |
Details
This function calculates the proportion of secondary cases that are caused by transmission events of a certain size. It does not calculate the proportion of transmission events that cause a cluster of secondary cases of a certain size. In other words it is the number of cases above a threshold divided by the total number of cases, not the number of transmission events above a certain threshold divided by the number of transmission events.
Value
A <data.frame>
with the value for the proportion of new cases
that are part of a transmission event above a threshold for a given value
of R and k.
Examples
R <- 2
k <- 0.1
cluster_size <- 10
proportion_cluster_size(R = R, k = k, cluster_size = cluster_size)
# example with a vector of k
k <- c(0.1, 0.2, 0.3, 0.4, 0.5)
proportion_cluster_size(R = R, k = k, cluster_size = cluster_size)
# example with a vector of cluster sizes
cluster_size <- c(5, 10, 25)
proportion_cluster_size(R = R, k = k, cluster_size = cluster_size)