Software

R packages and interactive Shiny applications for spatial statistics and global health.

I develop open-source software that makes model-based geostatistics and spatial epidemiology methods accessible to researchers, students, and public-health practitioners. Everything below is free and open source.

R packages

SDALGCP

An R package for spatially continuous inference with spatially aggregated disease count data, using a low-rank approximation to the log-Gaussian Cox process for computational efficiency.

remotes::install_github("olatunjijohnson/SDALGCP")

GitHub

ESPENAPI

An R package for downloading Neglected Tropical Disease (NTD) data directly from the WHO ESPEN portal API and the WHO Global Health Observatory, returning tidy data frames ready for analysis.

remotes::install_github("olatunjijohnson/ESPENAPI")

GitHub

MBGapp

An R package and Shiny application for teaching model-based geostatistics, walking learners through the full workflow: exploration → variogram → model fitting → prediction. Published in PLOS ONE (2021).

remotes::install_github("olatunjijohnson/MBGapp")

GitHub Launch app Paper

variogramApp

An R package and Shiny application for interactively exploring variograms and Gaussian random fields — a hands-on teaching tool for understanding spatial correlation across twelve covariance models.

remotes::install_github("olatunjijohnson/variogramApp")

GitHub Launch app

Shiny applications

MBGapp

Interactive model-based geostatistics for population-health scientists, using a Loa loa case study. Runs entirely in the browser — no R installation needed.

Launch app GitHub

variogramApp

Explore how covariance-model parameters shape the variogram and simulate Gaussian random fields in one or two dimensions. Ideal for classroom use — share the URL or a QR code.

Launch app GitHub

LEBLiverpool

A Shiny application visualising Life Expectancy at Birth (LEB) across Liverpool, UK, illustrating small-area health inequalities.

GitHub


All code is released under open-source licences. Contributions, bug reports, and feature requests are welcome via the GitHub repositories above.