add: how to estimate the probability of a large outbreak?

from @adamkucharski

``` r
# how to estimate the probability of a large outbreak?

# Get libraries
library(superspreading)
library(epiparameter)

# Load parameters
sars <- epidist_db(disease = "SARS",epi_dist = "offspring_distribution",single_epidist=T)
#> Using Lloyd-Smith J, Schreiber S, Kopp P, Getz W (2005). "Superspreading and
#> the effect of individual variation on disease emergence." _Nature_.
#> doi:10.1038/nature04153 ..
#> To retrieve the short citation use the 'get_citation' function
sars_params <- get_parameters(sars)
sars_params
#> mean dispersion
#> 1.63 0.16

# Estimate probability of large outbreak with 5 independent imported cases
probability_epidemic(
R = sars_params[["mean"]],
k = sars_params[["dispersion"]],
num_init_infect = 5
)
#> [1] 0.4722681
```

^{Created on 2024-01-09 with [reprex v2.0.2](https://reprex.tidyverse.org)}

No file or test is named. Start by reviewing the supplied R reprex and the repository's existing how-to guides, using the shown superspreading and epiparameter calls as the entry point; done means a reproducible guide demonstrates estimating the probability of a large outbreak with imported cases.

Written by the indexing model from the issue text.