Summarise R0 estimates across samples

Summarise R0 estimates across samples

summarise_end_r0(sims, group_var = c("event_size", "event_duration"))

Arguments

sims	A data.table from scenario_analysis.
group_var	Character vector indicating the groups to show. Defaults to event_duration and event_size

Value

A dataframe of R0 estimates for each scenario

Examples

## Code
summarise_end_r0
#> function (sims, group_var = c("event_size", "event_duration")) 
#> {
#>     time <- NULL
#>     R0 <- NULL
#>     median_R0 <- NULL
#>     lower_R0 <- NULL
#>     upper_R0 <- NULL
#>     sample <- NULL
#>     scenario <- NULL
#>     date_confirmation_str <- NULL
#>     restricted_scenarios <- sims %>% dplyr::group_by(sample, 
#>         scenario) %>% dplyr::filter(time == max(time)) %>% dplyr::group_by(.dots = group_var) %>% 
#>         dplyr::summarise(median_R0 = stats::median(R0, na.rm = TRUE), 
#>             lower_R0 = stats::quantile(R0, probs = 0.05, na.rm = TRUE), 
#>             upper_R0 = stats::quantile(R0, probs = 0.95, na.rm = TRUE), 
#>             samples = dplyr::n()) %>% dplyr::ungroup() %>% dplyr::mutate_at(.vars = c("median_R0", 
#>         "lower_R0", "upper_R0"), ~round(., 1)) %>% dplyr::mutate(R0 = paste0(lower_R0, 
#>         " - ", upper_R0))
#> }
#> <bytecode: 0x55a6b2fbb820>
#> <environment: namespace:WuhanSeedingVsTransmission>