Tuberculosis data from the World Health Organization (WHO).

This function relies on getTBinR to source WHO tuberculosis (TB) data. It then curates this data - extracting the country, region, year, TB incidence, TB incidence rates (+ CI's), the proportion of cases with extra-pulmonary TB, and the proportion of cases with HIV (+ CI's). Data prior to 2000 is dropped.

tb_data(inc_floor = NULL, inc_rate_floor = NULL, ...)

Arguments

inc_floor	Numeric, defaults to NULL. What is the minimum incidence to keep in the data.
inc_rate_floor	Numeric, defaults to NULL. What is the minimum incidence rate (per 100,000) to keep in the data.
...	Additional arguments to pass to getTBinR::get_tb_burden.

Value

A dataframe containing curated TB data from the WHO.

See also

get_tb_burden

Examples

## Get the data
tb_data()
#> Loading data from: /tmp/RtmpzHlUlm/tb_burden.rds
#> Loading data from: /tmp/RtmpzHlUlm/mdr_tb.rds
#> Joining TB burden data and MDR TB data.
#> Getting additional dataset: Latent TB infection
#> Loading data from: /tmp/RtmpzHlUlm/latent_tb_infection.rds
#> Getting additional dataset: Notification
#> Loading data from: /tmp/RtmpzHlUlm/notification.rds
#> Getting additional dataset: Drug resistance surveillance
#> Loading data from: /tmp/RtmpzHlUlm/drug_resistance_surveillance.rds
#> Getting additional dataset: Non-routine HIV surveillance
#> Loading data from: /tmp/RtmpzHlUlm/non-routine_hiv_surveillance.rds
#> Getting additional dataset: Outcomes
#> Loading data from: /tmp/RtmpzHlUlm/outcomes.rds
#> Getting additional dataset: Budget
#> Loading data from: /tmp/RtmpzHlUlm/budget.rds
#> Getting additional dataset: Expenditure and utilisation
#> Loading data from: /tmp/RtmpzHlUlm/expenditure_and_utilisation.rds
#> Getting additional dataset: Policies and services
#> Loading data from: /tmp/RtmpzHlUlm/policies_and_services.rds
#> Getting additional dataset: Community engagement
#> Loading data from: /tmp/RtmpzHlUlm/community_engagement.rds
#> Getting additional dataset: Laboratories
#> Loading data from: /tmp/RtmpzHlUlm/laboratories.rds
#> Joining TB burden data and additional datasets.
#> # A tibble: 4,474 x 12
#>    country iso3  g_whoregion  year tb_cases tb_inc tb_inc_lo tb_inc_hi
#>    <chr>   <chr> <chr>       <int>    <int>  <dbl>     <dbl>     <dbl>
#>  1 Afghan… AFG   Eastern Me…  2000    39000    190       123       271
#>  2 Afghan… AFG   Eastern Me…  2001    41000    189       123       271
#>  3 Afghan… AFG   Eastern Me…  2002    43000    189       122       270
#>  4 Afghan… AFG   Eastern Me…  2003    45000    189       122       270
#>  5 Afghan… AFG   Eastern Me…  2004    47000    189       122       270
#>  6 Afghan… AFG   Eastern Me…  2005    48000    189       122       270
#>  7 Afghan… AFG   Eastern Me…  2006    50000    189       122       270
#>  8 Afghan… AFG   Eastern Me…  2007    51000    189       122       270
#>  9 Afghan… AFG   Eastern Me…  2008    52000    189       122       270
#> 10 Afghan… AFG   Eastern Me…  2009    54000    189       123       270
#> # … with 4,464 more rows, and 4 more variables: prop_tb_ep <dbl>,
#> #   prop_hiv <dbl>, prop_hiv_lo <dbl>, prop_hiv_hi <dbl>