replace code from interpretation lines for explicit credible intervals

https://github.com/epiverse-trace/tutorials-middle/blob/e61911f8a231a2005bfaaefe0a55b86dd3f07cdd/episodes/quantify-transmissibility.Rmd#L459-L467

```{r}
#| echo: false
estimates_summary <- estimates$summary %>% as_tibble() %>% filter(!stringr::str_detect(measure,"change")) %>% unnest(numeric_estimate)
```

Interpretation

```
+ From the summary of our analysis we see that the expected change in reports is
`r estimates$summary %>% as_tibble() %>% filter(stringr::str_detect(measure,"change")) %>% pull(estimate)`
with the estimated new infections of
`r estimates_summary %>% filter(stringr::str_detect(measure,"infections")) %>% dplyr::select(median) %>% pull()`
with 90% credible interval of
`r estimates_summary %>% filter(stringr::str_detect(measure,"infections")) %>% dplyr::select(lower_90) %>% pull()` to `r estimates_summary %>% filter(stringr::str_detect(measure,"infections")) %>% dplyr::select(upper_90) %>% pull()`.

+ The effective reproduction number $R_t$ estimate (on the last date of the data),
or the number of new infections caused by one infectious individual, on average, is
`r estimates_summary %>% filter(stringr::str_detect(measure,"reproduction")) %>% dplyr::select(median) %>% pull()`,
with a 90% credible interval of
`r estimates_summary %>% filter(stringr::str_detect(measure,"reproduction")) %>% dplyr::select(lower_90) %>% pull()` to `r estimates_summary %>% filter(stringr::str_detect(measure,"reproduction")) %>% dplyr::select(upper_90) %>% pull()`.

+ The exponential growth rate of case reports is `r summary(estimates)$estimate[summary(estimates)$measure=="Rate of growth"]`.

+ The doubling time (the time taken for case reports to double) is `r summary(estimates)$estimate[summary(estimates)$measure=="Doubling/halving time (days)"]`.
```