Journal of Statistical Software (May 2023)

disaggregation: An R Package for Bayesian Spatial Disaggregation Modeling

  • Anita K. Nandi,
  • Tim C. D. Lucas,
  • Rohan Arambepola,
  • Peter Gething,
  • Daniel J. Weiss

DOI
https://doi.org/10.18637/jss.v106.i11
Journal volume & issue
Vol. 106
pp. 1 – 19

Abstract

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Disaggregation modeling, or downscaling, has become an important discipline in epidemiology. Surveillance data, aggregated over large regions, is becoming more common, leading to an increasing demand for modeling frameworks that can deal with this data to understand spatial patterns. Disaggregation regression models use response data aggregated over large heterogeneous regions to make predictions at fine-scale over the region by using fine-scale covariates to inform the heterogeneity. This paper presents the R package disaggregation, which provides functionality to streamline the process of running a disaggregation model for fine-scale predictions.

Keywords