# 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)