Summarise TB burden metrics by region, globally, and for custom groupings. For variables with uncertainty represented by confidence intervals bootstrapping can be used (assuming a normal distribution) to include this in any estimated summary measures. Currently two statistics are supported; the mean (with 95% confidence intervals) and the median (with 95% interquartile range), rates and proportions.

summarise_tb_burden(df = NULL, dict = NULL, metric = "e_inc_num",
  metric_label = NULL, conf = c("_lo", "_hi"), years = NULL,
  samples = 1000, countries = NULL, compare_to_region = FALSE,
  compare_to_world = TRUE, custom_compare = NULL,
  compare_all_regions = TRUE, stat = "rate", denom = "e_pop_num",
  rate_scale = 1e+05, truncate_at_zero = TRUE, annual_change = FALSE,
  download_data = TRUE, save = TRUE, verbose = TRUE, ...)

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.

conf

Character vector specifying the name variations to use to specify the upper and lower confidence intervals. Defaults to NULL for which no confidence intervals are used. Used by annual_change.

years

Numeric vector of years. Defaults to NULL which includes all years in the data.

samples

Numeric, the number of samples to use to generate confidence intervals (only used when conf are present)

countries

A character string specifying the countries to target.

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".

compare_to_world

Logical, defaults to TRUE. Should a comparison be made to the metric of interests global value.

custom_compare

Logical, defaults to NULL. A named list of custom countries.

compare_all_regions

Logical, defaults to TRUE. Should all regions be compared.

stat

Character string, defaults to "rate". The statistic to use to summarise the metric, currently "mean", "median", "rate" and "prop" are supported. Note "mean" and "median" do not recompute the supplied country levels values but can be used to summarise the distribution of region or global metrics. "prop" and"rate" compute the overall incidence rate for a given grouping (i.e the sum of the metric divided by the sum of the denominator).

denom

Character string defaulting to e_pop_num (country level population). If stat is set to rate or prop then this is the parameter to use as the denominator.

rate_scale

Numeric defaults to 100,000. The scaling to use for rates. If stat is to set to prop then this defaults to 1.

truncate_at_zero

Logical, defaults to TRUE. Should lower bounds be truncated at zero?

annual_change

Logical, defaults to FALSE. If TRUE then the percentage annual change is computed for the specified metric.

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.

verbose

Logical, defaults to TRUE. Should additional status and progress messages be displayed.

...

Additional arguments to pass to get_tb_burden.

Value

A tibble containing summarised values (with 95 stratified by area and year.

Examples

## Get the most recent year of data tb_burden <- get_tb_burden()
#> Loading data from: /tmp/RtmpA3cD0E/tb_burden.rds
#> Loading data from: /tmp/RtmpA3cD0E/mdr_tb.rds
#> Joining TB burden data and MDR TB data.
most_recent_year <- max(tb_burden$year) ## Get summary of the e_mdr_pct_rr_new cases summarise_tb_burden(metric = "e_mdr_pct_rr_new", years = most_recent_year, stat = "mean", samples = 100, compare_all_regions = TRUE, compare_to_world = TRUE, verbose = TRUE)
#> Loading data from: /tmp/RtmpA3cD0E/tb_burden.rds
#> Loading data from: /tmp/RtmpA3cD0E/mdr_tb.rds
#> Joining TB burden data and MDR TB data.
#> Loading data from: /tmp/RtmpA3cD0E/dictionary.rds
#> 1 results found for your variable search for e_mdr_pct_rr_new
#> Loading data from: /tmp/RtmpA3cD0E/tb_burden.rds
#> Loading data from: /tmp/RtmpA3cD0E/mdr_tb.rds
#> Joining TB burden data and MDR TB data.
#> Loading data from: /tmp/RtmpA3cD0E/dictionary.rds
#> 1 results found for your variable search for e_mdr_pct_rr_new
#> Filtering to use only data from: 2018
#> Confidence intervals were not found using your specified conf, so defaulting to estimating #> only based on the point estimate.
#> # A tibble: 7 x 5 #> area year e_mdr_pct_rr_new e_mdr_pct_rr_new_… e_mdr_pct_rr_new_… #> <fct> <int> <dbl> <dbl> <dbl> #> 1 Africa 2018 79.8 51.9 108. #> 2 Americas 2018 71.4 41.4 101. #> 3 Eastern Mediterr… 2018 79.6 39.2 120. #> 4 Europe 2018 83.3 45.8 121. #> 5 Global 2018 78.5 41.1 116. #> 6 South-East Asia 2018 96.4 79.7 113. #> 7 Western Pacific 2018 72.8 24.6 121.
if (FALSE) { ## Get median (with 95% IQR) of the case fatality rate for regions and the world ## Boostrapping uncertainty in country measures summarise_tb_burden(metric = "cfr", years = most_recent_year, samples = 100, stat = "median", compare_all_regions = TRUE, compare_to_world = TRUE, verbose = FALSE) ## Get summary data for the UK, Europe and the world ## Bootstrapping CI's summarise_tb_burden(metric = "e_inc_num", samples = 100, stat = "median", countries = "United Kingdom", compare_to_world = TRUE, compare_to_region = TRUE, verbose = FALSE) ## Get an overview of incidence rates regionally and globally compared to the UK summarise_tb_burden(metric = "e_inc_num", stat = "rate", countries = "United Kingdom", compare_to_world = TRUE, compare_to_region = TRUE, verbose = FALSE) }