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@seabbs
Last active January 9, 2018 14:20
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Explore 20 countries with highest TB incidence
# install.packages("getTBinR")
library(getTBinR)
# install.packages("tidyverse")
library(tidyverse)
# Get the data
tb_burden <- get_tb_burden(download_data = TRUE, save = TRUE)
dict <- get_data_dict(download_data = TRUE, save = TRUE)
# Look up variables with mortality in their definition
search_data_dict(def = "incidence")
# Map incidence rates in 2016
map_tb_burden(metric = "e_inc_100k", year = 2016)
# Get countries with highest incidence rates in the data
high_inc_countries <- tb_burden %>%
filter(year == 2016) %>%
group_by(country) %>%
summarise(e_inc_100k = max(e_inc_100k)) %>%
ungroup %>%
arrange(desc(e_inc_100k)) %>%
slice(1:20) %>%
pull(country) %>%
unique
#Overview of 20 countries with incidence rates
plot_tb_burden_overview(metric = "e_inc_100k",
countries = high_inc_countries)
# Trends over time in incidence rates by country for countries with highest incidence rates
plot_tb_burden(countries = high_inc_countries,
facet = "country", scales = "free_y")
# Trends over time in mortality rates (exc HIV) by country
plot_tb_burden(metric = "e_mort_exc_tbhiv_100k",
countries = high_inc_countries,
facet = "country", scales = "free_y")
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