Reproducing maps from Our World in Data: Mental Health

I will plot the global prevalence of anxiety disorders with data from Institute of Health Metrics & Evaluation (IHME). Inspiration is drawn from Our World in Data

# Data cleaning
ihme_percent <- ihme_raw %>% 
  filter(metric == "Percent") %>% 
  select(location, cause, year, val, upper, lower)

iso3166_revised <- maps::iso3166 %>% 
  mutate(ISOname = case_when(
    ISOname == "United States" ~ "United States of America",
    ISOname == "Bolivia, Plurinational State of" ~ "Bolivia",
    ISOname == "Venezuela, Bolivarian Republic of" ~ "Venezuela",
    ISOname == "United Kingdom of Great Britain and Northern Ireland" ~ "United Kingdom",
    ISOname == "Iran, Islamic Republic of" ~ "Iran",
    ISOname == "Lao People's Democratic Republic" ~ "Laos",
    ISOname == "Tanzania, United Republic of" ~ "Tanzania",
    TRUE ~ ISOname
  ))

world_data <- ihme_percent %>% 
  filter(cause == "Anxiety disorders") %>% 
  mutate(location = case_when(
    location == "Bolivia (Plurinational State of)" ~ "Bolivia",
    location == "Venezuela (Bolivarian Republic of)" ~ "Venezuela",
    location == "Iran (Islamic Republic of)" ~ "Iran",
    location == "Viet Nam" ~ "Vietnam",
    location == "Lao People's Democratic Republic" ~ "Laos",
    location == "Taiwan (Province of China)" ~ "Taiwan",
    TRUE ~ location
  )) %>% 
  inner_join(iso3166_revised, by = c(location = "ISOname"))

final_df <- map_data("world") %>% 
  as_tibble() %>% 
  filter(region != "Antarctica") %>%
  mutate(region = case_when(
    region == "Russia" ~ "Russian Federation",
    region == "USA" ~ "United States of America",
    region == "South Korea" ~ "Republic of Korea",
    region == "North Korea" ~ "Democratic People's Republic of Korea",
    region == "UK" ~ "United Kingdom",
    TRUE ~ region
  )) %>% 
  regex_left_join(world_data, by = c("region" = "location")) %>%
  filter(!is.na(year)) %>%
  # Take out unnecessary columns
  select(-order, -region, -subregion, -location, 
         -cause, -upper, -lower, -a2, -a3, -mapname,
         -sovereignty)

# Animate
final_df %>% 
  ggplot(aes(long, lat, group = group, fill = val)) +
  geom_polygon() +
  geom_polygon(color = "black", alpha = 0.4) +
  transition_time(year) +
  scale_fill_gradient2(low = "lightgreen", high = "forestgreen", midpoint = 0.05, na.value = "grey",
                       labels = scales::percent) +
  theme_map() +
  theme(legend.position = "bottom",
        text = element_text(size = 12,  family="Palatino")) +
  labs(fill = "Prevalence of Anxiety Disorders",
       title = "Global Prevalence of Anxiety Disorder in {round(frame_time, 0)}",
       subtitle = "Share of population with an anxiety disorder. Figures attempt to provide a true estimate (going beyond
reported diagnosis) of anxiety disorder prevalence based on medical, epidemiological data, surveys and
meta-regression modelling.",
caption = "Source: Our World in Data / IHME, Global Burden of Disease")