Health Metrics and the Spread of Infectious Diseases

A collection of datasets and supporting functions accompanying Health Metrics and the Spread of Infectious Diseases by Federica Gazzelloni (2024). This package provides data for health metrics calculations, including Disability-Adjusted Life Years (DALYs), Years of Life Lost (YLLs), and Years Lived with Disability (YLDs), as well as additional tools for analyzing and visualizing health data. Federica Gazzelloni (2024) .

hmsidwR - Health Metrics and the Spread of Infectious Diseases

The goal of {hmsidwR} is to provide the set of data used in the Health Metrics and the Spread of Infectious Diseases Machine Learning Applications and Spatial Modeling Analysis book.

Installation

install.packages("hmsidwR")

You can install the development version of hmsidwR from GitHub with:

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

Example

This is a basic example which shows you how to solve a common problem:

library(hmsidwR)
library(dplyr)
data(sdi90_19)
head(subset(sdi90_19, location == "Global"))
#> # 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

sdi_avg <- sdi90_19 |>
  group_by(location) |>
  reframe(sdi_avg = round(mean(value), 3))

head(sdi_avg)
#> # A tibble: 6 × 2
#>   location       sdi_avg
#>   <chr>            <dbl>
#> 1 Aceh             0.58 
#> 2 Acre             0.465
#> 3 Afghanistan      0.238
#> 4 Aguascalientes   0.606
#> 5 Aichi            0.846
#> 6 Akita            0.792

sdi90_19 |>
  filter(location %in% c("Global", "Italy", "France", "Germany")) |>
  group_by(location) |>
  reframe(sdi_avg = round(mean(value), 3)) |>
  head()
#> # A tibble: 4 × 2
#>   location sdi_avg
#>   <chr>      <dbl>
#> 1 France     0.79 
#> 2 Germany    0.863
#> 3 Global     0.58 
#> 4 Italy      0.763