---
title: "Welcome to hmsidwR!"
description: "this package is supporting the book"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{hmsidwR}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  message = FALSE,
  warning = FALSE
)

options(rmarkdown.html_vignette.check_title = FALSE)
```

## Setup
```{r eval=FALSE}
# install.packages("devtools")
devtools::install_github("Fgazzelloni/hmsidwR")
```


```{r}
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

```{r}
hmsidwR::sdi90_19 |>
  head()
```


```{r}
hmsidwR::deaths2019 |>
  head()
```

## Make a Plot

```{r}
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)
```