Accesing Clean UNAIDS Data

Introduction

This vignette covers how to access the clean and tidy annual UNAIDS Estimates from GitHub Releases. The MindTheGap package uses a cleaning function (munge_unaids) to process, munge, and tidy the UNAIDS HIV Estimates from AIDSInfo and pull_unaids to pull the cleaned data from Google Drive.

Let’s start by loading the MindTheGap package.

library(mindthegap)
library(glamr) #install.packages('glamr', repos = c('https://usaid-oha-si.r-universe.dev', getOption("repos")))
library(knitr)

Pull clean data from GitHub Releases

With munge_unaids, the developer is left with a clean and tidy dataset that includes a pepfar flag to denote whether a country is a PEPFAR country or not and an estimate_flag to indicate estimates that are an approximation (previously contained a “<”). In order to make this data accessible outside of R and cut down on the processing time, we uploaded the clean UNAIDS data to the package releases and wrote the function pull_unaids for users to easily access this data.

To use pull_unaids, there are 2 parameters:

1. data_type: This parameter returns one of the 2 datasets: “HIV Estimates” or “HIV Test & Treat”. Please note that if you want to filter to a specific indicator type (i.e. Percent or Integer), you will have to add that filter to your code filter(indic_type == "Integer").

2. pepfar_only: if TRUE, this parameter will return a dataset of only PEPFAR countries. If you do not specify this parameter, it will default to TRUE.

In order to access the data from GitHub releases, be sure to load the glamr package to run the pull_unaids function.

df_est <- pull_unaids(data_type = "HIV Estimates", pepfar_only = TRUE)

kable(head(df_est), format = "html")

year	iso	country	region	indicator	age	sex	estimate	lower_bound	upper_bound	estimate_flag	sheet	indic_type	pepfar	achv_95_plhiv	achv_95_relative	epi_ratio_2023	epi_control
1990	KHM	Cambodia	Asia and the Pacific	Number AIDS Related Deaths	All	All	100	100	100	TRUE	HIV Estimates	Integer	TRUE	FALSE	FALSE	0.7608939	TRUE
1990	KHM	Cambodia	Asia and the Pacific	Number AIDS Related Deaths	0-14	All	100	100	100	TRUE	HIV Estimates	Integer	TRUE	FALSE	FALSE	0.7608939	TRUE
1990	KHM	Cambodia	Asia and the Pacific	Number AIDS Related Deaths	15+	All	100	100	100	TRUE	HIV Estimates	Integer	TRUE	FALSE	FALSE	0.7608939	TRUE
1990	KHM	Cambodia	Asia and the Pacific	Number PLHIV	0-14	All	100	100	100	TRUE	HIV Estimates	Integer	TRUE	FALSE	FALSE	0.7608939	TRUE
1990	KHM	Cambodia	Asia and the Pacific	Number PLHIV	15+	Female	200	200	200	TRUE	HIV Estimates	Integer	TRUE	FALSE	FALSE	0.7608939	TRUE
1990	KHM	Cambodia	Asia and the Pacific	Number PLHIV	15+	All	500	500	500	TRUE	HIV Estimates	Integer	TRUE	FALSE	FALSE	0.7608939	TRUE