# NOT RUN {
## Get the WHO TB burden data and the data dictionary
tb_burden <- get_tb_burden()
dict <- get_data_dict()
## Get a random sample of 9 countries
sample_countries <- sample(unique(tb_burden$country), 9)
## Plot incidence rates in these countries
plot_tb_burden(df = tb_burden, dict = dict, facet = "country", countries = sample_countries)
# }
# NOT RUN {
## Plot smoothed incidence rates in these countries
plot_tb_burden(
df = tb_burden, dict = dict, facet = "country", smooth = TRUE,
countries = sample_countries
)
## Use data caching to plot incidence rates with free y scales
plot_tb_burden(facet = "country", countries = sample_countries, scales = "free_y")
## Plot annual percentage change in incidence rates in selected countries
plot_tb_burden(
df = tb_burden, dict = dict, facet = "country", scales = "free_y",
countries = sample_countries, annual_change = TRUE, conf = NULL
)
## Find variables relating to mortality in the WHO dataset
search_data_dict(def = "mortality")
## Plot mortality rates (exc HIV) - without progress messages
plot_tb_burden(
metric = "e_mort_exc_tbhiv_100k", facet = "country",
countries = sample_countries, scales = "free_y"
)
# }
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