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DIVINE

DIVINE is an R package that provides 14 curated datasets and 6 intuitive data management functions to streamline epidemiological data workflows.

It is designed to support researchers in quickly accessing clean, structured data and applying essential cleaning, summarizing, visualization, and export operations with minimal effort.

Whether you’re preparing a cohort for analysis or creating reports, DIVINE makes the process more efficient, transparent, and reproducible.

📦 Installation

Install the development version from GitHub with:

# install.packages("pak")
pak::pak("bruigtp/DIVINE")

🗂️ Included Datasets

DIVINE includes 14 real-world structured datasets, commonly used in longitudinal and hospital-based research:

analytics
end_followup
complications
comorbidities
demographic
symptoms
scores
vital_signs
concomitant_medicat
inhosp_other_treatments
icu
vaccine
inhosp_antivirals
inhosp_antibiotics

To list them inside R:

data(package = "DIVINE")

To load one:

data("demographic")
head(demographic)

⚙️ Core Functions

DIVINE includes 6 functions that follow a typical data preparation pipeline:

Step	Function	Description
Inspect data	`data_overview()`	Get a high-level summary (structure, missingness, preview)
Handle missing values	`impute_missing()`	Replace `NA`s using mean, median, mode, or a fixed value
Merge datasets	`multi_join()`	Join multiple datasets by a common key
Summarize tables	`stats_table()`	Create descriptive tables with gtsummary (mean/median + p-values)
Visualize data	`multi_plot()`	Plot histograms, boxplots, densities, radar charts, etc.
Export results	`export_data()`	Export to CSV, Excel, RDS, SPSS, Stata, or SAS

📖 Vignette

Read the full walkthrough with all examples:

vignette("DIVINE")

Or view online: https://bruigtp.github.io/DIVINE/articles/DIVINE.html

Citation

If you use these data, please cite the DIVINE study and the relevant publication:

Pallarès N., Tebé C., Abelenda-Alonso G., Rombauts A., Oriol I., Simonetti A. F., Rodríguez-Molinero A., Izquierdo E., Díaz-Brito V., Molist G., Gómez Melis G., Carratalà J., Videla S., & MetroSud and DIVINE study groups (2023). Characteristics and Outcomes by Ceiling of Care of Subjects Hospitalized with COVID-19 During Four Waves of the Pandemic in a Metropolitan Area: A Multicenter Cohort Study. Infectious Diseases and Therapy, 12(1), 273–289. https://doi.org/10.1007/s40121-022-00705-w

🤝 Contributing

If you encounter a bug, please file an issue with a minimal reproducible example on GitHub.

About

Package: DIVINE

Authors: Natàlia Pallarès, João Carmezim, Pau Satorra, Cristian Tebé.

Maintainer: João Carmezim

License: GPL (>= 3)

Encoding: UTF-8

Depends: R (>= 4.1.0)

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.