Plot an overview of TB Burden for Multiple Countries

This functions returns a dot plot for a given metric over a specified list of countries. If compare_to_region is specified then a given country will be compared to others in its region. This enables the user to rapidly understand trends in Tuberculosis over time and the progress towards global elimination.

plot_tb_burden_overview(
  df = NULL,
  dict = NULL,
  metric = "e_inc_100k",
  metric_label = NULL,
  countries = NULL,
  years = NULL,
  compare_to_region = FALSE,
  facet = NULL,
  annual_change = FALSE,
  trans = "identity",
  legend = "bottom",
  scales = "free_y",
  interactive = FALSE,
  download_data = TRUE,
  save = TRUE,
  viridis_palette = "viridis",
  viridis_direction = -1,
  viridis_end = 0.9,
  verbose = FALSE,
  ...
)

Arguments

df	Dataframe of TB burden data, as sourced by `get_tb_burden`. If not specified then will source the WHO TB burden data, either locally if available or directly from the WHO (if `download_data = TRUE`).
dict	A tibble of the data dictionary. See `get_data_dict` for details. If not supplied the function will attempt to load a saved version of the dictionary. If this fails and `download_data = TRUE` then the dictionary will be downloaded.
metric	Character string specifying the metric to plot
metric_label	Character string specifying the metric label to use.
countries	A character string specifying the countries to target.
years	Numeric vector of years. Defaults to `NULL` which includes all years in the data.
compare_to_region	Logical, defaults to `FALSE`. If `TRUE` all countries that share a region with those listed in `countries` will be plotted. Note that this will override settings for `facet`, unless it is set to "country".
facet	Character string, the name of the variable to facet by.
annual_change	Logical, defaults to `FALSE`. If `TRUE` then the percentage annual change is computed for the specified metric.
trans	A character string specifying the transform to use on the specified metric. Defaults to no transform ("identity"). Other options include log scaling ("log") and log base 10 scaling ("log10"). For a complete list of options see `ggplot2::continous_scale`.
legend	Character string, defaults to `"right"`. Position of the legend see `?ggplot2::theme` for defaults but known options are: `"none"`, `"top"`, `"right"` and `"bottom"`.
scales	Character string, see ?ggplot2::facet_wrap for details. Defaults to "fixed", alternatives are "free_y", "free_x", or "free".
interactive	Logical, defaults to `FALSE`. If `TRUE` then an interactive plot is returned.
download_data	Logical, defaults to `TRUE`. If not found locally should the data be downloaded from the specified URL?
save	Logical, should the data be saved for reuse during the current R session. Defaults to `TRUE`. If `TRUE` then the data is saved to the temporary directory specified by `tempdir`.
viridis_palette	Character string indicating the `viridis` colour palette to use. Defaults to "viridis". Options include "cividis", "magma", "inferno", "plasma", and "viridis". For additional details see `viridis_pal` for additional details.
viridis_direction	Numeric, indicating the direction for the colour palette (1 or -1), defaults to -1. See `scale_color_viridis` for additional details.
viridis_end	Numeric between 0 and 1, defaults to 0.9. The end point of the viridis scale to use. #' See `scale_color_viridis` for additional details.
verbose	Logical, defaults to `FALSE`. Should additional status and progress messages be displayed.
...	Additional arguments to pass to `get_tb_burden`.

Value

A dot plot of any numeric metric by country.

Examples


## Plot incidence rates over time for both the United Kingdom and Botswana
plot_tb_burden_overview(
  countries = c("United Kingdom", "Botswana"),
  compare_to_region = FALSE
)

## Plot percentage annual change in incidence rates.
plot_tb_burden_overview(
  countries = c("United Kingdom", "Botswana"),
  compare_to_region = FALSE, annual_change = TRUE
)

## Compare incidence rates in the UK and Botswana to incidence rates in their regions
plot_tb_burden_overview(
  countries = c("United Kingdom", "Botswana"),
  compare_to_region = TRUE
)

## Find variables relating to mortality in the WHO dataset
search_data_dict(def = "mortality")
#> # A tibble: 9 x 4
#>   variable_name      dataset  code_list definition                              
#>   <chr>              <chr>    <chr>     <chr>                                   
#> 1 e_mort_100k        Estimat… ""        Estimated mortality of TB cases (all fo…
#> 2 e_mort_100k_hi     Estimat… ""        Estimated mortality of TB cases (all fo…
#> 3 e_mort_100k_lo     Estimat… ""        Estimated mortality of TB cases (all fo…
#> 4 e_mort_exc_tbhiv_… Estimat… ""        Estimated mortality of TB cases (all fo…
#> 5 e_mort_exc_tbhiv_… Estimat… ""        Estimated mortality of TB cases (all fo…
#> 6 e_mort_exc_tbhiv_… Estimat… ""        Estimated mortality of TB cases (all fo…
#> 7 e_mort_tbhiv_100k  Estimat… ""        Estimated mortality of TB cases who are…
#> 8 e_mort_tbhiv_100k… Estimat… ""        Estimated mortality of TB cases who are…
#> 9 e_mort_tbhiv_100k… Estimat… ""        Estimated mortality of TB cases who are…

## Compare mortality rates (exc HIV) in the UK and Botswana to mortality rates in their regions
## Do not show progress messages
plot_tb_burden_overview(
  metric = "e_mort_exc_tbhiv_100k",
  countries = c("United Kingdom", "Botswana"),
  compare_to_region = TRUE, verbose = FALSE
)

Arguments

Value

See also

Examples