MBGapp: A Shiny application for teaching model-based geostatistics to population health scientists

Olatunji Johnson; Claudio Fronterre; Peter J Diggle; Benjamin Amoah; Emanuele Giorgi

doi:10.1371/journal.pone.0262145

MBGapp: A Shiny application for teaching model-based geostatistics to population health scientists

PLoS One. 2021 Dec 31;16(12):e0262145. doi: 10.1371/journal.pone.0262145. eCollection 2021.

Authors

Olatunji Johnson^{1

2}, Claudio Fronterre¹, Peter J Diggle¹, Benjamin Amoah¹, Emanuele Giorgi¹

Affiliations

¹ CHICAS, Lancaster Medical School, Lancaster University, Lancaster, United Kingdom.
² Department of Mathematics, University of Manchester, Manchester, United Kingdom.

Abstract

User-friendly interfaces have been increasingly used to facilitate the learning of advanced statistical methodology, especially for students with only minimal statistical training. In this paper, we illustrate the use of MBGapp for teaching geostatistical analysis to population health scientists. Using a case-study on Loa loa infections, we show how MBGapp can be used to teach the different stages of a geostatistical analysis in a more interactive fashion. For wider accessibility and usability, MBGapp is available as an R package and as a Shiny web-application that can be freely accessed on any web browser. In addition to MBGapp, we also present an auxiliary Shiny app, called VariagramApp, that can be used to aid the teaching of Gaussian processes in one and two dimensions using simulations.

Publication types

Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

Algorithms
Cameroon
Geography
Humans
Learning
Models, Statistical
Monte Carlo Method
Normal Distribution
Poisson Distribution
Population Dynamics*
Population Health*
Prevalence
Reproducibility of Results
Software
Statistics as Topic
Web Browser

Grants and funding

This work received financial support from the Coalition for Operational Research on Neglected Tropical Diseases, which is funded at The Task Force for Global Health 408 primarily by the Bill & Melinda Gates Foundation, by the United States Agency for International Development through its Neglected Tropical Diseases Program, and with UK aid from the British people (NTD-SC ID 026.2G). This is an open-access article distributed under the terms of the Creative Commons Attribution (CC-BY) License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. This work was also supported by funding through the NTD Modelling Consortium (OPP1184344) by Bill and Melinda Gates Foundation. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.