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Welcome to hmsidwR!

Setup

# install.packages("devtools")
devtools::install_github("Fgazzelloni/hmsidwR")
library(hmsidwR)

This package provides the set of data used in the Health Metrics and the Spread of Infectious Diseases Machine Learning Applications and Spatial Modeling Analysis book.

Load Sample Data

hmsidwR::sdi90_19 |>
  head()
#> # A tibble: 6 × 3
#>   location  year value
#>   <chr>    <dbl> <dbl>
#> 1 Global    1990 0.511
#> 2 Global    1991 0.516
#> 3 Global    1992 0.521
#> 4 Global    1993 0.525
#> 5 Global    1994 0.529
#> 6 Global    1995 0.534
hmsidwR::deaths2019 |>
  head()
#> # A tibble: 6 × 7
#>   location sex    age   cause                           dx upper  lower
#>   <chr>    <chr>  <ord> <chr>                        <dbl> <dbl>  <dbl>
#> 1 UK       male   <1    Lower respiratory infections 39.7  51.0  29.5  
#> 2 UK       female <1    Lower respiratory infections 30.0  38.0  22.6  
#> 3 UK       both   <1    Lower respiratory infections 69.7  88.3  53.3  
#> 4 UK       male   <1    Stroke                        1.33  2.41  0.850
#> 5 UK       female <1    Stroke                        1.04  1.84  0.669
#> 6 UK       both   <1    Stroke                        2.38  4.21  1.55

Make a Plot

library(tidyverse)
id <- hmsidwR::id_affected_countries %>%
  ggplot(aes(
    x = year,
    group = location_name
  )) +
  geom_line(aes(y = YLLs),
    linewidth = 0.2,
    color = "grey"
  ) +
  geom_line(
    data = id_affected_countries %>%
      filter(location_name %in% c(
        "Lesotho",
        "Eswatini",
        "Malawi",
        "Central African Republic",
        "Zambia"
      )),
    aes(y = YLLs, color = location_name)
  ) +
  theme_minimal() +
  theme(legend.position = "none") +
  labs(
    title = "Countries with highest AVG YLLs",
    subtitle = "due to infectious diseases from 1990 to 2021",
    caption = "DataSource: IHME GBD Results for infectious diseases deaths and YLLs 1980 to 1999",
    x = "Year", y = "DALYs"
  )
# add a plotly version
library(plotly)
plotly::ggplotly(id)

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.